Merge pull request #484 from PyPSA/merge-pypsa-eur-sec
Merge pypsa eur sec
This commit is contained in:
Fabian Neumann
GitHub
commit
4a61faf737
@ -5,3 +5,4 @@
|
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# Exclude pre-commit applications
|
||||
5d1ef8a64055a039aa4a0834d2d26fe7752fe9a0
|
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92080b1cd2ca5f123158571481722767b99c2b27
|
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13769f90af4500948b0376d57df4cceaa13e78b5
|
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|
||||
8
.github/pull_request_template.md
vendored
8
.github/pull_request_template.md
vendored
@ -7,7 +7,7 @@ Closes # (if applicable).
|
||||
|
||||
- [ ] I tested my contribution locally and it seems to work fine.
|
||||
- [ ] Code and workflow changes are sufficiently documented.
|
||||
- [ ] Newly introduced dependencies are added to `envs/environment.yaml` and `envs/environment.docs.yaml`.
|
||||
- [ ] Changes in configuration options are added in all of `config.default.yaml`, `config.tutorial.yaml`, and `test/config.test1.yaml`.
|
||||
- [ ] Changes in configuration options are also documented in `doc/configtables/*.csv` and line references are adjusted in `doc/configuration.rst` and `doc/tutorial.rst`.
|
||||
- [ ] A note for the release notes `doc/release_notes.rst` is amended in the format of previous release notes.
|
||||
- [ ] Changed dependencies are added to `envs/environment.yaml`.
|
||||
- [ ] Changes in configuration options are added in all of `config.default.yaml`.
|
||||
- [ ] Changes in configuration options are also documented in `doc/configtables/*.csv`.
|
||||
- [ ] A release note `doc/release_notes.rst` is added.
|
||||
|
||||
42
.github/workflows/ci.yaml
vendored
42
.github/workflows/ci.yaml
vendored
@ -1,4 +1,4 @@
|
||||
# SPDX-FileCopyrightText: : 2021 The PyPSA-Eur Authors
|
||||
# SPDX-FileCopyrightText: : 2021-2023 The PyPSA-Eur Authors
|
||||
#
|
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# SPDX-License-Identifier: CC0-1.0
|
||||
|
||||
@ -19,12 +19,14 @@ on:
|
||||
- cron: "0 5 * * TUE"
|
||||
|
||||
env:
|
||||
CACHE_NUMBER: 1 # Change this value to manually reset the environment cache
|
||||
CONDA_CACHE_NUMBER: 1 # Change this value to manually reset the environment cache
|
||||
DATA_CACHE_NUMBER: 2
|
||||
|
||||
jobs:
|
||||
build:
|
||||
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
include:
|
||||
# Matrix required to handle caching with Mambaforge
|
||||
@ -49,16 +51,12 @@ jobs:
|
||||
shell: bash -l {0}
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v2
|
||||
- uses: actions/checkout@v3
|
||||
|
||||
- name: Setup secrets
|
||||
run: |
|
||||
echo -ne "url: ${CDSAPI_URL}\nkey: ${CDSAPI_TOKEN}\n" > ~/.cdsapirc
|
||||
|
||||
- name: Add solver to environment
|
||||
run: |
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||||
echo -e "- glpk\n- ipopt" >> envs/environment.yaml
|
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|
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- name: Add solver to environment
|
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run: |
|
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echo -e "- glpk\n- ipopt<3.13.3" >> envs/environment.yaml
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@ -77,15 +75,25 @@ jobs:
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activate-environment: pypsa-eur
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use-mamba: true
|
||||
|
||||
- name: Set cache date
|
||||
run: echo "DATE=$(date +'%Y%m%d')" >> $GITHUB_ENV
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- name: Set cache dates
|
||||
run: |
|
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echo "DATE=$(date +'%Y%m%d')" >> $GITHUB_ENV
|
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echo "WEEK=$(date +'%Y%U')" >> $GITHUB_ENV
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|
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- name: Cache data and cutouts folders
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uses: actions/cache@v3
|
||||
with:
|
||||
path: |
|
||||
data
|
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cutouts
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key: data-cutouts-${{ env.WEEK }}-${{ env.DATA_CACHE_NUMBER }}
|
||||
|
||||
- name: Create environment cache
|
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uses: actions/cache@v3
|
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id: cache
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with:
|
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path: ${{ matrix.prefix }}
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||||
key: ${{ matrix.label }}-conda-${{ hashFiles('envs/environment.yaml') }}-${{ env.DATE }}-${{ env.CACHE_NUMBER }}
|
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key: ${{ matrix.label }}-conda-${{ env.DATE }}-${{ env.CONDA_CACHE_NUMBER }}
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|
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- name: Update environment due to outdated or unavailable cache
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run: mamba env update -n pypsa-eur -f envs/environment.yaml
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@ -95,4 +103,16 @@ jobs:
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run: |
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conda activate pypsa-eur
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conda list
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snakemake -call solve_all_networks --configfile test/config.test1.yaml
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snakemake -call solve_elec_networks --configfile test/config.electricity.yaml --rerun-triggers=mtime
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snakemake -call all --configfile test/config.overnight.yaml --rerun-triggers=mtime
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snakemake -call all --configfile test/config.myopic.yaml --rerun-triggers=mtime
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|
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- name: Upload artifacts
|
||||
uses: actions/upload-artifact@v3
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with:
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name: resources-results
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path: |
|
||||
resources
|
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results
|
||||
if-no-files-found: warn
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retention-days: 1
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|
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51
.gitignore
vendored
51
.gitignore
vendored
@ -11,18 +11,65 @@ gurobi.log
|
||||
|
||||
/bak
|
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/resources
|
||||
/resources*
|
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/results
|
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/networks
|
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/benchmarks
|
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/logs
|
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/notebooks
|
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/data
|
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/data/links_p_nom.csv
|
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/cutouts
|
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/dask-worker-space
|
||||
|
||||
doc/_build
|
||||
|
||||
config.yaml
|
||||
|
||||
dconf
|
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/data/links_p_nom.csv
|
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/data/*totals.csv
|
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/data/biomass*
|
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/data/emobility/
|
||||
/data/eea*
|
||||
/data/jrc*
|
||||
/data/heating/
|
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/data/eurostat*
|
||||
/data/odyssee/
|
||||
/data/transport_data.csv
|
||||
/data/switzerland*
|
||||
/data/.nfs*
|
||||
/data/Industrial_Database.csv
|
||||
/data/retro/tabula-calculator-calcsetbuilding.csv
|
||||
/data/nuts*
|
||||
data/gas_network/scigrid-gas/
|
||||
data/costs_*.csv
|
||||
|
||||
dask-worker-space/
|
||||
publications.jrc.ec.europa.eu/
|
||||
|
||||
*.org
|
||||
|
||||
*.nc
|
||||
|
||||
*~
|
||||
/scripts/old
|
||||
|
||||
*.pyc
|
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/cutouts
|
||||
/tmp
|
||||
/pypsa
|
||||
|
||||
*.xlsx
|
||||
|
||||
config.yaml
|
||||
|
||||
doc/_build
|
||||
|
||||
*.xls
|
||||
|
||||
*.geojson
|
||||
|
||||
*.ipynb
|
||||
|
||||
data/costs_*
|
||||
|
||||
merger-todos.md
|
||||
|
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@ -30,10 +30,10 @@ repos:
|
||||
|
||||
# Find common spelling mistakes in comments and docstrings
|
||||
- repo: https://github.com/codespell-project/codespell
|
||||
rev: v2.2.2
|
||||
rev: v2.2.4
|
||||
hooks:
|
||||
- id: codespell
|
||||
args: ['--ignore-regex="(\b[A-Z]+\b)"', '--ignore-words-list=fom'] # Ignore capital case words, e.g. country codes
|
||||
args: ['--ignore-regex="(\b[A-Z]+\b)"', '--ignore-words-list=fom,appartment,bage,ore,setis,tabacco,berfore'] # Ignore capital case words, e.g. country codes
|
||||
types_or: [python, rst, markdown]
|
||||
files: ^(scripts|doc)/
|
||||
|
||||
@ -74,7 +74,7 @@ repos:
|
||||
|
||||
# Format Snakemake rule / workflow files
|
||||
- repo: https://github.com/snakemake/snakefmt
|
||||
rev: v0.8.1
|
||||
rev: v0.8.2
|
||||
hooks:
|
||||
- id: snakefmt
|
||||
|
||||
@ -85,7 +85,7 @@ repos:
|
||||
- id: jupyter-notebook-cleanup
|
||||
exclude: examples/solve-on-remote.ipynb
|
||||
|
||||
# Check for FSFE REUSE compliance (licensing)
|
||||
# Check for FSFE REUSE compliance (licensing)
|
||||
- repo: https://github.com/fsfe/reuse-tool
|
||||
rev: v1.1.2
|
||||
hooks:
|
||||
|
||||
20
.reuse/dep5
20
.reuse/dep5
@ -1,14 +1,18 @@
|
||||
Format: https://www.debian.org/doc/packaging-manuals/copyright-format/1.0/
|
||||
Upstream-Name: PyPSA-Eur
|
||||
Upstream-Contact: Tom Brown <tom.brown@kit.edu>
|
||||
Upstream-Contact: Tom Brown <t.brown@tu-berlin.de>
|
||||
Source: https://github.com/pypsa/pypsa-eur
|
||||
|
||||
Files: doc/img/*
|
||||
Copyright: 2019 Fabian Neumann (TUB, KIT)
|
||||
Copyright: 2019-2023 The PyPSA-Eur Authors
|
||||
License: CC-BY-4.0
|
||||
|
||||
Files: doc/data.csv
|
||||
Copyright: 2019-2023 The PyPSA-Eur Authors
|
||||
License: CC-BY-4.0
|
||||
|
||||
Files: doc/configtables/*
|
||||
Copyright: 2019 Fabian Neumann (TUB, KIT)
|
||||
Copyright: 2019-2023 The PyPSA-Eur Authors
|
||||
License: CC-BY-4.0
|
||||
|
||||
Files: data/*
|
||||
@ -16,13 +20,17 @@ Copyright: 2017-2023 The PyPSA-Eur Authors
|
||||
License: CC-BY-4.0
|
||||
|
||||
Files: .github/*
|
||||
Copyright: 2019 The PyPSA-Eur Authors
|
||||
Copyright: 2019-2023 The PyPSA-Eur Authors
|
||||
License: CC0-1.0
|
||||
|
||||
Files: matplotlibrc
|
||||
Copyright: : 2017-2023 The PyPSA-Eur Authors
|
||||
Copyright: 2017-2023 The PyPSA-Eur Authors
|
||||
License: CC0-1.0
|
||||
|
||||
Files: borg-it
|
||||
Copyright: : 2017-2023 The PyPSA-Eur Authors
|
||||
Copyright: 2017-2023 The PyPSA-Eur Authors
|
||||
License: CC0-1.0
|
||||
|
||||
Files: graphics/*
|
||||
Copyright: 2017-2023 The PyPSA-Eur Authors
|
||||
License: CC-BY-4.0
|
||||
|
||||
@ -1,4 +1,4 @@
|
||||
# SPDX-FileCopyrightText: : 2021 The PyPSA-Eur Authors
|
||||
# SPDX-FileCopyrightText: : 2021-2023 The PyPSA-Eur Authors
|
||||
#
|
||||
# SPDX-License-Identifier: CC0-1.0
|
||||
|
||||
@ -15,5 +15,6 @@ __pycache__
|
||||
notebooks
|
||||
doc
|
||||
cutouts
|
||||
data/bundle
|
||||
data
|
||||
benchmarks
|
||||
*.nc
|
||||
|
||||
@ -1,4 +1,4 @@
|
||||
# SPDX-FileCopyrightText: : 2021 The PyPSA-Eur Authors
|
||||
# SPDX-FileCopyrightText: : 2021-2023 The PyPSA-Eur Authors
|
||||
#
|
||||
# SPDX-License-Identifier: CC0-1.0
|
||||
|
||||
|
||||
79
README.md
79
README.md
@ -7,42 +7,54 @@ SPDX-License-Identifier: CC-BY-4.0
|
||||
[](https://github.com/PyPSA/pypsa-eur/actions)
|
||||
[](https://pypsa-eur.readthedocs.io/en/latest/?badge=latest)
|
||||
|
||||
[](https://doi.org/10.5281/zenodo.3520874)
|
||||
[](https://doi.org/10.5281/zenodo.3520874)
|
||||
[](https://doi.org/10.5281/zenodo.3938042)
|
||||
[](https://snakemake.readthedocs.io)
|
||||
[](https://api.reuse.software/info/github.com/pypsa/pypsa-eur)
|
||||
|
||||
# PyPSA-Eur: An Open Optimisation Model of the European Transmission System
|
||||
# PyPSA-Eur: A Sector-Coupled Open Optimisation Model of the European Energy System
|
||||
|
||||
|
||||
PyPSA-Eur is an open model dataset of the European power system at the
|
||||
transmission network level that covers the full ENTSO-E area.
|
||||
The model is suitable both for operational studies and generation and transmission expansion planning studies.
|
||||
PyPSA-Eur is an open model dataset of the European energy system at the
|
||||
transmission network level that covers the full ENTSO-E area. The model is suitable both for operational studies and generation and transmission expansion planning studies.
|
||||
The continental scope and highly resolved spatial scale enables a proper description of the long-range
|
||||
smoothing effects for renewable power generation and their varying resource availability.
|
||||
|
||||
|
||||
|
||||
|
||||
The model is described in the [documentation](https://pypsa-eur.readthedocs.io)
|
||||
and in the paper
|
||||
[PyPSA-Eur: An Open Optimisation Model of the European Transmission
|
||||
System](https://arxiv.org/abs/1806.01613), 2018,
|
||||
[arXiv:1806.01613](https://arxiv.org/abs/1806.01613).
|
||||
The model building routines are defined through a snakemake workflow.
|
||||
Please see the [documentation](https://pypsa-eur.readthedocs.io/)
|
||||
for installation instructions and other useful information about the snakemake workflow.
|
||||
The model is designed to be imported into the open toolbox
|
||||
[PyPSA](https://github.com/PyPSA/PyPSA).
|
||||
|
||||
**WARNING**: PyPSA-Eur is under active development and has several
|
||||
[limitations](https://pypsa-eur.readthedocs.io/en/latest/limitations.html)
|
||||
which you should understand before using the model. The github repository
|
||||
[issues](https://github.com/PyPSA/pypsa-eur/issues) collect known topics we are
|
||||
working on (please feel free to help or make suggestions). The
|
||||
[documentation](https://pypsa-eur.readthedocs.io/) remains somewhat patchy. You
|
||||
can find showcases of the model's capabilities in the preprint [Benefits of a
|
||||
Hydrogen Network in Europe](https://arxiv.org/abs/2207.05816), a [paper in Joule
|
||||
with a description of the industry sector](https://arxiv.org/abs/2109.09563), or
|
||||
in [a 2021 presentation at EMP-E](https://nworbmot.org/energy/brown-empe.pdf).
|
||||
We cannot support this model if you choose to use it. We do not recommend to use
|
||||
the full resolution network model for simulations. At high granularity the
|
||||
assignment of loads and generators to the nearest network node may not be a
|
||||
correct assumption, depending on the topology of the underlying distribution
|
||||
grid, and local grid bottlenecks may cause unrealistic load-shedding or
|
||||
generator curtailment. We recommend to cluster the network to a couple of
|
||||
hundred nodes to remove these local inconsistencies. See the discussion in
|
||||
Section 3.4 "Model validation" of the paper.
|
||||
|
||||
**WARNING**: Please read the [limitations](https://pypsa-eur.readthedocs.io/en/latest/limitations.html) section of the
|
||||
documentation and paper carefully before using the model. We do not
|
||||
recommend to use the full resolution network model for simulations. At
|
||||
high granularity the assignment of loads and generators to the nearest
|
||||
network node may not be a correct assumption, depending on the topology of the underlying distribution grid,
|
||||
and local grid
|
||||
bottlenecks may cause unrealistic load-shedding or generator
|
||||
curtailment. We recommend to cluster the network to a couple of
|
||||
hundred nodes to remove these local inconsistencies. See the
|
||||
discussion in Section 3.4 "Model validation" of the paper.
|
||||
|
||||
|
||||
|
||||
The model building routines are defined through a snakemake workflow. The model is designed to be imported into the open toolbox
|
||||
[PyPSA](https://github.com/PyPSA/PyPSA) for operational studies as
|
||||
well as generation and transmission expansion planning studies.
|
||||
|
||||
The dataset consists of:
|
||||
|
||||
- A grid model based on a modified [GridKit](https://github.com/bdw/GridKit)
|
||||
@ -57,9 +69,30 @@ The dataset consists of:
|
||||
- Renewable time series based on ERA5 and SARAH, assembled using the [atlite tool](https://github.com/FRESNA/atlite).
|
||||
- Geographical potentials for wind and solar generators based on land use (CORINE) and excluding nature reserves (Natura2000) are computed with the [atlite library](https://github.com/PyPSA/atlite).
|
||||
|
||||
A sector-coupled extension adds demand
|
||||
and supply for the following sectors: transport, space and water
|
||||
heating, biomass, industry and industrial feedstocks, agriculture,
|
||||
forestry and fishing. This completes the energy system and includes
|
||||
all greenhouse gas emitters except waste management and land use.
|
||||
|
||||
This diagram gives an overview of the sectors and the links between
|
||||
them:
|
||||
|
||||
|
||||
|
||||
Each of these sectors is built up on the transmission network nodes
|
||||
from [PyPSA-Eur](https://github.com/PyPSA/pypsa-eur):
|
||||
|
||||
|
||||
|
||||
For computational reasons the model is usually clustered down
|
||||
to 50-200 nodes.
|
||||
|
||||
Already-built versions of the model can be found in the accompanying [Zenodo
|
||||
repository](https://doi.org/10.5281/zenodo.3601881).
|
||||
# Licence
|
||||
|
||||
A version of the model that adds building heating, transport and
|
||||
industry sectors to the model, as well as gas networks, can be found
|
||||
in the [PyPSA-Eur-Sec](https://github.com/PyPSA/pypsa-eur-sec) repository.
|
||||
The code in PyPSA-Eur is released as free software under the
|
||||
[MIT License](https://opensource.org/licenses/MIT), see `LICENSE.txt`.
|
||||
However, different licenses and terms of use may apply to the various
|
||||
input data.
|
||||
|
||||
733
Snakefile
733
Snakefile
@ -3,12 +3,17 @@
|
||||
# SPDX-License-Identifier: MIT
|
||||
|
||||
from os.path import normpath, exists
|
||||
from shutil import copyfile, move
|
||||
from shutil import copyfile, move, rmtree
|
||||
|
||||
from snakemake.remote.HTTP import RemoteProvider as HTTPRemoteProvider
|
||||
|
||||
HTTP = HTTPRemoteProvider()
|
||||
|
||||
from snakemake.utils import min_version
|
||||
|
||||
min_version("7.7")
|
||||
|
||||
|
||||
if not exists("config.yaml"):
|
||||
copyfile("config.default.yaml", "config.yaml")
|
||||
|
||||
@ -16,700 +21,80 @@ if not exists("config.yaml"):
|
||||
configfile: "config.yaml"
|
||||
|
||||
|
||||
COSTS = f"data/costs_{config['costs']['year']}.csv"
|
||||
ATLITE_NPROCESSES = config["atlite"].get("nprocesses", 4)
|
||||
|
||||
run = config.get("run", {})
|
||||
RDIR = run["name"] + "/" if run.get("name") else ""
|
||||
CDIR = RDIR if not run.get("shared_cutouts") else ""
|
||||
|
||||
COSTS = "resources/" + RDIR + "costs.csv"
|
||||
ATLITE_NPROCESSES = config["atlite"].get("nprocesses", 4)
|
||||
LOGS = "logs/" + RDIR
|
||||
BENCHMARKS = "benchmarks/" + RDIR
|
||||
RESOURCES = "resources/" + RDIR if not run.get("shared_resources") else "resources/"
|
||||
RESULTS = "results/" + RDIR
|
||||
|
||||
|
||||
localrules:
|
||||
purge,
|
||||
|
||||
|
||||
wildcard_constraints:
|
||||
simpl="[a-zA-Z0-9]*|all",
|
||||
simpl="[a-zA-Z0-9]*",
|
||||
clusters="[0-9]+m?|all",
|
||||
ll="(v|c)([0-9\.]+|opt|all)|all",
|
||||
ll="(v|c)([0-9\.]+|opt)",
|
||||
opts="[-+a-zA-Z0-9\.]*",
|
||||
sector_opts="[-+a-zA-Z0-9\.\s]*",
|
||||
|
||||
|
||||
rule cluster_all_networks:
|
||||
input:
|
||||
expand("networks/" + RDIR + "elec_s{simpl}_{clusters}.nc", **config["scenario"]),
|
||||
include: "rules/common.smk"
|
||||
include: "rules/collect.smk"
|
||||
include: "rules/retrieve.smk"
|
||||
include: "rules/build_electricity.smk"
|
||||
include: "rules/build_sector.smk"
|
||||
include: "rules/solve_electricity.smk"
|
||||
include: "rules/postprocess.smk"
|
||||
|
||||
|
||||
rule extra_components_all_networks:
|
||||
input:
|
||||
expand(
|
||||
"networks/" + RDIR + "elec_s{simpl}_{clusters}_ec.nc", **config["scenario"]
|
||||
),
|
||||
if config["foresight"] == "overnight":
|
||||
|
||||
include: "rules/solve_overnight.smk"
|
||||
|
||||
|
||||
rule prepare_all_networks:
|
||||
input:
|
||||
expand(
|
||||
"networks/" + RDIR + "elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc",
|
||||
**config["scenario"]
|
||||
),
|
||||
if config["foresight"] == "myopic":
|
||||
|
||||
include: "rules/solve_myopic.smk"
|
||||
|
||||
|
||||
rule solve_all_networks:
|
||||
input:
|
||||
expand(
|
||||
"results/networks/" + RDIR + "elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc",
|
||||
**config["scenario"]
|
||||
),
|
||||
|
||||
|
||||
if config["enable"].get("prepare_links_p_nom", False):
|
||||
|
||||
rule prepare_links_p_nom:
|
||||
output:
|
||||
"data/links_p_nom.csv",
|
||||
log:
|
||||
"logs/" + RDIR + "prepare_links_p_nom.log",
|
||||
threads: 1
|
||||
resources:
|
||||
mem_mb=1500,
|
||||
script:
|
||||
"scripts/prepare_links_p_nom.py"
|
||||
|
||||
|
||||
datafiles = [
|
||||
"ch_cantons.csv",
|
||||
"je-e-21.03.02.xls",
|
||||
"eez/World_EEZ_v8_2014.shp",
|
||||
"hydro_capacities.csv",
|
||||
"naturalearth/ne_10m_admin_0_countries.shp",
|
||||
"NUTS_2013_60M_SH/data/NUTS_RG_60M_2013.shp",
|
||||
"nama_10r_3popgdp.tsv.gz",
|
||||
"nama_10r_3gdp.tsv.gz",
|
||||
"corine/g250_clc06_V18_5.tif",
|
||||
]
|
||||
|
||||
|
||||
if not config.get("tutorial", False):
|
||||
datafiles.extend(["natura/Natura2000_end2015.shp", "GEBCO_2014_2D.nc"])
|
||||
|
||||
|
||||
if config["enable"].get("retrieve_databundle", True):
|
||||
|
||||
rule retrieve_databundle:
|
||||
output:
|
||||
expand("data/bundle/{file}", file=datafiles),
|
||||
log:
|
||||
"logs/" + RDIR + "retrieve_databundle.log",
|
||||
resources:
|
||||
mem_mb=1000,
|
||||
script:
|
||||
"scripts/retrieve_databundle.py"
|
||||
|
||||
|
||||
rule retrieve_load_data:
|
||||
input:
|
||||
HTTP.remote(
|
||||
"data.open-power-system-data.org/time_series/2019-06-05/time_series_60min_singleindex.csv",
|
||||
keep_local=True,
|
||||
static=True,
|
||||
),
|
||||
output:
|
||||
"data/load_raw.csv",
|
||||
resources:
|
||||
mem_mb=5000,
|
||||
rule purge:
|
||||
message:
|
||||
"Purging generated resources, results and docs. Downloads are kept."
|
||||
run:
|
||||
move(input[0], output[0])
|
||||
rmtree("resources/", ignore_errors=True)
|
||||
rmtree("results/", ignore_errors=True)
|
||||
rmtree("doc/_build", ignore_errors=True)
|
||||
|
||||
|
||||
rule build_load_data:
|
||||
input:
|
||||
"data/load_raw.csv",
|
||||
rule dag:
|
||||
message:
|
||||
"Creating DAG of workflow."
|
||||
output:
|
||||
"resources/" + RDIR + "load.csv",
|
||||
log:
|
||||
"logs/" + RDIR + "build_load_data.log",
|
||||
resources:
|
||||
mem_mb=5000,
|
||||
script:
|
||||
"scripts/build_load_data.py"
|
||||
dot=RESOURCES + "dag.dot",
|
||||
pdf=RESOURCES + "dag.pdf",
|
||||
png=RESOURCES + "dag.png",
|
||||
conda:
|
||||
"envs/environment.yaml"
|
||||
shell:
|
||||
"""
|
||||
snakemake --rulegraph all | sed -n "/digraph/,\$p" > {output.dot}
|
||||
dot -Tpdf -o {output.pdf} {output.dot}
|
||||
dot -Tpng -o {output.png} {output.dot}
|
||||
"""
|
||||
|
||||
|
||||
rule build_powerplants:
|
||||
input:
|
||||
base_network="networks/" + RDIR + "base.nc",
|
||||
custom_powerplants="data/custom_powerplants.csv",
|
||||
rule doc:
|
||||
message:
|
||||
"Build documentation."
|
||||
output:
|
||||
"resources/" + RDIR + "powerplants.csv",
|
||||
log:
|
||||
"logs/" + RDIR + "build_powerplants.log",
|
||||
threads: 1
|
||||
resources:
|
||||
mem_mb=5000,
|
||||
script:
|
||||
"scripts/build_powerplants.py"
|
||||
|
||||
|
||||
rule base_network:
|
||||
input:
|
||||
eg_buses="data/entsoegridkit/buses.csv",
|
||||
eg_lines="data/entsoegridkit/lines.csv",
|
||||
eg_links="data/entsoegridkit/links.csv",
|
||||
eg_converters="data/entsoegridkit/converters.csv",
|
||||
eg_transformers="data/entsoegridkit/transformers.csv",
|
||||
parameter_corrections="data/parameter_corrections.yaml",
|
||||
links_p_nom="data/links_p_nom.csv",
|
||||
links_tyndp="data/links_tyndp.csv",
|
||||
country_shapes="resources/" + RDIR + "country_shapes.geojson",
|
||||
offshore_shapes="resources/" + RDIR + "offshore_shapes.geojson",
|
||||
europe_shape="resources/" + RDIR + "europe_shape.geojson",
|
||||
output:
|
||||
"networks/" + RDIR + "base.nc",
|
||||
log:
|
||||
"logs/" + RDIR + "base_network.log",
|
||||
benchmark:
|
||||
"benchmarks/" + RDIR + "base_network"
|
||||
threads: 1
|
||||
resources:
|
||||
mem_mb=1500,
|
||||
script:
|
||||
"scripts/base_network.py"
|
||||
|
||||
|
||||
rule build_shapes:
|
||||
input:
|
||||
naturalearth="data/bundle/naturalearth/ne_10m_admin_0_countries.shp",
|
||||
eez="data/bundle/eez/World_EEZ_v8_2014.shp",
|
||||
nuts3="data/bundle/NUTS_2013_60M_SH/data/NUTS_RG_60M_2013.shp",
|
||||
nuts3pop="data/bundle/nama_10r_3popgdp.tsv.gz",
|
||||
nuts3gdp="data/bundle/nama_10r_3gdp.tsv.gz",
|
||||
ch_cantons="data/bundle/ch_cantons.csv",
|
||||
ch_popgdp="data/bundle/je-e-21.03.02.xls",
|
||||
output:
|
||||
country_shapes="resources/" + RDIR + "country_shapes.geojson",
|
||||
offshore_shapes="resources/" + RDIR + "offshore_shapes.geojson",
|
||||
europe_shape="resources/" + RDIR + "europe_shape.geojson",
|
||||
nuts3_shapes="resources/" + RDIR + "nuts3_shapes.geojson",
|
||||
log:
|
||||
"logs/" + RDIR + "build_shapes.log",
|
||||
threads: 1
|
||||
resources:
|
||||
mem_mb=1500,
|
||||
script:
|
||||
"scripts/build_shapes.py"
|
||||
|
||||
|
||||
rule build_bus_regions:
|
||||
input:
|
||||
country_shapes="resources/" + RDIR + "country_shapes.geojson",
|
||||
offshore_shapes="resources/" + RDIR + "offshore_shapes.geojson",
|
||||
base_network="networks/" + RDIR + "base.nc",
|
||||
output:
|
||||
regions_onshore="resources/" + RDIR + "regions_onshore.geojson",
|
||||
regions_offshore="resources/" + RDIR + "regions_offshore.geojson",
|
||||
log:
|
||||
"logs/" + RDIR + "build_bus_regions.log",
|
||||
threads: 1
|
||||
resources:
|
||||
mem_mb=1000,
|
||||
script:
|
||||
"scripts/build_bus_regions.py"
|
||||
|
||||
|
||||
if config["enable"].get("build_cutout", False):
|
||||
|
||||
rule build_cutout:
|
||||
input:
|
||||
regions_onshore="resources/" + RDIR + "regions_onshore.geojson",
|
||||
regions_offshore="resources/" + RDIR + "regions_offshore.geojson",
|
||||
output:
|
||||
"cutouts/" + CDIR + "{cutout}.nc",
|
||||
log:
|
||||
"logs/" + CDIR + "build_cutout/{cutout}.log",
|
||||
benchmark:
|
||||
"benchmarks/" + CDIR + "build_cutout_{cutout}"
|
||||
threads: ATLITE_NPROCESSES
|
||||
resources:
|
||||
mem_mb=ATLITE_NPROCESSES * 1000,
|
||||
script:
|
||||
"scripts/build_cutout.py"
|
||||
|
||||
|
||||
if config["enable"].get("retrieve_cutout", True):
|
||||
|
||||
rule retrieve_cutout:
|
||||
input:
|
||||
HTTP.remote(
|
||||
"zenodo.org/record/6382570/files/{cutout}.nc",
|
||||
keep_local=True,
|
||||
static=True,
|
||||
),
|
||||
output:
|
||||
"cutouts/" + CDIR + "{cutout}.nc",
|
||||
log:
|
||||
"logs/" + CDIR + "retrieve_cutout_{cutout}.log",
|
||||
resources:
|
||||
mem_mb=5000,
|
||||
run:
|
||||
move(input[0], output[0])
|
||||
|
||||
|
||||
if config["enable"].get("retrieve_cost_data", True):
|
||||
|
||||
rule retrieve_cost_data:
|
||||
input:
|
||||
HTTP.remote(
|
||||
f"raw.githubusercontent.com/PyPSA/technology-data/{config['costs']['version']}/outputs/costs_{config['costs']['year']}.csv",
|
||||
keep_local=True,
|
||||
),
|
||||
output:
|
||||
COSTS,
|
||||
log:
|
||||
"logs/" + RDIR + "retrieve_cost_data.log",
|
||||
resources:
|
||||
mem_mb=5000,
|
||||
run:
|
||||
move(input[0], output[0])
|
||||
|
||||
|
||||
if config["enable"].get("build_natura_raster", False):
|
||||
|
||||
rule build_natura_raster:
|
||||
input:
|
||||
natura="data/bundle/natura/Natura2000_end2015.shp",
|
||||
cutouts=expand("cutouts/" + CDIR + "{cutouts}.nc", **config["atlite"]),
|
||||
output:
|
||||
"resources/" + RDIR + "natura.tiff",
|
||||
resources:
|
||||
mem_mb=5000,
|
||||
log:
|
||||
"logs/" + RDIR + "build_natura_raster.log",
|
||||
script:
|
||||
"scripts/build_natura_raster.py"
|
||||
|
||||
|
||||
if config["enable"].get("retrieve_natura_raster", True):
|
||||
|
||||
rule retrieve_natura_raster:
|
||||
input:
|
||||
HTTP.remote(
|
||||
"zenodo.org/record/4706686/files/natura.tiff",
|
||||
keep_local=True,
|
||||
static=True,
|
||||
),
|
||||
output:
|
||||
"resources/" + RDIR + "natura.tiff",
|
||||
resources:
|
||||
mem_mb=5000,
|
||||
run:
|
||||
move(input[0], output[0])
|
||||
|
||||
|
||||
rule retrieve_ship_raster:
|
||||
input:
|
||||
HTTP.remote(
|
||||
"https://zenodo.org/record/6953563/files/shipdensity_global.zip",
|
||||
keep_local=True,
|
||||
static=True,
|
||||
),
|
||||
output:
|
||||
"data/shipdensity_global.zip",
|
||||
resources:
|
||||
mem_mb=5000,
|
||||
run:
|
||||
move(input[0], output[0])
|
||||
|
||||
|
||||
rule build_ship_raster:
|
||||
input:
|
||||
ship_density="data/shipdensity_global.zip",
|
||||
cutouts=expand(
|
||||
"cutouts/" + CDIR + "{cutout}.nc",
|
||||
cutout=[
|
||||
config["renewable"][k]["cutout"]
|
||||
for k in config["electricity"]["renewable_carriers"]
|
||||
],
|
||||
),
|
||||
output:
|
||||
"resources/" + RDIR + "shipdensity_raster.nc",
|
||||
log:
|
||||
"logs/" + RDIR + "build_ship_raster.log",
|
||||
resources:
|
||||
mem_mb=5000,
|
||||
benchmark:
|
||||
"benchmarks/" + RDIR + "build_ship_raster"
|
||||
script:
|
||||
"scripts/build_ship_raster.py"
|
||||
|
||||
|
||||
rule build_renewable_profiles:
|
||||
input:
|
||||
base_network="networks/" + RDIR + "base.nc",
|
||||
corine="data/bundle/corine/g250_clc06_V18_5.tif",
|
||||
natura=lambda w: (
|
||||
"resources/" + RDIR + "natura.tiff"
|
||||
if config["renewable"][w.technology]["natura"]
|
||||
else []
|
||||
),
|
||||
gebco=lambda w: (
|
||||
"data/bundle/GEBCO_2014_2D.nc"
|
||||
if config["renewable"][w.technology].get("max_depth")
|
||||
else []
|
||||
),
|
||||
ship_density=lambda w: (
|
||||
"resources/" + RDIR + "shipdensity_raster.nc"
|
||||
if "ship_threshold" in config["renewable"][w.technology].keys()
|
||||
else []
|
||||
),
|
||||
country_shapes="resources/" + RDIR + "country_shapes.geojson",
|
||||
offshore_shapes="resources/" + RDIR + "offshore_shapes.geojson",
|
||||
regions=lambda w: (
|
||||
"resources/" + RDIR + "regions_onshore.geojson"
|
||||
if w.technology in ("onwind", "solar")
|
||||
else "resources/" + RDIR + "regions_offshore.geojson"
|
||||
),
|
||||
cutout=lambda w: "cutouts/"
|
||||
+ CDIR
|
||||
+ config["renewable"][w.technology]["cutout"]
|
||||
+ ".nc",
|
||||
output:
|
||||
profile="resources/" + RDIR + "profile_{technology}.nc",
|
||||
log:
|
||||
"logs/" + RDIR + "build_renewable_profile_{technology}.log",
|
||||
benchmark:
|
||||
"benchmarks/" + RDIR + "build_renewable_profiles_{technology}"
|
||||
threads: ATLITE_NPROCESSES
|
||||
resources:
|
||||
mem_mb=ATLITE_NPROCESSES * 5000,
|
||||
wildcard_constraints:
|
||||
technology="(?!hydro).*", # Any technology other than hydro
|
||||
script:
|
||||
"scripts/build_renewable_profiles.py"
|
||||
|
||||
|
||||
rule build_hydro_profile:
|
||||
input:
|
||||
country_shapes="resources/" + RDIR + "country_shapes.geojson",
|
||||
eia_hydro_generation="data/eia_hydro_annual_generation.csv",
|
||||
cutout=f"cutouts/" + CDIR + config["renewable"]["hydro"]["cutout"] + ".nc",
|
||||
output:
|
||||
"resources/" + RDIR + "profile_hydro.nc",
|
||||
log:
|
||||
"logs/" + RDIR + "build_hydro_profile.log",
|
||||
resources:
|
||||
mem_mb=5000,
|
||||
script:
|
||||
"scripts/build_hydro_profile.py"
|
||||
|
||||
|
||||
rule add_electricity:
|
||||
input:
|
||||
**{
|
||||
f"profile_{tech}": "resources/" + RDIR + f"profile_{tech}.nc"
|
||||
for tech in config["electricity"]["renewable_carriers"]
|
||||
},
|
||||
**{
|
||||
f"conventional_{carrier}_{attr}": fn
|
||||
for carrier, d in config.get("conventional", {None: {}}).items()
|
||||
for attr, fn in d.items()
|
||||
if str(fn).startswith("data/")
|
||||
},
|
||||
base_network="networks/" + RDIR + "base.nc",
|
||||
tech_costs=COSTS,
|
||||
regions="resources/" + RDIR + "regions_onshore.geojson",
|
||||
powerplants="resources/" + RDIR + "powerplants.csv",
|
||||
hydro_capacities="data/bundle/hydro_capacities.csv",
|
||||
geth_hydro_capacities="data/geth2015_hydro_capacities.csv",
|
||||
load="resources/" + RDIR + "load.csv",
|
||||
nuts3_shapes="resources/" + RDIR + "nuts3_shapes.geojson",
|
||||
output:
|
||||
"networks/" + RDIR + "elec.nc",
|
||||
log:
|
||||
"logs/" + RDIR + "add_electricity.log",
|
||||
benchmark:
|
||||
"benchmarks/" + RDIR + "add_electricity"
|
||||
threads: 1
|
||||
resources:
|
||||
mem_mb=5000,
|
||||
script:
|
||||
"scripts/add_electricity.py"
|
||||
|
||||
|
||||
rule simplify_network:
|
||||
input:
|
||||
network="networks/" + RDIR + "elec.nc",
|
||||
tech_costs=COSTS,
|
||||
regions_onshore="resources/" + RDIR + "regions_onshore.geojson",
|
||||
regions_offshore="resources/" + RDIR + "regions_offshore.geojson",
|
||||
output:
|
||||
network="networks/" + RDIR + "elec_s{simpl}.nc",
|
||||
regions_onshore="resources/" + RDIR + "regions_onshore_elec_s{simpl}.geojson",
|
||||
regions_offshore="resources/" + RDIR + "regions_offshore_elec_s{simpl}.geojson",
|
||||
busmap="resources/" + RDIR + "busmap_elec_s{simpl}.csv",
|
||||
connection_costs="resources/" + RDIR + "connection_costs_s{simpl}.csv",
|
||||
log:
|
||||
"logs/" + RDIR + "simplify_network/elec_s{simpl}.log",
|
||||
benchmark:
|
||||
"benchmarks/" + RDIR + "simplify_network/elec_s{simpl}"
|
||||
threads: 1
|
||||
resources:
|
||||
mem_mb=4000,
|
||||
script:
|
||||
"scripts/simplify_network.py"
|
||||
|
||||
|
||||
rule cluster_network:
|
||||
input:
|
||||
network="networks/" + RDIR + "elec_s{simpl}.nc",
|
||||
regions_onshore="resources/" + RDIR + "regions_onshore_elec_s{simpl}.geojson",
|
||||
regions_offshore="resources/" + RDIR + "regions_offshore_elec_s{simpl}.geojson",
|
||||
busmap=ancient("resources/" + RDIR + "busmap_elec_s{simpl}.csv"),
|
||||
custom_busmap=(
|
||||
"data/custom_busmap_elec_s{simpl}_{clusters}.csv"
|
||||
if config["enable"].get("custom_busmap", False)
|
||||
else []
|
||||
),
|
||||
tech_costs=COSTS,
|
||||
output:
|
||||
network="networks/" + RDIR + "elec_s{simpl}_{clusters}.nc",
|
||||
regions_onshore="resources/"
|
||||
+ RDIR
|
||||
+ "regions_onshore_elec_s{simpl}_{clusters}.geojson",
|
||||
regions_offshore="resources/"
|
||||
+ RDIR
|
||||
+ "regions_offshore_elec_s{simpl}_{clusters}.geojson",
|
||||
busmap="resources/" + RDIR + "busmap_elec_s{simpl}_{clusters}.csv",
|
||||
linemap="resources/" + RDIR + "linemap_elec_s{simpl}_{clusters}.csv",
|
||||
log:
|
||||
"logs/" + RDIR + "cluster_network/elec_s{simpl}_{clusters}.log",
|
||||
benchmark:
|
||||
"benchmarks/" + RDIR + "cluster_network/elec_s{simpl}_{clusters}"
|
||||
threads: 1
|
||||
resources:
|
||||
mem_mb=6000,
|
||||
script:
|
||||
"scripts/cluster_network.py"
|
||||
|
||||
|
||||
rule add_extra_components:
|
||||
input:
|
||||
network="networks/" + RDIR + "elec_s{simpl}_{clusters}.nc",
|
||||
tech_costs=COSTS,
|
||||
output:
|
||||
"networks/" + RDIR + "elec_s{simpl}_{clusters}_ec.nc",
|
||||
log:
|
||||
"logs/" + RDIR + "add_extra_components/elec_s{simpl}_{clusters}.log",
|
||||
benchmark:
|
||||
"benchmarks/" + RDIR + "add_extra_components/elec_s{simpl}_{clusters}_ec"
|
||||
threads: 1
|
||||
resources:
|
||||
mem_mb=3000,
|
||||
script:
|
||||
"scripts/add_extra_components.py"
|
||||
|
||||
|
||||
rule prepare_network:
|
||||
input:
|
||||
"networks/" + RDIR + "elec_s{simpl}_{clusters}_ec.nc",
|
||||
tech_costs=COSTS,
|
||||
output:
|
||||
"networks/" + RDIR + "elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc",
|
||||
log:
|
||||
"logs/" + RDIR + "prepare_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.log",
|
||||
benchmark:
|
||||
(
|
||||
"benchmarks/"
|
||||
+ RDIR
|
||||
+ "prepare_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}"
|
||||
)
|
||||
threads: 1
|
||||
resources:
|
||||
mem_mb=4000,
|
||||
script:
|
||||
"scripts/prepare_network.py"
|
||||
|
||||
|
||||
def memory(w):
|
||||
factor = 3.0
|
||||
for o in w.opts.split("-"):
|
||||
m = re.match(r"^(\d+)h$", o, re.IGNORECASE)
|
||||
if m is not None:
|
||||
factor /= int(m.group(1))
|
||||
break
|
||||
for o in w.opts.split("-"):
|
||||
m = re.match(r"^(\d+)seg$", o, re.IGNORECASE)
|
||||
if m is not None:
|
||||
factor *= int(m.group(1)) / 8760
|
||||
break
|
||||
if w.clusters.endswith("m"):
|
||||
return int(factor * (18000 + 180 * int(w.clusters[:-1])))
|
||||
elif w.clusters == "all":
|
||||
return int(factor * (18000 + 180 * 4000))
|
||||
else:
|
||||
return int(factor * (10000 + 195 * int(w.clusters)))
|
||||
|
||||
|
||||
rule solve_network:
|
||||
input:
|
||||
"networks/" + RDIR + "elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc",
|
||||
output:
|
||||
"results/networks/" + RDIR + "elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc",
|
||||
log:
|
||||
solver=normpath(
|
||||
"logs/"
|
||||
+ RDIR
|
||||
+ "solve_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_solver.log"
|
||||
),
|
||||
python="logs/"
|
||||
+ RDIR
|
||||
+ "solve_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_python.log",
|
||||
memory="logs/"
|
||||
+ RDIR
|
||||
+ "solve_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_memory.log",
|
||||
benchmark:
|
||||
"benchmarks/" + RDIR + "solve_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}"
|
||||
threads: 4
|
||||
resources:
|
||||
mem_mb=memory,
|
||||
shadow:
|
||||
"minimal"
|
||||
script:
|
||||
"scripts/solve_network.py"
|
||||
|
||||
|
||||
rule solve_operations_network:
|
||||
input:
|
||||
unprepared="networks/" + RDIR + "elec_s{simpl}_{clusters}_ec.nc",
|
||||
optimized="results/networks/"
|
||||
+ RDIR
|
||||
+ "elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc",
|
||||
output:
|
||||
"results/networks/" + RDIR + "elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_op.nc",
|
||||
log:
|
||||
solver=normpath(
|
||||
"logs/"
|
||||
+ RDIR
|
||||
+ "solve_operations_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_op_solver.log"
|
||||
),
|
||||
python="logs/"
|
||||
+ RDIR
|
||||
+ "solve_operations_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_op_python.log",
|
||||
memory="logs/"
|
||||
+ RDIR
|
||||
+ "solve_operations_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_op_memory.log",
|
||||
benchmark:
|
||||
(
|
||||
"benchmarks/"
|
||||
+ RDIR
|
||||
+ "solve_operations_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}"
|
||||
)
|
||||
threads: 4
|
||||
resources:
|
||||
mem_mb=(lambda w: 5000 + 372 * int(w.clusters)),
|
||||
shadow:
|
||||
"minimal"
|
||||
script:
|
||||
"scripts/solve_operations_network.py"
|
||||
|
||||
|
||||
rule plot_network:
|
||||
input:
|
||||
network="results/networks/"
|
||||
+ RDIR
|
||||
+ "elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc",
|
||||
tech_costs=COSTS,
|
||||
output:
|
||||
only_map="results/plots/"
|
||||
+ RDIR
|
||||
+ "elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{attr}.{ext}",
|
||||
ext="results/plots/"
|
||||
+ RDIR
|
||||
+ "elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{attr}_ext.{ext}",
|
||||
log:
|
||||
"logs/"
|
||||
+ RDIR
|
||||
+ "plot_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{attr}_{ext}.log",
|
||||
script:
|
||||
"scripts/plot_network.py"
|
||||
|
||||
|
||||
def input_make_summary(w):
|
||||
# It's mildly hacky to include the separate costs input as first entry
|
||||
if w.ll.endswith("all"):
|
||||
ll = config["scenario"]["ll"]
|
||||
if len(w.ll) == 4:
|
||||
ll = [l for l in ll if l[0] == w.ll[0]]
|
||||
else:
|
||||
ll = w.ll
|
||||
return [COSTS] + expand(
|
||||
"results/networks/" + RDIR + "elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc",
|
||||
ll=ll,
|
||||
**{
|
||||
k: config["scenario"][k] if getattr(w, k) == "all" else getattr(w, k)
|
||||
for k in ["simpl", "clusters", "opts"]
|
||||
}
|
||||
)
|
||||
|
||||
|
||||
rule make_summary:
|
||||
input:
|
||||
input_make_summary,
|
||||
output:
|
||||
directory(
|
||||
"results/summaries/"
|
||||
+ RDIR
|
||||
+ "elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{country}"
|
||||
),
|
||||
log:
|
||||
"logs/"
|
||||
+ RDIR
|
||||
+ "make_summary/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{country}.log",
|
||||
resources:
|
||||
mem_mb=1500,
|
||||
script:
|
||||
"scripts/make_summary.py"
|
||||
|
||||
|
||||
rule plot_summary:
|
||||
input:
|
||||
"results/summaries/"
|
||||
+ RDIR
|
||||
+ "elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{country}",
|
||||
output:
|
||||
"results/plots/"
|
||||
+ RDIR
|
||||
+ "summary_{summary}_elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{country}.{ext}",
|
||||
log:
|
||||
"logs/"
|
||||
+ RDIR
|
||||
+ "plot_summary/{summary}_elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{country}_{ext}.log",
|
||||
resources:
|
||||
mem_mb=1500,
|
||||
script:
|
||||
"scripts/plot_summary.py"
|
||||
|
||||
|
||||
def input_plot_p_nom_max(w):
|
||||
return [
|
||||
(
|
||||
"results/networks/"
|
||||
+ RDIR
|
||||
+ "elec_s{simpl}{maybe_cluster}.nc".format(
|
||||
maybe_cluster=("" if c == "full" else ("_" + c)), **w
|
||||
)
|
||||
)
|
||||
for c in w.clusts.split(",")
|
||||
]
|
||||
|
||||
|
||||
rule plot_p_nom_max:
|
||||
input:
|
||||
input_plot_p_nom_max,
|
||||
output:
|
||||
"results/plots/"
|
||||
+ RDIR
|
||||
+ "elec_s{simpl}_cum_p_nom_max_{clusts}_{techs}_{country}.{ext}",
|
||||
log:
|
||||
"logs/"
|
||||
+ RDIR
|
||||
+ "plot_p_nom_max/elec_s{simpl}_{clusts}_{techs}_{country}_{ext}.log",
|
||||
resources:
|
||||
mem_mb=1500,
|
||||
script:
|
||||
"scripts/plot_p_nom_max.py"
|
||||
directory("doc/_build"),
|
||||
shell:
|
||||
"make -C doc html"
|
||||
|
||||
@ -11,14 +11,53 @@ logging:
|
||||
|
||||
run:
|
||||
name: "" # use this to keep track of runs with different settings
|
||||
shared_cutouts: false # set to true to share the default cutout(s) across runs
|
||||
disable_progressbar: false # set to true to disable the progressbar
|
||||
shared_resources: false # set to true to share the default resources across runs
|
||||
shared_cutouts: true # set to true to share the default cutout(s) across runs
|
||||
|
||||
foresight: overnight # options are overnight, myopic, perfect (perfect is not yet implemented)
|
||||
# if you use myopic or perfect foresight, set the investment years in "planning_horizons" below
|
||||
|
||||
scenario:
|
||||
simpl: ['']
|
||||
ll: ['copt']
|
||||
clusters: [37, 128, 256, 512, 1024]
|
||||
opts: [Co2L-3H]
|
||||
simpl:
|
||||
- ''
|
||||
ll: # allowed transmission line volume expansion, can be any float >= 1.0 with a prefix v|c (today) or "copt"
|
||||
- v1.0
|
||||
- v1.5
|
||||
clusters: # number of nodes in Europe, any integer between 37 (1 node per country-zone) and several hundred
|
||||
- 37
|
||||
- 128
|
||||
- 256
|
||||
- 512
|
||||
- 1024
|
||||
opts: # only relevant for PyPSA-Eur
|
||||
- ''
|
||||
sector_opts: # this is where the main scenario settings are
|
||||
- Co2L0-3H-T-H-B-I-A-solar+p3-dist1
|
||||
# to really understand the options here, look in scripts/prepare_sector_network.py
|
||||
# Co2Lx specifies the CO2 target in x% of the 1990 values; default will give default (5%);
|
||||
# Co2L0p25 will give 25% CO2 emissions; Co2Lm0p05 will give 5% negative emissions
|
||||
# xH is the temporal resolution; 3H is 3-hourly, i.e. one snapshot every 3 hours
|
||||
# single letters are sectors: T for land transport, H for building heating,
|
||||
# B for biomass supply, I for industry, shipping and aviation,
|
||||
# A for agriculture, forestry and fishing
|
||||
# solar+c0.5 reduces the capital cost of solar to 50\% of reference value
|
||||
# solar+p3 multiplies the available installable potential by factor 3
|
||||
# seq400 sets the potential of CO2 sequestration to 400 Mt CO2 per year
|
||||
# dist{n} includes distribution grids with investment cost of n times cost in data/costs.csv
|
||||
# for myopic/perfect foresight cb states the carbon budget in GtCO2 (cumulative
|
||||
# emissions throughout the transition path in the timeframe determined by the
|
||||
# planning_horizons), be:beta decay; ex:exponential decay
|
||||
# cb40ex0 distributes a carbon budget of 40 GtCO2 following an exponential
|
||||
# decay with initial growth rate 0
|
||||
planning_horizons: # investment years for myopic and perfect; for overnight, year of cost assumptions can be different and is defined under 'costs'
|
||||
- 2050
|
||||
# for example, set to
|
||||
# - 2020
|
||||
# - 2030
|
||||
# - 2040
|
||||
# - 2050
|
||||
# for myopic foresight
|
||||
|
||||
countries: ['AL', 'AT', 'BA', 'BE', 'BG', 'CH', 'CZ', 'DE', 'DK', 'EE', 'ES', 'FI', 'FR', 'GB', 'GR', 'HR', 'HU', 'IE', 'IT', 'LT', 'LU', 'LV', 'ME', 'MK', 'NL', 'NO', 'PL', 'PT', 'RO', 'RS', 'SE', 'SI', 'SK']
|
||||
|
||||
@ -30,6 +69,7 @@ snapshots:
|
||||
enable:
|
||||
prepare_links_p_nom: false
|
||||
retrieve_databundle: true
|
||||
retrieve_sector_databundle: true
|
||||
retrieve_cost_data: true
|
||||
build_cutout: false
|
||||
retrieve_cutout: true
|
||||
@ -37,6 +77,18 @@ enable:
|
||||
retrieve_natura_raster: true
|
||||
custom_busmap: false
|
||||
|
||||
# CO2 budget as a fraction of 1990 emissions
|
||||
# this is over-ridden if CO2Lx is set in sector_opts
|
||||
# this is also over-ridden if cb is set in sector_opts
|
||||
co2_budget:
|
||||
2020: 0.701
|
||||
2025: 0.524
|
||||
2030: 0.297
|
||||
2035: 0.150
|
||||
2040: 0.071
|
||||
2045: 0.032
|
||||
2050: 0.000
|
||||
|
||||
electricity:
|
||||
voltages: [220., 300., 380.]
|
||||
gaslimit: false # global gas usage limit of X MWh_th
|
||||
@ -84,7 +136,9 @@ electricity:
|
||||
Onshore: [onwind]
|
||||
PV: [solar]
|
||||
|
||||
|
||||
atlite:
|
||||
default_cutout: europe-2013-era5
|
||||
nprocesses: 4
|
||||
show_progress: false # false saves time
|
||||
cutouts:
|
||||
@ -121,7 +175,7 @@ renewable:
|
||||
# acceptance issues.
|
||||
# correction_factor: 0.93
|
||||
corine:
|
||||
# Scholz, Y. (2012). Renewable energy based electricity supply at low costs:
|
||||
# Scholz, Y. (2012). Renewable energy based electricity supply at low costs
|
||||
# development of the REMix model and application for Europe. ( p.42 / p.28)
|
||||
grid_codes: [12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 31, 32]
|
||||
distance: 1000
|
||||
@ -182,7 +236,7 @@ renewable:
|
||||
# Correction factor determined by comparing uncorrected area-weighted full-load hours to those
|
||||
# published in Supplementary Data to
|
||||
# Pietzcker, Robert Carl, et al. "Using the sun to decarbonize the power
|
||||
# sector: The economic potential of photovoltaics and concentrating solar
|
||||
# sector -- The economic potential of photovoltaics and concentrating solar
|
||||
# power." Applied Energy 135 (2014): 704-720.
|
||||
# This correction factor of 0.854337 may be in order if using reanalysis data.
|
||||
# for discussion refer to https://github.com/PyPSA/pypsa-eur/pull/304
|
||||
@ -231,6 +285,287 @@ load:
|
||||
manual_adjustments: true # false
|
||||
scaling_factor: 1.0
|
||||
|
||||
# regulate what components with which carriers are kept from PyPSA-Eur;
|
||||
# some technologies are removed because they are implemented differently
|
||||
# (e.g. battery or H2 storage) or have different year-dependent costs
|
||||
# in PyPSA-Eur-Sec
|
||||
pypsa_eur:
|
||||
Bus:
|
||||
- AC
|
||||
Link:
|
||||
- DC
|
||||
Generator:
|
||||
- onwind
|
||||
- offwind-ac
|
||||
- offwind-dc
|
||||
- solar
|
||||
- ror
|
||||
StorageUnit:
|
||||
- PHS
|
||||
- hydro
|
||||
Store: []
|
||||
|
||||
energy:
|
||||
energy_totals_year: 2011
|
||||
base_emissions_year: 1990
|
||||
eurostat_report_year: 2016
|
||||
emissions: CO2 # "CO2" or "All greenhouse gases - (CO2 equivalent)"
|
||||
|
||||
biomass:
|
||||
year: 2030
|
||||
scenario: ENS_Med
|
||||
classes:
|
||||
solid biomass:
|
||||
- Agricultural waste
|
||||
- Fuelwood residues
|
||||
- Secondary Forestry residues - woodchips
|
||||
- Sawdust
|
||||
- Residues from landscape care
|
||||
- Municipal waste
|
||||
not included:
|
||||
- Sugar from sugar beet
|
||||
- Rape seed
|
||||
- "Sunflower, soya seed "
|
||||
- Bioethanol barley, wheat, grain maize, oats, other cereals and rye
|
||||
- Miscanthus, switchgrass, RCG
|
||||
- Willow
|
||||
- Poplar
|
||||
- FuelwoodRW
|
||||
- C&P_RW
|
||||
biogas:
|
||||
- Manure solid, liquid
|
||||
- Sludge
|
||||
|
||||
|
||||
solar_thermal:
|
||||
clearsky_model: simple # should be "simple" or "enhanced"?
|
||||
orientation:
|
||||
slope: 45.
|
||||
azimuth: 180.
|
||||
|
||||
# only relevant for foresight = myopic or perfect
|
||||
existing_capacities:
|
||||
grouping_years_power: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020, 2025, 2030]
|
||||
grouping_years_heat: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2019] # these should not extend 2020
|
||||
threshold_capacity: 10
|
||||
conventional_carriers:
|
||||
- lignite
|
||||
- coal
|
||||
- oil
|
||||
- uranium
|
||||
|
||||
|
||||
sector:
|
||||
district_heating:
|
||||
potential: 0.6 # maximum fraction of urban demand which can be supplied by district heating
|
||||
# increase of today's district heating demand to potential maximum district heating share
|
||||
# progress = 0 means today's district heating share, progress = 1 means maximum fraction of urban demand is supplied by district heating
|
||||
progress:
|
||||
2020: 0.0
|
||||
2030: 0.3
|
||||
2040: 0.6
|
||||
2050: 1.0
|
||||
district_heating_loss: 0.15
|
||||
cluster_heat_buses: false # cluster residential and service heat buses to one to save memory
|
||||
bev_dsm_restriction_value: 0.75 #Set to 0 for no restriction on BEV DSM
|
||||
bev_dsm_restriction_time: 7 #Time at which SOC of BEV has to be dsm_restriction_value
|
||||
transport_heating_deadband_upper: 20.
|
||||
transport_heating_deadband_lower: 15.
|
||||
ICE_lower_degree_factor: 0.375 #in per cent increase in fuel consumption per degree above deadband
|
||||
ICE_upper_degree_factor: 1.6
|
||||
EV_lower_degree_factor: 0.98
|
||||
EV_upper_degree_factor: 0.63
|
||||
bev_dsm: true #turns on EV battery
|
||||
bev_availability: 0.5 #How many cars do smart charging
|
||||
bev_energy: 0.05 #average battery size in MWh
|
||||
bev_charge_efficiency: 0.9 #BEV (dis-)charging efficiency
|
||||
bev_plug_to_wheel_efficiency: 0.2 #kWh/km from EPA https://www.fueleconomy.gov/feg/ for Tesla Model S
|
||||
bev_charge_rate: 0.011 #3-phase charger with 11 kW
|
||||
bev_avail_max: 0.95
|
||||
bev_avail_mean: 0.8
|
||||
v2g: true #allows feed-in to grid from EV battery
|
||||
#what is not EV or FCEV is oil-fuelled ICE
|
||||
land_transport_fuel_cell_share:
|
||||
2020: 0
|
||||
2030: 0.05
|
||||
2040: 0.1
|
||||
2050: 0.15
|
||||
land_transport_electric_share:
|
||||
2020: 0
|
||||
2030: 0.25
|
||||
2040: 0.6
|
||||
2050: 0.85
|
||||
land_transport_ice_share:
|
||||
2020: 1
|
||||
2030: 0.7
|
||||
2040: 0.3
|
||||
2050: 0
|
||||
transport_fuel_cell_efficiency: 0.5
|
||||
transport_internal_combustion_efficiency: 0.3
|
||||
agriculture_machinery_electric_share: 0
|
||||
agriculture_machinery_oil_share: 1
|
||||
agriculture_machinery_fuel_efficiency: 0.7 # fuel oil per use
|
||||
agriculture_machinery_electric_efficiency: 0.3 # electricity per use
|
||||
MWh_MeOH_per_MWh_H2: 0.8787 # in LHV, source: DECHEMA (2017): Low carbon energy and feedstock for the European chemical industry , pg. 64.
|
||||
MWh_MeOH_per_tCO2: 4.0321 # in LHV, source: DECHEMA (2017): Low carbon energy and feedstock for the European chemical industry , pg. 64.
|
||||
MWh_MeOH_per_MWh_e: 3.6907 # in LHV, source: DECHEMA (2017): Low carbon energy and feedstock for the European chemical industry , pg. 64.
|
||||
shipping_hydrogen_liquefaction: false # whether to consider liquefaction costs for shipping H2 demands
|
||||
shipping_hydrogen_share:
|
||||
2020: 0
|
||||
2030: 0
|
||||
2040: 0
|
||||
2050: 0
|
||||
shipping_methanol_share:
|
||||
2020: 0
|
||||
2030: 0.3
|
||||
2040: 0.7
|
||||
2050: 1
|
||||
shipping_oil_share:
|
||||
2020: 1
|
||||
2030: 0.7
|
||||
2040: 0.3
|
||||
2050: 0
|
||||
shipping_methanol_efficiency: 0.46 # 10-15% higher https://www.iea-amf.org/app/webroot/files/file/Annex%20Reports/AMF_Annex_56.pdf, https://users.ugent.be/~lsileghe/documents/extended_abstract.pdf
|
||||
shipping_oil_efficiency: 0.40 #For conversion of fuel oil to propulsion in 2011
|
||||
aviation_demand_factor: 1. # relative aviation demand compared to today
|
||||
HVC_demand_factor: 1. # relative HVC demand compared to today
|
||||
time_dep_hp_cop: true #time dependent heat pump coefficient of performance
|
||||
heat_pump_sink_T: 55. # Celsius, based on DTU / large area radiators; used in build_cop_profiles.py
|
||||
# conservatively high to cover hot water and space heating in poorly-insulated buildings
|
||||
reduce_space_heat_exogenously: true # reduces space heat demand by a given factor (applied before losses in DH)
|
||||
# this can represent e.g. building renovation, building demolition, or if
|
||||
# the factor is negative: increasing floor area, increased thermal comfort, population growth
|
||||
reduce_space_heat_exogenously_factor: # per unit reduction in space heat demand
|
||||
# the default factors are determined by the LTS scenario from http://tool.european-calculator.eu/app/buildings/building-types-area/?levers=1ddd4444421213bdbbbddd44444ffffff11f411111221111211l212221
|
||||
2020: 0.10 # this results in a space heat demand reduction of 10%
|
||||
2025: 0.09 # first heat demand increases compared to 2020 because of larger floor area per capita
|
||||
2030: 0.09
|
||||
2035: 0.11
|
||||
2040: 0.16
|
||||
2045: 0.21
|
||||
2050: 0.29
|
||||
retrofitting: # co-optimises building renovation to reduce space heat demand
|
||||
retro_endogen: false # co-optimise space heat savings
|
||||
cost_factor: 1.0 # weight costs for building renovation
|
||||
interest_rate: 0.04 # for investment in building components
|
||||
annualise_cost: true # annualise the investment costs
|
||||
tax_weighting: false # weight costs depending on taxes in countries
|
||||
construction_index: true # weight costs depending on labour/material costs per country
|
||||
tes: true
|
||||
tes_tau: # 180 day time constant for centralised, 3 day for decentralised
|
||||
decentral: 3
|
||||
central: 180
|
||||
boilers: true
|
||||
oil_boilers: false
|
||||
biomass_boiler: true
|
||||
chp: true
|
||||
micro_chp: false
|
||||
solar_thermal: true
|
||||
solar_cf_correction: 0.788457 # = >>> 1/1.2683
|
||||
marginal_cost_storage: 0. #1e-4
|
||||
methanation: true
|
||||
helmeth: true
|
||||
coal_cc: false
|
||||
dac: true
|
||||
co2_vent: false
|
||||
allam_cycle: false
|
||||
SMR: true
|
||||
regional_co2_sequestration_potential:
|
||||
enable: false # enable regionally resolved geological co2 storage potential
|
||||
attribute: 'conservative estimate Mt'
|
||||
include_onshore: false # include onshore sequestration potentials
|
||||
min_size: 3 # Gt, sites with lower potential will be excluded
|
||||
max_size: 25 # Gt, max sequestration potential for any one site, TODO research suitable value
|
||||
years_of_storage: 25 # years until potential exhausted at optimised annual rate
|
||||
co2_sequestration_potential: 200 #MtCO2/a sequestration potential for Europe
|
||||
co2_sequestration_cost: 10 #EUR/tCO2 for sequestration of CO2
|
||||
co2_spatial: false
|
||||
co2network: false
|
||||
cc_fraction: 0.9 # default fraction of CO2 captured with post-combustion capture
|
||||
hydrogen_underground_storage: true
|
||||
hydrogen_underground_storage_locations:
|
||||
# - onshore # more than 50 km from sea
|
||||
- nearshore # within 50 km of sea
|
||||
# - offshore
|
||||
ammonia: false # can be false (no NH3 carrier), true (copperplated NH3), "regional" (regionalised NH3 without network)
|
||||
min_part_load_fischer_tropsch: 0.9 # p_min_pu
|
||||
min_part_load_methanolisation: 0.5 # p_min_pu
|
||||
use_fischer_tropsch_waste_heat: true
|
||||
use_fuel_cell_waste_heat: true
|
||||
use_electrolysis_waste_heat: false
|
||||
electricity_distribution_grid: true
|
||||
electricity_distribution_grid_cost_factor: 1.0 #multiplies cost in data/costs.csv
|
||||
electricity_grid_connection: true # only applies to onshore wind and utility PV
|
||||
H2_network: true
|
||||
gas_network: false
|
||||
H2_retrofit: false # if set to True existing gas pipes can be retrofitted to H2 pipes
|
||||
# according to hydrogen backbone strategy (April, 2020) p.15
|
||||
# https://gasforclimate2050.eu/wp-content/uploads/2020/07/2020_European-Hydrogen-Backbone_Report.pdf
|
||||
# 60% of original natural gas capacity could be used in cost-optimal case as H2 capacity
|
||||
H2_retrofit_capacity_per_CH4: 0.6 # ratio for H2 capacity per original CH4 capacity of retrofitted pipelines
|
||||
gas_network_connectivity_upgrade: 1 # https://networkx.org/documentation/stable/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation.html#networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation
|
||||
gas_distribution_grid: true
|
||||
gas_distribution_grid_cost_factor: 1.0 #multiplies cost in data/costs.csv
|
||||
biomass_spatial: false # regionally resolve biomass (e.g. potentials)
|
||||
biomass_transport: false # allow transport of solid biomass between nodes
|
||||
conventional_generation: # generator : carrier
|
||||
OCGT: gas
|
||||
biomass_to_liquid: false
|
||||
biosng: false
|
||||
|
||||
industry:
|
||||
St_primary_fraction: # fraction of steel produced via primary route versus secondary route (scrap+EAF); today fraction is 0.6
|
||||
2020: 0.6
|
||||
2025: 0.55
|
||||
2030: 0.5
|
||||
2035: 0.45
|
||||
2040: 0.4
|
||||
2045: 0.35
|
||||
2050: 0.3
|
||||
DRI_fraction: # fraction of the primary route converted to DRI + EAF
|
||||
2020: 0
|
||||
2025: 0
|
||||
2030: 0.05
|
||||
2035: 0.2
|
||||
2040: 0.4
|
||||
2045: 0.7
|
||||
2050: 1
|
||||
H2_DRI: 1.7 #H2 consumption in Direct Reduced Iron (DRI), MWh_H2,LHV/ton_Steel from 51kgH2/tSt in Vogl et al (2018) doi:10.1016/j.jclepro.2018.08.279
|
||||
elec_DRI: 0.322 #electricity consumption in Direct Reduced Iron (DRI) shaft, MWh/tSt HYBRIT brochure https://ssabwebsitecdn.azureedge.net/-/media/hybrit/files/hybrit_brochure.pdf
|
||||
Al_primary_fraction: # fraction of aluminium produced via the primary route versus scrap; today fraction is 0.4
|
||||
2020: 0.4
|
||||
2025: 0.375
|
||||
2030: 0.35
|
||||
2035: 0.325
|
||||
2040: 0.3
|
||||
2045: 0.25
|
||||
2050: 0.2
|
||||
MWh_NH3_per_tNH3: 5.166 # LHV
|
||||
MWh_CH4_per_tNH3_SMR: 10.8 # 2012's demand from https://ec.europa.eu/docsroom/documents/4165/attachments/1/translations/en/renditions/pdf
|
||||
MWh_elec_per_tNH3_SMR: 0.7 # same source, assuming 94-6% split methane-elec of total energy demand 11.5 MWh/tNH3
|
||||
MWh_H2_per_tNH3_electrolysis: 6.5 # from https://doi.org/10.1016/j.joule.2018.04.017, around 0.197 tH2/tHN3 (>3/17 since some H2 lost and used for energy)
|
||||
MWh_elec_per_tNH3_electrolysis: 1.17 # from https://doi.org/10.1016/j.joule.2018.04.017 Table 13 (air separation and HB)
|
||||
MWh_NH3_per_MWh_H2_cracker: 1.46 # https://github.com/euronion/trace/blob/44a5ff8401762edbef80eff9cfe5a47c8d3c8be4/data/efficiencies.csv
|
||||
NH3_process_emissions: 24.5 # in MtCO2/a from SMR for H2 production for NH3 from UNFCCC for 2015 for EU28
|
||||
petrochemical_process_emissions: 25.5 # in MtCO2/a for petrochemical and other from UNFCCC for 2015 for EU28
|
||||
HVC_primary_fraction: 1. # fraction of today's HVC produced via primary route
|
||||
HVC_mechanical_recycling_fraction: 0. # fraction of today's HVC produced via mechanical recycling
|
||||
HVC_chemical_recycling_fraction: 0. # fraction of today's HVC produced via chemical recycling
|
||||
HVC_production_today: 52. # MtHVC/a from DECHEMA (2017), Figure 16, page 107; includes ethylene, propylene and BTX
|
||||
MWh_elec_per_tHVC_mechanical_recycling: 0.547 # from SI of https://doi.org/10.1016/j.resconrec.2020.105010, Table S5, for HDPE, PP, PS, PET. LDPE would be 0.756.
|
||||
MWh_elec_per_tHVC_chemical_recycling: 6.9 # Material Economics (2019), page 125; based on pyrolysis and electric steam cracking
|
||||
chlorine_production_today: 9.58 # MtCl/a from DECHEMA (2017), Table 7, page 43
|
||||
MWh_elec_per_tCl: 3.6 # DECHEMA (2017), Table 6, page 43
|
||||
MWh_H2_per_tCl: -0.9372 # DECHEMA (2017), page 43; negative since hydrogen produced in chloralkali process
|
||||
methanol_production_today: 1.5 # MtMeOH/a from DECHEMA (2017), page 62
|
||||
MWh_elec_per_tMeOH: 0.167 # DECHEMA (2017), Table 14, page 65
|
||||
MWh_CH4_per_tMeOH: 10.25 # DECHEMA (2017), Table 14, page 65
|
||||
hotmaps_locate_missing: false
|
||||
reference_year: 2015
|
||||
# references:
|
||||
# DECHEMA (2017): https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf
|
||||
# Material Economics (2019): https://materialeconomics.com/latest-updates/industrial-transformation-2050
|
||||
|
||||
costs:
|
||||
year: 2030
|
||||
version: v0.5.0
|
||||
@ -244,6 +579,9 @@ costs:
|
||||
lifetime: 25
|
||||
"CO2 intensity": 0
|
||||
"discount rate": 0.07
|
||||
# Marginal and capital costs can be overwritten
|
||||
# capital_cost:
|
||||
# onwind: 500
|
||||
marginal_cost:
|
||||
solar: 0.01
|
||||
onwind: 0.015
|
||||
@ -291,15 +629,7 @@ solving:
|
||||
track_iterations: false
|
||||
min_iterations: 4
|
||||
max_iterations: 6
|
||||
keep_shadowprices:
|
||||
- Bus
|
||||
- Line
|
||||
- Link
|
||||
- Transformer
|
||||
- GlobalConstraint
|
||||
- Generator
|
||||
- Store
|
||||
- StorageUnit
|
||||
seed: 123
|
||||
|
||||
solver:
|
||||
name: gurobi
|
||||
@ -364,70 +694,61 @@ solving:
|
||||
|
||||
plotting:
|
||||
map:
|
||||
figsize: [7, 7]
|
||||
boundaries: [-10.2, 29, 35, 72]
|
||||
p_nom:
|
||||
bus_size_factor: 5.e+4
|
||||
linewidth_factor: 3.e+3
|
||||
|
||||
costs_max: 800
|
||||
boundaries: [-11, 30, 34, 71]
|
||||
color_geomap:
|
||||
ocean: white
|
||||
land: white
|
||||
eu_node_location:
|
||||
x: -5.5
|
||||
y: 46.
|
||||
costs_max: 1000
|
||||
costs_threshold: 1
|
||||
|
||||
energy_max: 15000.
|
||||
energy_min: -10000.
|
||||
energy_max: 20000
|
||||
energy_min: -20000
|
||||
energy_threshold: 50.
|
||||
vre_techs:
|
||||
- onwind
|
||||
- offwind-ac
|
||||
- offwind-dc
|
||||
- solar
|
||||
- ror
|
||||
renewable_storage_techs:
|
||||
- PHS
|
||||
- hydro
|
||||
conv_techs:
|
||||
- OCGT
|
||||
- CCGT
|
||||
- Nuclear
|
||||
- Coal
|
||||
storage_techs:
|
||||
- hydro+PHS
|
||||
- battery
|
||||
- H2
|
||||
load_carriers:
|
||||
- AC load
|
||||
AC_carriers:
|
||||
- AC line
|
||||
- AC transformer
|
||||
link_carriers:
|
||||
- DC line
|
||||
- Converter AC-DC
|
||||
heat_links:
|
||||
- heat pump
|
||||
- resistive heater
|
||||
- CHP heat
|
||||
- CHP electric
|
||||
- gas boiler
|
||||
- central heat pump
|
||||
- central resistive heater
|
||||
- central CHP heat
|
||||
- central CHP electric
|
||||
- central gas boiler
|
||||
heat_generators:
|
||||
- gas boiler
|
||||
- central gas boiler
|
||||
- solar thermal collector
|
||||
- central solar thermal collector
|
||||
|
||||
vre_techs: ["onwind", "offwind-ac", "offwind-dc", "solar", "ror"]
|
||||
conv_techs: ["OCGT", "CCGT", "Nuclear", "Coal"]
|
||||
storage_techs: ["hydro+PHS", "battery", "H2"]
|
||||
load_carriers: ["AC load"]
|
||||
AC_carriers: ["AC line", "AC transformer"]
|
||||
link_carriers: ["DC line", "Converter AC-DC"]
|
||||
tech_colors:
|
||||
"onwind": "#235ebc"
|
||||
"onshore wind": "#235ebc"
|
||||
'offwind': "#6895dd"
|
||||
'offwind-ac': "#6895dd"
|
||||
'offshore wind': "#6895dd"
|
||||
'offshore wind ac': "#6895dd"
|
||||
'offwind-dc': "#74c6f2"
|
||||
'offshore wind dc': "#74c6f2"
|
||||
"hydro": "#08ad97"
|
||||
"hydro+PHS": "#08ad97"
|
||||
"PHS": "#08ad97"
|
||||
"hydro reservoir": "#08ad97"
|
||||
'hydroelectricity': '#08ad97'
|
||||
"ror": "#4adbc8"
|
||||
"run of river": "#4adbc8"
|
||||
'solar': "#f9d002"
|
||||
'solar PV': "#f9d002"
|
||||
'solar thermal': '#ffef60'
|
||||
'biomass': '#0c6013'
|
||||
'solid biomass': '#06540d'
|
||||
'biogas': '#23932d'
|
||||
'waste': '#68896b'
|
||||
'geothermal': '#ba91b1'
|
||||
"OCGT": "#d35050"
|
||||
"gas": "#d35050"
|
||||
"natural gas": "#d35050"
|
||||
"CCGT": "#b20101"
|
||||
"nuclear": "#ff9000"
|
||||
"coal": "#707070"
|
||||
"lignite": "#9e5a01"
|
||||
"oil": "#262626"
|
||||
"H2": "#ea048a"
|
||||
"hydrogen storage": "#ea048a"
|
||||
"battery": "#b8ea04"
|
||||
"Electric load": "#f9d002"
|
||||
"electricity": "#f9d002"
|
||||
"lines": "#70af1d"
|
||||
"transmission lines": "#70af1d"
|
||||
"AC-AC": "#70af1d"
|
||||
"AC line": "#70af1d"
|
||||
"links": "#8a1caf"
|
||||
"HVDC links": "#8a1caf"
|
||||
"DC-DC": "#8a1caf"
|
||||
"DC link": "#8a1caf"
|
||||
nice_names:
|
||||
OCGT: "Open-Cycle Gas"
|
||||
CCGT: "Combined-Cycle Gas"
|
||||
@ -441,3 +762,198 @@ plotting:
|
||||
H2: "Hydrogen Storage"
|
||||
lines: "Transmission Lines"
|
||||
ror: "Run of River"
|
||||
|
||||
tech_colors:
|
||||
# wind
|
||||
onwind: "#235ebc"
|
||||
onshore wind: "#235ebc"
|
||||
offwind: "#6895dd"
|
||||
offshore wind: "#6895dd"
|
||||
offwind-ac: "#6895dd"
|
||||
offshore wind (AC): "#6895dd"
|
||||
offshore wind ac: "#6895dd"
|
||||
offwind-dc: "#74c6f2"
|
||||
offshore wind (DC): "#74c6f2"
|
||||
offshore wind dc: "#74c6f2"
|
||||
# water
|
||||
hydro: '#298c81'
|
||||
hydro reservoir: '#298c81'
|
||||
ror: '#3dbfb0'
|
||||
run of river: '#3dbfb0'
|
||||
hydroelectricity: '#298c81'
|
||||
PHS: '#51dbcc'
|
||||
hydro+PHS: "#08ad97"
|
||||
wave: '#a7d4cf'
|
||||
# solar
|
||||
solar: "#f9d002"
|
||||
solar PV: "#f9d002"
|
||||
solar thermal: '#ffbf2b'
|
||||
solar rooftop: '#ffea80'
|
||||
# gas
|
||||
OCGT: '#e0986c'
|
||||
OCGT marginal: '#e0986c'
|
||||
OCGT-heat: '#e0986c'
|
||||
gas boiler: '#db6a25'
|
||||
gas boilers: '#db6a25'
|
||||
gas boiler marginal: '#db6a25'
|
||||
gas: '#e05b09'
|
||||
fossil gas: '#e05b09'
|
||||
natural gas: '#e05b09'
|
||||
CCGT: '#a85522'
|
||||
CCGT marginal: '#a85522'
|
||||
allam: '#B98F76'
|
||||
gas for industry co2 to atmosphere: '#692e0a'
|
||||
gas for industry co2 to stored: '#8a3400'
|
||||
gas for industry: '#853403'
|
||||
gas for industry CC: '#692e0a'
|
||||
gas pipeline: '#ebbca0'
|
||||
gas pipeline new: '#a87c62'
|
||||
# oil
|
||||
oil: '#c9c9c9'
|
||||
oil boiler: '#adadad'
|
||||
agriculture machinery oil: '#949494'
|
||||
shipping oil: "#808080"
|
||||
land transport oil: '#afafaf'
|
||||
# nuclear
|
||||
Nuclear: '#ff8c00'
|
||||
Nuclear marginal: '#ff8c00'
|
||||
nuclear: '#ff8c00'
|
||||
uranium: '#ff8c00'
|
||||
# coal
|
||||
Coal: '#545454'
|
||||
coal: '#545454'
|
||||
Coal marginal: '#545454'
|
||||
solid: '#545454'
|
||||
Lignite: '#826837'
|
||||
lignite: '#826837'
|
||||
Lignite marginal: '#826837'
|
||||
# biomass
|
||||
biogas: '#e3d37d'
|
||||
biomass: '#baa741'
|
||||
solid biomass: '#baa741'
|
||||
solid biomass transport: '#baa741'
|
||||
solid biomass for industry: '#7a6d26'
|
||||
solid biomass for industry CC: '#47411c'
|
||||
solid biomass for industry co2 from atmosphere: '#736412'
|
||||
solid biomass for industry co2 to stored: '#47411c'
|
||||
biomass boiler: '#8A9A5B'
|
||||
biomass to liquid: '#32CD32'
|
||||
BioSNG: '#123456'
|
||||
# power transmission
|
||||
lines: '#6c9459'
|
||||
transmission lines: '#6c9459'
|
||||
electricity distribution grid: '#97ad8c'
|
||||
# electricity demand
|
||||
Electric load: '#110d63'
|
||||
electric demand: '#110d63'
|
||||
electricity: '#110d63'
|
||||
industry electricity: '#2d2a66'
|
||||
industry new electricity: '#2d2a66'
|
||||
agriculture electricity: '#494778'
|
||||
# battery + EVs
|
||||
battery: '#ace37f'
|
||||
battery storage: '#ace37f'
|
||||
home battery: '#80c944'
|
||||
home battery storage: '#80c944'
|
||||
BEV charger: '#baf238'
|
||||
V2G: '#e5ffa8'
|
||||
land transport EV: '#baf238'
|
||||
Li ion: '#baf238'
|
||||
# hot water storage
|
||||
water tanks: '#e69487'
|
||||
hot water storage: '#e69487'
|
||||
hot water charging: '#e69487'
|
||||
hot water discharging: '#e69487'
|
||||
# heat demand
|
||||
Heat load: '#cc1f1f'
|
||||
heat: '#cc1f1f'
|
||||
heat demand: '#cc1f1f'
|
||||
rural heat: '#ff5c5c'
|
||||
central heat: '#cc1f1f'
|
||||
decentral heat: '#750606'
|
||||
low-temperature heat for industry: '#8f2727'
|
||||
process heat: '#ff0000'
|
||||
agriculture heat: '#d9a5a5'
|
||||
# heat supply
|
||||
heat pumps: '#2fb537'
|
||||
heat pump: '#2fb537'
|
||||
air heat pump: '#36eb41'
|
||||
ground heat pump: '#2fb537'
|
||||
Ambient: '#98eb9d'
|
||||
CHP: '#8a5751'
|
||||
CHP CC: '#634643'
|
||||
CHP heat: '#8a5751'
|
||||
CHP electric: '#8a5751'
|
||||
district heating: '#e8beac'
|
||||
resistive heater: '#d8f9b8'
|
||||
retrofitting: '#8487e8'
|
||||
building retrofitting: '#8487e8'
|
||||
# hydrogen
|
||||
H2 for industry: "#f073da"
|
||||
H2 for shipping: "#ebaee0"
|
||||
H2: '#bf13a0'
|
||||
hydrogen: '#bf13a0'
|
||||
SMR: '#870c71'
|
||||
SMR CC: '#4f1745'
|
||||
H2 liquefaction: '#d647bd'
|
||||
hydrogen storage: '#bf13a0'
|
||||
H2 storage: '#bf13a0'
|
||||
land transport fuel cell: '#6b3161'
|
||||
H2 pipeline: '#f081dc'
|
||||
H2 pipeline retrofitted: '#ba99b5'
|
||||
H2 Fuel Cell: '#c251ae'
|
||||
H2 Electrolysis: '#ff29d9'
|
||||
# ammonia
|
||||
NH3: '#46caf0'
|
||||
ammonia: '#46caf0'
|
||||
ammonia store: '#00ace0'
|
||||
ammonia cracker: '#87d0e6'
|
||||
Haber-Bosch: '#076987'
|
||||
# syngas
|
||||
Sabatier: '#9850ad'
|
||||
methanation: '#c44ce6'
|
||||
methane: '#c44ce6'
|
||||
helmeth: '#e899ff'
|
||||
# synfuels
|
||||
Fischer-Tropsch: '#25c49a'
|
||||
liquid: '#25c49a'
|
||||
kerosene for aviation: '#a1ffe6'
|
||||
naphtha for industry: '#57ebc4'
|
||||
methanolisation: '#83d6d5'
|
||||
methanol: '#468c8b'
|
||||
shipping methanol: '#468c8b'
|
||||
# co2
|
||||
CC: '#f29dae'
|
||||
CCS: '#f29dae'
|
||||
CO2 sequestration: '#f29dae'
|
||||
DAC: '#ff5270'
|
||||
co2 stored: '#f2385a'
|
||||
co2: '#f29dae'
|
||||
co2 vent: '#ffd4dc'
|
||||
CO2 pipeline: '#f5627f'
|
||||
# emissions
|
||||
process emissions CC: '#000000'
|
||||
process emissions: '#222222'
|
||||
process emissions to stored: '#444444'
|
||||
process emissions to atmosphere: '#888888'
|
||||
oil emissions: '#aaaaaa'
|
||||
shipping oil emissions: "#555555"
|
||||
shipping methanol emissions: '#666666'
|
||||
land transport oil emissions: '#777777'
|
||||
agriculture machinery oil emissions: '#333333'
|
||||
# other
|
||||
shipping: '#03a2ff'
|
||||
power-to-heat: '#2fb537'
|
||||
power-to-gas: '#c44ce6'
|
||||
power-to-H2: '#ff29d9'
|
||||
power-to-liquid: '#25c49a'
|
||||
gas-to-power/heat: '#ee8340'
|
||||
waste: '#e3d37d'
|
||||
other: '#000000'
|
||||
geothermal: '#ba91b1'
|
||||
AC-AC: "#70af1d"
|
||||
AC line: "#70af1d"
|
||||
links: "#8a1caf"
|
||||
HVDC links: "#8a1caf"
|
||||
DC-DC: "#8a1caf"
|
||||
DC link: "#8a1caf"
|
||||
|
||||
@ -1,318 +0,0 @@
|
||||
# SPDX-FileCopyrightText: : 2017-2023 The PyPSA-Eur Authors
|
||||
#
|
||||
# SPDX-License-Identifier: CC0-1.0
|
||||
|
||||
version: 0.7.0
|
||||
tutorial: true
|
||||
|
||||
logging:
|
||||
level: INFO
|
||||
format: '%(levelname)s:%(name)s:%(message)s'
|
||||
|
||||
run:
|
||||
name: ""
|
||||
shared_cutouts: false
|
||||
|
||||
scenario:
|
||||
simpl: ['']
|
||||
ll: ['copt']
|
||||
clusters: [5]
|
||||
opts: [Co2L-24H]
|
||||
|
||||
countries: ['BE']
|
||||
|
||||
snapshots:
|
||||
start: "2013-03-01"
|
||||
end: "2013-04-01"
|
||||
inclusive: 'left' # include start, not end
|
||||
|
||||
enable:
|
||||
prepare_links_p_nom: false
|
||||
retrieve_databundle: true
|
||||
retrieve_cost_data: true
|
||||
build_cutout: false
|
||||
retrieve_cutout: true
|
||||
build_natura_raster: false
|
||||
retrieve_natura_raster: true
|
||||
custom_busmap: false
|
||||
|
||||
electricity:
|
||||
voltages: [220., 300., 380.]
|
||||
co2limit: 100.e+6
|
||||
|
||||
extendable_carriers:
|
||||
Generator: [OCGT]
|
||||
StorageUnit: [] #battery, H2
|
||||
Store: [battery, H2]
|
||||
Link: [] # H2 pipeline
|
||||
|
||||
max_hours:
|
||||
battery: 6
|
||||
H2: 168
|
||||
|
||||
# use pandas query strings here, e.g. Country not in ['Germany']
|
||||
powerplants_filter: (DateOut >= 2022 or DateOut != DateOut)
|
||||
# use pandas query strings here, e.g. Country in ['Germany']
|
||||
custom_powerplants: false
|
||||
|
||||
conventional_carriers: [nuclear, oil, OCGT, CCGT, coal, lignite, geothermal, biomass]
|
||||
renewable_carriers: [solar, onwind, offwind-ac, offwind-dc, hydro]
|
||||
|
||||
estimate_renewable_capacities:
|
||||
enable: true
|
||||
# Add capacities from OPSD data
|
||||
from_opsd: true
|
||||
# Renewable capacities are based on existing capacities reported by IRENA
|
||||
year: 2020
|
||||
# Artificially limit maximum capacities to factor * (IRENA capacities),
|
||||
# i.e. 110% of <years>'s capacities => expansion_limit: 1.1
|
||||
# false: Use estimated renewable potentials determine by the workflow
|
||||
expansion_limit: false
|
||||
technology_mapping:
|
||||
# Wind is the Fueltype in powerplantmatching, onwind, offwind-{ac,dc} the carrier in PyPSA-Eur
|
||||
Offshore: [offwind-ac, offwind-dc]
|
||||
Onshore: [onwind]
|
||||
PV: [solar]
|
||||
|
||||
atlite:
|
||||
nprocesses: 4
|
||||
show_progress: false # false saves time
|
||||
cutouts:
|
||||
be-03-2013-era5:
|
||||
module: era5
|
||||
x: [4., 15.]
|
||||
y: [46., 56.]
|
||||
time: ["2013-03", "2013-03"]
|
||||
|
||||
renewable:
|
||||
onwind:
|
||||
cutout: be-03-2013-era5
|
||||
resource:
|
||||
method: wind
|
||||
turbine: Vestas_V112_3MW
|
||||
capacity_per_sqkm: 3 # ScholzPhd Tab 4.3.1: 10MW/km^2
|
||||
# correction_factor: 0.93
|
||||
corine:
|
||||
# Scholz, Y. (2012). Renewable energy based electricity supply at low costs:
|
||||
# development of the REMix model and application for Europe. ( p.42 / p.28)
|
||||
grid_codes: [12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 31, 32]
|
||||
distance: 1000
|
||||
distance_grid_codes: [1, 2, 3, 4, 5, 6]
|
||||
natura: true
|
||||
excluder_resolution: 200
|
||||
potential: simple # or conservative
|
||||
clip_p_max_pu: 1.e-2
|
||||
offwind-ac:
|
||||
cutout: be-03-2013-era5
|
||||
resource:
|
||||
method: wind
|
||||
turbine: NREL_ReferenceTurbine_5MW_offshore
|
||||
capacity_per_sqkm: 3
|
||||
# correction_factor: 0.93
|
||||
corine: [44, 255]
|
||||
natura: true
|
||||
ship_threshold: 400
|
||||
max_shore_distance: 30000
|
||||
excluder_resolution: 200
|
||||
potential: simple # or conservative
|
||||
clip_p_max_pu: 1.e-2
|
||||
offwind-dc:
|
||||
cutout: be-03-2013-era5
|
||||
resource:
|
||||
method: wind
|
||||
turbine: NREL_ReferenceTurbine_5MW_offshore
|
||||
# ScholzPhd Tab 4.3.1: 10MW/km^2
|
||||
capacity_per_sqkm: 3
|
||||
# correction_factor: 0.93
|
||||
corine: [44, 255]
|
||||
natura: true
|
||||
ship_threshold: 400
|
||||
min_shore_distance: 30000
|
||||
excluder_resolution: 200
|
||||
potential: simple # or conservative
|
||||
clip_p_max_pu: 1.e-2
|
||||
solar:
|
||||
cutout: be-03-2013-era5
|
||||
resource:
|
||||
method: pv
|
||||
panel: CSi
|
||||
orientation:
|
||||
slope: 35.
|
||||
azimuth: 180.
|
||||
capacity_per_sqkm: 1.7 # ScholzPhd Tab 4.3.1: 170 MW/km^2
|
||||
# Correction factor determined by comparing uncorrected area-weighted full-load hours to those
|
||||
# published in Supplementary Data to
|
||||
# Pietzcker, Robert Carl, et al. "Using the sun to decarbonize the power
|
||||
# sector: The economic potential of photovoltaics and concentrating solar
|
||||
# power." Applied Energy 135 (2014): 704-720.
|
||||
# This correction factor of 0.854337 may be in order if using reanalysis data.
|
||||
# correction_factor: 0.854337
|
||||
corine: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 26, 31, 32]
|
||||
natura: true
|
||||
excluder_resolution: 200
|
||||
potential: simple # or conservative
|
||||
clip_p_max_pu: 1.e-2
|
||||
|
||||
lines:
|
||||
types:
|
||||
220.: "Al/St 240/40 2-bundle 220.0"
|
||||
300.: "Al/St 240/40 3-bundle 300.0"
|
||||
380.: "Al/St 240/40 4-bundle 380.0"
|
||||
s_max_pu: 0.7
|
||||
s_nom_max: .inf
|
||||
length_factor: 1.25
|
||||
under_construction: 'zero' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity
|
||||
|
||||
links:
|
||||
p_max_pu: 1.0
|
||||
p_nom_max: .inf
|
||||
include_tyndp: true
|
||||
under_construction: 'zero' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity
|
||||
|
||||
transformers:
|
||||
x: 0.1
|
||||
s_nom: 2000.
|
||||
type: ''
|
||||
|
||||
load:
|
||||
power_statistics: true # only for files from <2019; set false in order to get ENTSOE transparency data
|
||||
interpolate_limit: 3 # data gaps up until this size are interpolated linearly
|
||||
time_shift_for_large_gaps: 1w # data gaps up until this size are copied by copying from
|
||||
manual_adjustments: true # false
|
||||
scaling_factor: 1.0
|
||||
|
||||
costs:
|
||||
year: 2030
|
||||
version: v0.5.0
|
||||
rooftop_share: 0.14
|
||||
fill_values:
|
||||
FOM: 0
|
||||
VOM: 0
|
||||
efficiency: 1
|
||||
fuel: 0
|
||||
investment: 0
|
||||
lifetime: 25
|
||||
"CO2 intensity": 0
|
||||
"discount rate": 0.07
|
||||
marginal_cost:
|
||||
solar: 0.01
|
||||
onwind: 0.015
|
||||
offwind: 0.015
|
||||
H2: 0.
|
||||
battery: 0.
|
||||
emission_prices: # in currency per tonne emission, only used with the option Ep
|
||||
co2: 0.
|
||||
|
||||
clustering:
|
||||
simplify_network:
|
||||
to_substations: false # network is simplified to nodes with positive or negative power injection (i.e. substations or offwind connections)
|
||||
algorithm: kmeans # choose from: [hac, kmeans]
|
||||
feature: solar+onwind-time # only for hac. choose from: [solar+onwind-time, solar+onwind-cap, solar-time, solar-cap, solar+offwind-cap] etc.
|
||||
exclude_carriers: []
|
||||
cluster_network:
|
||||
algorithm: kmeans
|
||||
feature: solar+onwind-time
|
||||
exclude_carriers: []
|
||||
aggregation_strategies:
|
||||
generators:
|
||||
p_nom_max: sum # use "min" for more conservative assumptions
|
||||
p_nom_min: sum
|
||||
p_min_pu: mean
|
||||
marginal_cost: mean
|
||||
committable: any
|
||||
ramp_limit_up: max
|
||||
ramp_limit_down: max
|
||||
efficiency: mean
|
||||
|
||||
solving:
|
||||
options:
|
||||
formulation: kirchhoff
|
||||
load_shedding: false
|
||||
noisy_costs: true
|
||||
min_iterations: 1
|
||||
max_iterations: 1
|
||||
clip_p_max_pu: 0.01
|
||||
skip_iterations: false
|
||||
track_iterations: false
|
||||
solver:
|
||||
name: cbc
|
||||
|
||||
plotting:
|
||||
map:
|
||||
figsize: [7, 7]
|
||||
boundaries: [-10.2, 29, 35, 72]
|
||||
p_nom:
|
||||
bus_size_factor: 5.e+4
|
||||
linewidth_factor: 3.e+3
|
||||
|
||||
costs_max: 800
|
||||
costs_threshold: 1
|
||||
|
||||
energy_max: 15000.
|
||||
energy_min: -10000.
|
||||
energy_threshold: 50.
|
||||
|
||||
vre_techs: ["onwind", "offwind-ac", "offwind-dc", "solar", "ror"]
|
||||
conv_techs: ["OCGT", "CCGT", "Nuclear", "Coal"]
|
||||
storage_techs: ["hydro+PHS", "battery", "H2"]
|
||||
load_carriers: ["AC load"]
|
||||
AC_carriers: ["AC line", "AC transformer"]
|
||||
link_carriers: ["DC line", "Converter AC-DC"]
|
||||
tech_colors:
|
||||
"onwind": "#235ebc"
|
||||
"onshore wind": "#235ebc"
|
||||
'offwind': "#6895dd"
|
||||
'offwind-ac': "#6895dd"
|
||||
'offshore wind': "#6895dd"
|
||||
'offshore wind ac': "#6895dd"
|
||||
'offwind-dc': "#74c6f2"
|
||||
'offshore wind dc': "#74c6f2"
|
||||
"hydro": "#08ad97"
|
||||
"hydro+PHS": "#08ad97"
|
||||
"PHS": "#08ad97"
|
||||
"hydro reservoir": "#08ad97"
|
||||
'hydroelectricity': '#08ad97'
|
||||
"ror": "#4adbc8"
|
||||
"run of river": "#4adbc8"
|
||||
'solar': "#f9d002"
|
||||
'solar PV': "#f9d002"
|
||||
'solar thermal': '#ffef60'
|
||||
'biomass': '#0c6013'
|
||||
'solid biomass': '#06540d'
|
||||
'biogas': '#23932d'
|
||||
'waste': '#68896b'
|
||||
'geothermal': '#ba91b1'
|
||||
"OCGT": "#d35050"
|
||||
"gas": "#d35050"
|
||||
"natural gas": "#d35050"
|
||||
"CCGT": "#b20101"
|
||||
"nuclear": "#ff9000"
|
||||
"coal": "#707070"
|
||||
"lignite": "#9e5a01"
|
||||
"oil": "#262626"
|
||||
"H2": "#ea048a"
|
||||
"hydrogen storage": "#ea048a"
|
||||
"battery": "#b8ea04"
|
||||
"Electric load": "#f9d002"
|
||||
"electricity": "#f9d002"
|
||||
"lines": "#70af1d"
|
||||
"transmission lines": "#70af1d"
|
||||
"AC-AC": "#70af1d"
|
||||
"AC line": "#70af1d"
|
||||
"links": "#8a1caf"
|
||||
"HVDC links": "#8a1caf"
|
||||
"DC-DC": "#8a1caf"
|
||||
"DC link": "#8a1caf"
|
||||
nice_names:
|
||||
OCGT: "Open-Cycle Gas"
|
||||
CCGT: "Combined-Cycle Gas"
|
||||
offwind-ac: "Offshore Wind (AC)"
|
||||
offwind-dc: "Offshore Wind (DC)"
|
||||
onwind: "Onshore Wind"
|
||||
solar: "Solar"
|
||||
PHS: "Pumped Hydro Storage"
|
||||
hydro: "Reservoir & Dam"
|
||||
battery: "Battery Storage"
|
||||
H2: "Hydrogen Storage"
|
||||
lines: "Transmission Lines"
|
||||
ror: "Run of River"
|
||||
861
data/attributed_ports.json
Normal file
861
data/attributed_ports.json
Normal file
@ -0,0 +1,861 @@
|
||||
{
|
||||
"type": "FeatureCollection",
|
||||
"features": [
|
||||
{ "type": "Feature", "properties": { "Country": "United Arab Emirates", "Function": "1-345---", "LOCODE": "AEAUH", "Name": "Abu Dhabi", "NameWoDiac": "Abu Dhabi", "Status": "AI", "outflows": 41597.142851999997 }, "geometry": { "type": "Point", "coordinates": [ 54.366666666666667, 24.466666666666665 ] } },
|
||||
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{ "type": "Feature", "properties": { "Country": "Brazil", "Function": "1-34----", "LOCODE": "BRNVT", "Name": "Navegantes", "NameWoDiac": "Navegantes", "Status": "AI", "outflows": 10279036.91334 }, "geometry": { "type": "Point", "coordinates": [ -48.65, -26.9 ] } },
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{ "type": "Feature", "properties": { "Country": "Brazil", "Function": "12------", "LOCODE": "BRPEC", "Name": "Pecém Pt\/São Gonçalo do Amarante", "NameWoDiac": "Pecem Pt\/Sao Goncalo do Amarante", "Status": "AA", "outflows": 2174063.6046599997 }, "geometry": { "type": "Point", "coordinates": [ -38.866666666666667, -3.533333333333333 ] } },
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{ "type": "Feature", "properties": { "Country": "Brazil", "Function": "1-34----", "LOCODE": "BRSLZ", "Name": "São Luís", "NameWoDiac": "Sao Luis", "Status": "AI", "outflows": 45240.0 }, "geometry": { "type": "Point", "coordinates": [ -44.3, -2.5 ] } },
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{ "type": "Feature", "properties": { "Country": "Brazil", "Function": "1-------", "LOCODE": "BRVIX", "Name": "Vitória Pt", "NameWoDiac": "Vitoria Pt", "Status": "AA", "outflows": 738129.52788000007 }, "geometry": { "type": "Point", "coordinates": [ -40.333333333333336, -20.316666666666666 ] } },
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{ "type": "Feature", "properties": { "Country": "Canada", "Function": "1-34-6--", "LOCODE": "CASJB", "Name": "Saint-John", "NameWoDiac": "Saint-John", "Status": "AS", "outflows": 389420.2 }, "geometry": { "type": "Point", "coordinates": [ -66.066666666666663, 45.266666666666666 ] } },
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{ "type": "Feature", "properties": { "Country": "Canada", "Function": "1-3-----", "LOCODE": "CASJF", "Name": "Saint-John's", "NameWoDiac": "Saint-John's", "Status": "AS", "outflows": 26845.0 }, "geometry": { "type": "Point", "coordinates": [ -52.733333333333334, 47.56666666666667 ] } },
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{ "type": "Feature", "properties": { "Country": "Congo", "Function": "1--45---", "LOCODE": "CGPNR", "Name": "Pointe Noire", "NameWoDiac": "Pointe Noire", "Status": "AI", "outflows": 3473713.5811700015 }, "geometry": { "type": "Point", "coordinates": [ 11.85, -4.8 ] } },
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{ "type": "Feature", "properties": { "Country": "Chile", "Function": "1--4----", "LOCODE": "CLIQQ", "Name": "Iquique", "NameWoDiac": "Iquique", "Status": "AI", "outflows": 1915647.5 }, "geometry": { "type": "Point", "coordinates": [ -70.13333333333334, -20.216666666666665 ] } },
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{ "type": "Feature", "properties": { "Country": "Chile", "Function": "123-----", "LOCODE": "CLLQN", "Name": "Lirquén", "NameWoDiac": "Lirquen", "Status": "AI", "outflows": 3185838.4995000004 }, "geometry": { "type": "Point", "coordinates": [ -72.983333333333334, -36.7 ] } },
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{ "type": "Feature", "properties": { "Country": "Chile", "Function": "1-------", "LOCODE": "CLMJS", "Name": "Mejillones", "NameWoDiac": "Mejillones", "Status": "AI", "outflows": 32362.2 }, "geometry": { "type": "Point", "coordinates": [ -70.45, -23.1 ] } },
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{ "type": "Feature", "properties": { "Country": "Chile", "Function": "123-----", "LOCODE": "CLPAG", "Name": "Puerto Angamos", "NameWoDiac": "Puerto Angamos", "Status": "RL", "outflows": 5408319.3663000017 }, "geometry": { "type": "Point", "coordinates": [ -70.45, -23.083333333333332 ] } },
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{ "type": "Feature", "properties": { "Country": "Chile", "Function": "1-34----", "LOCODE": "CLPUQ", "Name": "Punta Arenas", "NameWoDiac": "Punta Arenas", "Status": "AI", "outflows": 18174.0 }, "geometry": { "type": "Point", "coordinates": [ -70.933333333333337, -53.133333333333333 ] } },
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{ "type": "Feature", "properties": { "Country": "Chile", "Function": "123-----", "LOCODE": "CLSAI", "Name": "San Antonio", "NameWoDiac": "San Antonio", "Status": "AI", "outflows": 9417069.025 }, "geometry": { "type": "Point", "coordinates": [ -71.6, -33.6 ] } },
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{ "type": "Feature", "properties": { "Country": "Chile", "Function": "1-3-----", "LOCODE": "CLSVE", "Name": "San Vicente", "NameWoDiac": "San Vicente", "Status": "AI", "outflows": 945075.625 }, "geometry": { "type": "Point", "coordinates": [ -73.13333333333334, -36.7 ] } },
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{ "type": "Feature", "properties": { "Country": "China", "Function": "1-------", "LOCODE": "CNCFD", "Name": "Caofeidian Pt", "NameWoDiac": "Caofeidian Pt", "Status": "AS", "outflows": 168350.0 }, "geometry": { "type": "Point", "coordinates": [ 118.533333333333331, 38.95 ] } },
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{ "type": "Feature", "properties": { "Country": "China", "Function": "1----6--", "LOCODE": "CNDCB", "Name": "DA CHAN BAY", "NameWoDiac": "DA CHAN BAY", "Status": "RL", "outflows": 4367401.0713399984 }, "geometry": { "type": "Point", "coordinates": [ 113.86666666666666, 22.533333333333335 ] } },
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{ "type": "Feature", "properties": { "Country": "China", "Function": "1-------", "LOCODE": "CNDGG", "Name": "Dongguan Pt", "NameWoDiac": "Dongguan Pt", "Status": "AS", "outflows": 94354.0 }, "geometry": { "type": "Point", "coordinates": [ 113.75, 23.033333333333335 ] } },
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{ "type": "Feature", "properties": { "Country": "China", "Function": "1-------", "LOCODE": "CNDJK", "Name": "Dongjiangkou", "NameWoDiac": "Dongjiangkou", "Status": "AS", "outflows": 386750.0 }, "geometry": { "type": "Point", "coordinates": [ 119.52253982618285, 35.308885331582253 ] } },
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{ "type": "Feature", "properties": { "Country": "China", "Function": "--3-----", "LOCODE": "CNFQG", "Name": "Fuqing", "NameWoDiac": "Fuqing", "Status": "RL", "outflows": 1164780.9333599997 }, "geometry": { "type": "Point", "coordinates": [ 119.36666666666666, 25.716666666666665 ] } },
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{ "type": "Feature", "properties": { "Country": "China", "Function": "1-------", "LOCODE": "CNHUI", "Name": "Huizhou Pt", "NameWoDiac": "Huizhou Pt", "Status": "AS", "outflows": 27300.0 }, "geometry": { "type": "Point", "coordinates": [ 114.36666666666666, 23.083333333333332 ] } },
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{ "type": "Feature", "properties": { "Country": "China", "Function": "1-------", "LOCODE": "CNHMN", "Name": "Humen Pt", "NameWoDiac": "Humen Pt", "Status": "AS", "outflows": 630027.5 }, "geometry": { "type": "Point", "coordinates": [ 113.666666666666671, 22.833333333333332 ] } },
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{ "type": "Feature", "properties": { "Country": "China", "Function": "1-3-----", "LOCODE": "CNJGY", "Name": "Jiangyin", "NameWoDiac": "Jiangyin", "Status": "RL", "outflows": 594906.0 }, "geometry": { "type": "Point", "coordinates": [ 119.3, 25.466666666666665 ] } },
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{ "type": "Feature", "properties": { "Country": "China", "Function": "1-------", "LOCODE": "CNJNZ", "Name": "Jinzhou Pt", "NameWoDiac": "Jinzhou Pt", "Status": "AS", "outflows": 684866.0 }, "geometry": { "type": "Point", "coordinates": [ 121.15, 41.116666666666667 ] } },
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{ "type": "Feature", "properties": { "Country": "China", "Function": "1-------", "LOCODE": "CNLYG", "Name": "Lianyungang", "NameWoDiac": "Lianyungang", "Status": "AS", "outflows": 9288988.8094500005 }, "geometry": { "type": "Point", "coordinates": [ 119.433333333333337, 34.716666666666669 ] } },
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{ "type": "Feature", "properties": { "Country": "China", "Function": "1-------", "LOCODE": "CNNSA", "Name": "Nansha Pt", "NameWoDiac": "Nansha Pt", "Status": "AS", "outflows": 42484636.038412996 }, "geometry": { "type": "Point", "coordinates": [ 113.583333333333329, 22.75 ] } },
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{ "type": "Feature", "properties": { "Country": "China", "Function": "1-------", "LOCODE": "CNNTG", "Name": "Nantong Pt", "NameWoDiac": "Nantong Pt", "Status": "AS", "outflows": 261618.5 }, "geometry": { "type": "Point", "coordinates": [ 120.85, 32.016666666666666 ] } },
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{ "type": "Feature", "properties": { "Country": "Spain", "Function": "123-----", "LOCODE": "ESCAS", "Name": "Castellón de la Plana", "NameWoDiac": "Castellon de la Plana", "Status": "AI", "outflows": 2188540.79158 }, "geometry": { "type": "Point", "coordinates": [ -0.033333333333333, 39.983333333333334 ] } },
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{ "type": "Feature", "properties": { "Country": "Spain", "Function": "123-----", "LOCODE": "ESFRO", "Name": "Ferrol", "NameWoDiac": "Ferrol", "Status": "AI", "outflows": 165064.5 }, "geometry": { "type": "Point", "coordinates": [ -8.25, 43.483333333333334 ] } },
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{ "type": "Feature", "properties": { "Country": "Spain", "Function": "1--45---", "LOCODE": "ESAGP", "Name": "Málaga", "NameWoDiac": "Malaga", "Status": "AI", "outflows": 439868.0 }, "geometry": { "type": "Point", "coordinates": [ -4.416666666666667, 36.716666666666669 ] } },
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{ "type": "Feature", "properties": { "Country": "Spain", "Function": "1-34----", "LOCODE": "ESMLN", "Name": "Melilla", "NameWoDiac": "Melilla", "Status": "AI", "outflows": 45500.0 }, "geometry": { "type": "Point", "coordinates": [ -2.883333333333333, 35.31666666666667 ] } },
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{ "type": "Feature", "properties": { "Country": "Spain", "Function": "123-----", "LOCODE": "ESSAG", "Name": "Sagunto", "NameWoDiac": "Sagunto", "Status": "AI", "outflows": 417560.0 }, "geometry": { "type": "Point", "coordinates": [ -0.266666666666667, 39.68333333333333 ] } },
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{ "type": "Feature", "properties": { "Country": "Spain", "Function": "1--4----", "LOCODE": "ESSPC", "Name": "Santa Cruz de La Palma", "NameWoDiac": "Santa Cruz de La Palma", "Status": "AI", "outflows": 245440.0 }, "geometry": { "type": "Point", "coordinates": [ -17.766666666666666, 28.683333333333334 ] } },
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{ "type": "Feature", "properties": { "Country": "Spain", "Function": "1-3-----", "LOCODE": "ESVIL", "Name": "Villagarcía de Arosa", "NameWoDiac": "Villagarcia de Arosa", "Status": "AI", "outflows": 130988.0 }, "geometry": { "type": "Point", "coordinates": [ -8.75, 42.6 ] } },
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{ "type": "Feature", "properties": { "Country": "Finland", "Function": "1-34----", "LOCODE": "FITKU", "Name": "Turku (Åbo)", "NameWoDiac": "Turku (Abo)", "Status": "AI", "outflows": 16263.0 }, "geometry": { "type": "Point", "coordinates": [ 22.283333333333335, 60.45 ] } },
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{ "type": "Feature", "properties": { "Country": "Finland", "Function": "1-34----", "LOCODE": "FIPOR", "Name": "Björneborg (Pori)", "NameWoDiac": "Bjorneborg (Pori)", "Status": "AI", "outflows": 5220.0 }, "geometry": { "type": "Point", "coordinates": [ 21.8, 61.483333333333334 ] } },
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{ "type": "Feature", "properties": { "Country": "Finland", "Function": "1-34----", "LOCODE": "FIPOR", "Name": "Pori (Björneborg)", "NameWoDiac": "Pori (Bjorneborg)", "Status": "AI", "outflows": 5220.0 }, "geometry": { "type": "Point", "coordinates": [ 21.8, 61.483333333333334 ] } },
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{ "type": "Feature", "properties": { "Country": "Finland", "Function": "1-------", "LOCODE": "FIHMN", "Name": "Fredrikshamn (Hamina)", "NameWoDiac": "Fredrikshamn (Hamina)", "Status": "AI", "outflows": 4437.0 }, "geometry": { "type": "Point", "coordinates": [ 27.2, 60.56666666666667 ] } },
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{ "type": "Feature", "properties": { "Country": "Finland", "Function": "1-------", "LOCODE": "FIHMN", "Name": "Hamina (Fredrikshamn)", "NameWoDiac": "Hamina (Fredrikshamn)", "Status": "AI", "outflows": 4437.0 }, "geometry": { "type": "Point", "coordinates": [ 27.2, 60.56666666666667 ] } },
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{ "type": "Feature", "properties": { "Country": "Finland", "Function": "123-----", "LOCODE": "FIPRS", "Name": "Pietarsaari (Jakobstad)", "NameWoDiac": "Pietarsaari (Jakobstad)", "Status": "AI", "outflows": 9396.0 }, "geometry": { "type": "Point", "coordinates": [ 22.783333333333335, 63.68333333333333 ] } },
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{ "type": "Feature", "properties": { "Country": "Finland", "Function": "1-------", "LOCODE": "FITOR", "Name": "Tornio (Torneå)", "NameWoDiac": "Tornio (Tornea)", "Status": "AI", "outflows": 91624.0 }, "geometry": { "type": "Point", "coordinates": [ 24.183333333333334, 65.85 ] } },
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{ "type": "Feature", "properties": { "Country": "France", "Function": "12345---", "LOCODE": "FRLEH", "Name": "Le Havre", "NameWoDiac": "Le Havre", "Status": "AF", "outflows": 35976285.665610015 }, "geometry": { "type": "Point", "coordinates": [ 0.1, 49.5 ] } },
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{ "type": "Feature", "properties": { "Country": "France", "Function": "123-----", "LOCODE": "FRSET", "Name": "Sète", "NameWoDiac": "Sete", "Status": "AF", "outflows": 34041.0 }, "geometry": { "type": "Point", "coordinates": [ 3.7, 43.4 ] } },
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{ "type": "Feature", "properties": { "Country": "France", "Function": "12-4----", "LOCODE": "FRTLN", "Name": "Toulon", "NameWoDiac": "Toulon", "Status": "AF", "outflows": 1080.0 }, "geometry": { "type": "Point", "coordinates": [ 5.933333333333334, 43.116666666666667 ] } },
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{ "type": "Feature", "properties": { "Country": "United Kingdom", "Function": "1-------", "LOCODE": "GBGRG", "Name": "Grangemouth", "NameWoDiac": "Grangemouth", "Status": "AF", "outflows": 192244.0 }, "geometry": { "type": "Point", "coordinates": [ -3.716666666666667, 56.0 ] } },
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{ "type": "Feature", "properties": { "Country": "United Kingdom", "Function": "1-------", "LOCODE": "GBHUL", "Name": "Hull", "NameWoDiac": "Hull", "Status": "AF", "outflows": 219740.33333800005 }, "geometry": { "type": "Point", "coordinates": [ -0.316666666666667, 53.733333333333334 ] } },
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{ "type": "Feature", "properties": { "Country": "United Kingdom", "Function": "1-------", "LOCODE": "GBIMM", "Name": "Immingham", "NameWoDiac": "Immingham", "Status": "AF", "outflows": 329625.0 }, "geometry": { "type": "Point", "coordinates": [ -0.216666666666667, 53.6 ] } },
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{ "type": "Feature", "properties": { "Country": "United Kingdom", "Function": "1--4----", "LOCODE": "GBLIV", "Name": "Liverpool", "NameWoDiac": "Liverpool", "Status": "AF", "outflows": 1673890.2916200003 }, "geometry": { "type": "Point", "coordinates": [ -3.0, 53.416666666666664 ] } },
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{ "type": "Feature", "properties": { "Country": "United Kingdom", "Function": "1-------", "LOCODE": "GBTYN", "Name": "Tyne", "NameWoDiac": "Tyne", "Status": "RQ", "outflows": 31668.0 }, "geometry": { "type": "Point", "coordinates": [ -1.433333333333333, 55.0 ] } },
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{ "type": "Feature", "properties": { "Country": "Greece", "Function": "1--4----", "LOCODE": "GRHER", "Name": "Iraklion (Heraklion)", "NameWoDiac": "Iraklion (Heraklion)", "Status": "AI", "outflows": 23582.0 }, "geometry": { "type": "Point", "coordinates": [ 25.166666666666668, 35.333333333333336 ] } },
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{ "type": "Feature", "properties": { "Country": "Croatia", "Function": "1234----", "LOCODE": "HRRJK", "Name": "Rijeka", "NameWoDiac": "Rijeka", "Status": "AI", "outflows": 3818455.3333799997 }, "geometry": { "type": "Point", "coordinates": [ 14.4, 45.333333333333336 ] } },
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{ "type": "Feature", "properties": { "Country": "Croatia", "Function": "1234----", "LOCODE": "HRSPU", "Name": "Split", "NameWoDiac": "Split", "Status": "AI", "outflows": 63609.0 }, "geometry": { "type": "Point", "coordinates": [ 16.45, 43.5 ] } },
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{ "type": "Feature", "properties": { "Country": "Haiti", "Function": "1-------", "LOCODE": "HTLFF", "Name": "Lafiteau", "NameWoDiac": "Lafiteau", "Status": "AI", "outflows": 1098127.3333000003 }, "geometry": { "type": "Point", "coordinates": [ -72.433333333333337, 18.483333333333334 ] } },
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{ "type": "Feature", "properties": { "Country": "Indonesia", "Function": "1--4----", "LOCODE": "IDBPN", "Name": "Balikpapan", "NameWoDiac": "Balikpapan", "Status": "AI", "outflows": 77320.75 }, "geometry": { "type": "Point", "coordinates": [ 116.833333333333329, -1.283333333333333 ] } },
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{ "type": "Feature", "properties": { "Country": "Indonesia", "Function": "1-3-----", "LOCODE": "IDBTM", "Name": "Batam Island", "NameWoDiac": "Batam Island", "Status": "RL", "outflows": 7335.5 }, "geometry": { "type": "Point", "coordinates": [ 104.033333333333331, 1.083333333333333 ] } },
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{ "type": "Feature", "properties": { "Country": "Indonesia", "Function": "1-------", "LOCODE": "IDBEN", "Name": "Benete", "NameWoDiac": "Benete", "Status": "RL", "outflows": 12681.75 }, "geometry": { "type": "Point", "coordinates": [ 116.716666666666669, -8.866666666666667 ] } },
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{ "type": "Feature", "properties": { "Country": "Indonesia", "Function": "1-------", "LOCODE": "IDBOA", "Name": "Benoa", "NameWoDiac": "Benoa", "Status": "RL", "outflows": 6747.0 }, "geometry": { "type": "Point", "coordinates": [ 115.216666666666669, -8.766666666666667 ] } },
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{ "type": "Feature", "properties": { "Country": "Indonesia", "Function": "1-345---", "LOCODE": "IDDJJ", "Name": "Jayapura, Irian Jaya", "NameWoDiac": "Jayapura, Irian Jaya", "Status": "AI", "outflows": 136162.0 }, "geometry": { "type": "Point", "coordinates": [ 140.7, -2.533333333333333 ] } },
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{ "type": "Feature", "properties": { "Country": "Indonesia", "Function": "1-3-----", "LOCODE": "IDKUM", "Name": "Kumai", "NameWoDiac": "Kumai", "Status": "RL", "outflows": 4238.0 }, "geometry": { "type": "Point", "coordinates": [ 111.716666666666669, -2.733333333333333 ] } },
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{ "type": "Feature", "properties": { "Country": "Indonesia", "Function": "1-3-----", "LOCODE": "IDMAK", "Name": "Makassar", "NameWoDiac": "Makassar", "Status": "RL", "outflows": 664450.0 }, "geometry": { "type": "Point", "coordinates": [ 119.4, -5.116666666666666 ] } },
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{ "type": "Feature", "properties": { "Country": "Indonesia", "Function": "1234----", "LOCODE": "IDPDG", "Name": "Padang", "NameWoDiac": "Padang", "Status": "AI", "outflows": 74470.25 }, "geometry": { "type": "Point", "coordinates": [ 100.35, -0.95 ] } },
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{ "type": "Feature", "properties": { "Country": "Indonesia", "Function": "1-3-----", "LOCODE": "IDPER", "Name": "Perawang", "NameWoDiac": "Perawang", "Status": "RL", "outflows": 3627.0 }, "geometry": { "type": "Point", "coordinates": [ 102.86666666666666, 1.066666666666667 ] } },
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{ "type": "Feature", "properties": { "Country": "Indonesia", "Function": "1-345---", "LOCODE": "IDSRG", "Name": "Semarang", "NameWoDiac": "Semarang", "Status": "AI", "outflows": 2529727.4165999996 }, "geometry": { "type": "Point", "coordinates": [ 110.483333333333334, -6.966666666666667 ] } },
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{ "type": "Feature", "properties": { "Country": "Indonesia", "Function": "123456--", "LOCODE": "IDSUB", "Name": "Surabaya", "NameWoDiac": "Surabaya", "Status": "AI", "outflows": 5004081.1427500024 }, "geometry": { "type": "Point", "coordinates": [ 112.75, -7.233333333333333 ] } },
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{ "type": "Feature", "properties": { "Country": "Indonesia", "Function": "1--4----", "LOCODE": "IDTNJ", "Name": "Tanjungpinang", "NameWoDiac": "Tanjungpinang", "Status": "AI", "outflows": 3068.0 }, "geometry": { "type": "Point", "coordinates": [ 104.45, 0.916666666666667 ] } },
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{ "type": "Feature", "properties": { "Country": "Indonesia", "Function": "1-------", "LOCODE": "IDTMK", "Name": "Timika", "NameWoDiac": "Timika", "Status": "RQ", "outflows": 3240.0 }, "geometry": { "type": "Point", "coordinates": [ 136.55, -4.75 ] } },
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{ "type": "Feature", "properties": { "Country": "Indonesia", "Function": "1-------", "LOCODE": "IDTUA", "Name": "Tual", "NameWoDiac": "Tual", "Status": "RQ", "outflows": 12207.0 }, "geometry": { "type": "Point", "coordinates": [ 132.73333333333332, -5.633333333333333 ] } },
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{ "type": "Feature", "properties": { "Country": "Ireland", "Function": "1-345---", "LOCODE": "IEWAT", "Name": "Waterford", "NameWoDiac": "Waterford", "Status": "AF", "outflows": 86515.0 }, "geometry": { "type": "Point", "coordinates": [ -7.1, 52.25 ] } },
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{ "type": "Feature", "properties": { "Country": "Mexico", "Function": "1--4----", "LOCODE": "MXGYM", "Name": "Guaymas", "NameWoDiac": "Guaymas", "Status": "AI", "outflows": 15320.0 }, "geometry": { "type": "Point", "coordinates": [ -110.88333333333334, 27.916666666666668 ] } },
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{ "type": "Feature", "properties": { "Country": "Mexico", "Function": "1-------", "LOCODE": "MXLZC", "Name": "Lázaro Cárdenas", "NameWoDiac": "Lazaro Cardenas", "Status": "AI", "outflows": 9280527.0998299997 }, "geometry": { "type": "Point", "coordinates": [ -102.183333333333337, 17.95 ] } },
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{ "type": "Feature", "properties": { "Country": "Mexico", "Function": "1--4----", "LOCODE": "MXMZT", "Name": "Mazatlan", "NameWoDiac": "Mazatlan", "Status": "AI", "outflows": 258563.0 }, "geometry": { "type": "Point", "coordinates": [ -106.4, 23.4 ] } },
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{ "type": "Feature", "properties": { "Country": "Mexico", "Function": "--3-----", "LOCODE": "MXPRO", "Name": "Paraiso", "NameWoDiac": "Paraiso", "Status": "RL", "outflows": 771394.2 }, "geometry": { "type": "Point", "coordinates": [ -92.2, 18.183333333333334 ] } },
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{ "type": "Feature", "properties": { "Country": "Mexico", "Function": "1--4----", "LOCODE": "MXTAM", "Name": "Tampico", "NameWoDiac": "Tampico", "Status": "AI", "outflows": 33951.0 }, "geometry": { "type": "Point", "coordinates": [ -97.86666666666666, 22.25 ] } },
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{ "type": "Feature", "properties": { "Country": "Mexico", "Function": "1-------", "LOCODE": "MXTUX", "Name": "Tuxpan", "NameWoDiac": "Tuxpan", "Status": "AI", "outflows": 21541.0 }, "geometry": { "type": "Point", "coordinates": [ -97.4, 20.95 ] } },
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{ "type": "Feature", "properties": { "Country": "Malaysia", "Function": "123-----", "LOCODE": "MYTPP", "Name": "Tanjung Pelepas", "NameWoDiac": "Tanjung Pelepas", "Status": "RL", "outflows": 36861511.888539977 }, "geometry": { "type": "Point", "coordinates": [ 103.55, 1.366666666666667 ] } },
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{ "type": "Feature", "properties": { "Country": "Netherlands", "Function": "123-----", "LOCODE": "NLVLI", "Name": "Vlissingen", "NameWoDiac": "Vlissingen", "Status": "AF", "outflows": 935022.40001200011 }, "geometry": { "type": "Point", "coordinates": [ 3.7, 51.45 ] } },
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{ "type": "Feature", "properties": { "Country": "Norway", "Function": "1-3-----", "LOCODE": "NOHRD", "Name": "Harstad", "NameWoDiac": "Harstad", "Status": "AA", "outflows": 9516.0 }, "geometry": { "type": "Point", "coordinates": [ 16.533333333333335, 68.783333333333331 ] } },
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{ "type": "Feature", "properties": { "Country": "Norway", "Function": "1234----", "LOCODE": "NOSVG", "Name": "Stavanger", "NameWoDiac": "Stavanger", "Status": "AI", "outflows": 99528.0 }, "geometry": { "type": "Point", "coordinates": [ 5.75, 58.966666666666669 ] } },
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{ "type": "Feature", "properties": { "Country": "Norway", "Function": "1-34----", "LOCODE": "NOSKN", "Name": "Stokmarknes", "NameWoDiac": "Stokmarknes", "Status": "AA", "outflows": 34164.0 }, "geometry": { "type": "Point", "coordinates": [ 14.9, 68.566666666666663 ] } },
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{ "type": "Feature", "properties": { "Country": "Norway", "Function": "1-3-----", "LOCODE": "NOSUN", "Name": "Sunndalsøra", "NameWoDiac": "Sunndalsora", "Status": "AF", "outflows": 107250.0 }, "geometry": { "type": "Point", "coordinates": [ 8.55, 62.666666666666664 ] } },
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{ "type": "Feature", "properties": { "Country": "Norway", "Function": "1-3-----", "LOCODE": "NOSVE", "Name": "Svelgen", "NameWoDiac": "Svelgen", "Status": "AA", "outflows": 34164.0 }, "geometry": { "type": "Point", "coordinates": [ 5.283333333333333, 61.766666666666666 ] } },
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{ "type": "Feature", "properties": { "Country": "Australia", "Function": "1--4----", "LOCODE": "AUDPO", "Name": "Devonport", "NameWoDiac": "Devonport", "Status": "AC", "outflows": 11960.0 }, "geometry": { "type": "Point", "coordinates": [ 146.35152, -41.17695 ] } },
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{ "type": "Feature", "properties": { "Country": "Australia", "Function": "1--4----", "LOCODE": "AUFRE", "Name": "Fremantle", "NameWoDiac": "Fremantle", "Status": "AC", "outflows": 4485214.6003799979 }, "geometry": { "type": "Point", "coordinates": [ 115.74557, -32.05632 ] } },
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{ "type": "Feature", "properties": { "Country": "Australia", "Function": "1--4----", "LOCODE": "AUGEX", "Name": "Geelong", "NameWoDiac": "Geelong", "Status": "AC", "outflows": 3084.0 }, "geometry": { "type": "Point", "coordinates": [ 144.36069, -38.14711 ] } },
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{ "type": "Feature", "properties": { "Country": "Australia", "Function": "1--4----", "LOCODE": "AUNTL", "Name": "Newcastle", "NameWoDiac": "Newcastle", "Status": "AI", "outflows": 69717.0 }, "geometry": { "type": "Point", "coordinates": [ 151.7801, -32.92953 ] } },
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{ "type": "Feature", "properties": { "Country": "Australia", "Function": "123-----", "LOCODE": "AUPBT", "Name": "Port Botany", "NameWoDiac": "Port Botany", "Status": "AC", "outflows": 47151.0 }, "geometry": { "type": "Point", "coordinates": [ 151.22277, -33.97447 ] } },
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{ "type": "Feature", "properties": { "Country": "Australia", "Function": "1--4----", "LOCODE": "AUPKL", "Name": "Port Kembla", "NameWoDiac": "Port Kembla", "Status": "AC", "outflows": 33267.0 }, "geometry": { "type": "Point", "coordinates": [ 150.9012, -34.4818 ] } },
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{ "type": "Feature", "properties": { "Country": "Australia", "Function": "1--4----", "LOCODE": "AUTSV", "Name": "Townsville", "NameWoDiac": "Townsville", "Status": "AI", "outflows": 227206.58331800002 }, "geometry": { "type": "Point", "coordinates": [ 146.80569, -19.26639 ] } },
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{ "type": "Feature", "properties": { "Country": "Australia", "Function": "1--4----", "LOCODE": "AUWEI", "Name": "Weipa", "NameWoDiac": "Weipa", "Status": "AC", "outflows": 806.0 }, "geometry": { "type": "Point", "coordinates": [ 141.87883, -12.62346 ] } },
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{ "type": "Feature", "properties": { "Country": "Aruba", "Function": "1---5---", "LOCODE": "AWORJ", "Name": "Oranjestad", "NameWoDiac": "Oranjestad", "Status": "AI", "outflows": 721990.3 }, "geometry": { "type": "Point", "coordinates": [ -70.02703, 12.52398 ] } },
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{ "type": "Feature", "properties": { "Country": "Barbados", "Function": "1--45---", "LOCODE": "BBBGI", "Name": "Bridgetown", "NameWoDiac": "Bridgetown", "Status": "AI", "outflows": 687251.06668999989 }, "geometry": { "type": "Point", "coordinates": [ -59.62021, 13.10732 ] } },
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{ "type": "Feature", "properties": { "Country": "Bangladesh", "Function": "1-------", "LOCODE": "BDMGL", "Name": "Mongla", "NameWoDiac": "Mongla", "Status": "RQ", "outflows": 65143.0 }, "geometry": { "type": "Point", "coordinates": [ 89.61095, 22.47223 ] } },
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{ "type": "Feature", "properties": { "Country": "Bulgaria", "Function": "1--4----", "LOCODE": "BGVAR", "Name": "Varna", "NameWoDiac": "Varna", "Status": "AI", "outflows": 147810.0 }, "geometry": { "type": "Point", "coordinates": [ 27.91667, 43.21667 ] } },
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{ "type": "Feature", "properties": { "Country": "Benin", "Function": "1--45---", "LOCODE": "BJCOO", "Name": "Cotonou", "NameWoDiac": "Cotonou", "Status": "AI", "outflows": 4812454.6643299991 }, "geometry": { "type": "Point", "coordinates": [ 2.41833, 6.36536 ] } },
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{ "type": "Feature", "properties": { "Country": "Bermuda", "Function": "1--45---", "LOCODE": "BMBDA", "Name": "Hamilton", "NameWoDiac": "Hamilton", "Status": "AI", "outflows": 13100.0 }, "geometry": { "type": "Point", "coordinates": [ -64.78303, 32.2949 ] } },
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{ "type": "Feature", "properties": { "Country": "Brazil", "Function": "1--4----", "LOCODE": "BRFOR", "Name": "Fortaleza", "NameWoDiac": "Fortaleza", "Status": "AI", "outflows": 278482.75 }, "geometry": { "type": "Point", "coordinates": [ -38.54306, -3.71722 ] } },
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{ "type": "Feature", "properties": { "Country": "Brazil", "Function": "1--4----", "LOCODE": "BRIOS", "Name": "Ilheus", "NameWoDiac": "Ilheus", "Status": "AI", "outflows": 36877.75 }, "geometry": { "type": "Point", "coordinates": [ -39.03949, -14.79364 ] } },
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{ "type": "Feature", "properties": { "Country": "Brazil", "Function": "1-------", "LOCODE": "BRIBB", "Name": "Imbituba", "NameWoDiac": "Imbituba", "Status": "AI", "outflows": 378681.33330999996 }, "geometry": { "type": "Point", "coordinates": [ -48.67028, -28.24 ] } },
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{ "type": "Feature", "properties": { "Country": "Brazil", "Function": "1--4----", "LOCODE": "BRITJ", "Name": "Itajai", "NameWoDiac": "Itajai", "Status": "AI", "outflows": 4871215.6998899989 }, "geometry": { "type": "Point", "coordinates": [ -48.66194, -26.90778 ] } },
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{ "type": "Feature", "properties": { "Country": "Brazil", "Function": "1--4----", "LOCODE": "BRMAO", "Name": "Manaus", "NameWoDiac": "Manaus", "Status": "AI", "outflows": 1385527.97796 }, "geometry": { "type": "Point", "coordinates": [ -60.025, -3.10194 ] } },
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{ "type": "Feature", "properties": { "Country": "Brazil", "Function": "1--4----", "LOCODE": "BRNAT", "Name": "Natal", "NameWoDiac": "Natal", "Status": "AI", "outflows": 241605.0 }, "geometry": { "type": "Point", "coordinates": [ -35.20944, -5.795 ] } },
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{ "type": "Feature", "properties": { "Country": "Brazil", "Function": "1--4----", "LOCODE": "BRRIG", "Name": "Rio Grande", "NameWoDiac": "Rio Grande", "Status": "AI", "outflows": 10184119.863509998 }, "geometry": { "type": "Point", "coordinates": [ -43.18223, -22.90642 ] } },
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{ "type": "Feature", "properties": { "Country": "Brazil", "Function": "1--4----", "LOCODE": "BRSSA", "Name": "Salvador", "NameWoDiac": "Salvador", "Status": "AI", "outflows": 8800539.5732199997 }, "geometry": { "type": "Point", "coordinates": [ -38.51083, -12.97111 ] } },
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{ "type": "Feature", "properties": { "Country": "Brazil", "Function": "1-------", "LOCODE": "BRSUA", "Name": "Suape", "NameWoDiac": "Suape", "Status": "RQ", "outflows": 5878585.3904299997 }, "geometry": { "type": "Point", "coordinates": [ -38.62083, -12.74083 ] } },
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{ "type": "Feature", "properties": { "Country": "Belize", "Function": "1--45---", "LOCODE": "BZBZE", "Name": "Belize City", "NameWoDiac": "Belize City", "Status": "AI", "outflows": 469495.0 }, "geometry": { "type": "Point", "coordinates": [ -88.19756, 17.49952 ] } },
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{ "type": "Feature", "properties": { "Country": "Canada", "Function": "1--4----", "LOCODE": "CAHAL", "Name": "Halifax", "NameWoDiac": "Halifax", "Status": "AS", "outflows": 4454972.4670409998 }, "geometry": { "type": "Point", "coordinates": [ -63.57291, 44.6464 ] } },
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{ "type": "Feature", "properties": { "Country": "Canada", "Function": "1--45---", "LOCODE": "CAMTR", "Name": "Montreal", "NameWoDiac": "Montreal", "Status": "AS", "outflows": 2304234.075 }, "geometry": { "type": "Point", "coordinates": [ -73.58781, 45.50884 ] } },
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{ "type": "Feature", "properties": { "Country": "Canada", "Function": "1-------", "LOCODE": "CANWE", "Name": "New Westminster", "NameWoDiac": "New Westminster", "Status": "AS", "outflows": 27774.0 }, "geometry": { "type": "Point", "coordinates": [ -122.91092, 49.20678 ] } },
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{ "type": "Feature", "properties": { "Country": "Canada", "Function": "1--4----", "LOCODE": "CAPRR", "Name": "Prince Rupert", "NameWoDiac": "Prince Rupert", "Status": "AS", "outflows": 2510218.7498600003 }, "geometry": { "type": "Point", "coordinates": [ -130.32098, 54.31507 ] } },
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{ "type": "Feature", "properties": { "Country": "Canada", "Function": "1--4----", "LOCODE": "CASQA", "Name": "Squamish", "NameWoDiac": "Squamish", "Status": "AS", "outflows": 9606.0 }, "geometry": { "type": "Point", "coordinates": [ -122.95396, 50.11817 ] } },
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{ "type": "Feature", "properties": { "Country": "Canada", "Function": "1--45---", "LOCODE": "CATOR", "Name": "Toronto", "NameWoDiac": "Toronto", "Status": "AS", "outflows": 5720.0 }, "geometry": { "type": "Point", "coordinates": [ -79.4163, 43.70011 ] } },
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{ "type": "Feature", "properties": { "Country": "Canada", "Function": "1--45---", "LOCODE": "CAVAN", "Name": "Vancouver", "NameWoDiac": "Vancouver", "Status": "AS", "outflows": 11959843.503790002 }, "geometry": { "type": "Point", "coordinates": [ -123.11934, 49.24966 ] } },
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{ "type": "Feature", "properties": { "Country": "Cook Islands", "Function": "1--45---", "LOCODE": "CKAIT", "Name": "Aitutaki", "NameWoDiac": "Aitutaki", "Status": "AI", "outflows": 40320.0 }, "geometry": { "type": "Point", "coordinates": [ -159.79293, -18.85195 ] } },
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{ "type": "Feature", "properties": { "Country": "Cook Islands", "Function": "1--45---", "LOCODE": "CKRAR", "Name": "Rarotonga", "NameWoDiac": "Rarotonga", "Status": "AI", "outflows": 41157.0 }, "geometry": { "type": "Point", "coordinates": [ -159.77545, -21.2075 ] } },
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{ "type": "Feature", "properties": { "Country": "Cameroon", "Function": "1--45---", "LOCODE": "CMDLA", "Name": "Douala", "NameWoDiac": "Douala", "Status": "AI", "outflows": 1089387.80006 }, "geometry": { "type": "Point", "coordinates": [ 9.70428, 4.04827 ] } },
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{ "type": "Feature", "properties": { "Country": "Cameroon", "Function": "1--4----", "LOCODE": "CMKBI", "Name": "Kribi", "NameWoDiac": "Kribi", "Status": "AI", "outflows": 1338743.54556 }, "geometry": { "type": "Point", "coordinates": [ 9.90765, 2.93725 ] } },
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{ "type": "Feature", "properties": { "Country": "Colombia", "Function": "1--45---", "LOCODE": "COBAQ", "Name": "Barranquilla", "NameWoDiac": "Barranquilla", "Status": "AI", "outflows": 1238849.9999530001 }, "geometry": { "type": "Point", "coordinates": [ -74.78132, 10.96854 ] } },
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{ "type": "Feature", "properties": { "Country": "Colombia", "Function": "1--4----", "LOCODE": "COBUN", "Name": "Buenaventura", "NameWoDiac": "Buenaventura", "Status": "AI", "outflows": 12125518.600159997 }, "geometry": { "type": "Point", "coordinates": [ -77.03116, 3.8801 ] } },
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{ "type": "Feature", "properties": { "Country": "Colombia", "Function": "1--4----", "LOCODE": "COCTG", "Name": "Cartagena", "NameWoDiac": "Cartagena", "Status": "AI", "outflows": 16624367.157963 }, "geometry": { "type": "Point", "coordinates": [ -75.51444, 10.39972 ] } },
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{ "type": "Feature", "properties": { "Country": "Colombia", "Function": "1--4----", "LOCODE": "COSMR", "Name": "Santa Marta", "NameWoDiac": "Santa Marta", "Status": "AI", "outflows": 1906046.5665720007 }, "geometry": { "type": "Point", "coordinates": [ -74.19904, 11.24079 ] } },
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{ "type": "Feature", "properties": { "Country": "Cuba", "Function": "---4----", "LOCODE": "CUMOA", "Name": "Moa", "NameWoDiac": "Moa", "Status": "AI", "outflows": 65431.8 }, "geometry": { "type": "Point", "coordinates": [ -74.95075, 20.65776 ] } },
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{ "type": "Feature", "properties": { "Country": "Cuba", "Function": "1--4----", "LOCODE": "CUSCU", "Name": "Santiago de Cuba", "NameWoDiac": "Santiago de Cuba", "Status": "AI", "outflows": 63230.0 }, "geometry": { "type": "Point", "coordinates": [ -75.82667, 20.02083 ] } },
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{ "type": "Feature", "properties": { "Country": "Cabo Verde", "Function": "0-------", "LOCODE": "CVPAL", "Name": "Palmeira", "NameWoDiac": "Palmeira", "Status": "RQ", "outflows": 13234.0 }, "geometry": { "type": "Point", "coordinates": [ -22.98348, 16.75754 ] } },
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{ "type": "Feature", "properties": { "Country": "Cabo Verde", "Function": "1--4----", "LOCODE": "CVRAI", "Name": "Praia", "NameWoDiac": "Praia", "Status": "AI", "outflows": 114309.0 }, "geometry": { "type": "Point", "coordinates": [ -23.51254, 14.93152 ] } },
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{ "type": "Feature", "properties": { "Country": "Cabo Verde", "Function": "0-------", "LOCODE": "CVSAR", "Name": "Sal Rei", "NameWoDiac": "Sal Rei", "Status": "RQ", "outflows": 25421.5 }, "geometry": { "type": "Point", "coordinates": [ -22.91722, 16.17611 ] } },
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{ "type": "Feature", "properties": { "Country": "Germany", "Function": "12345---", "LOCODE": "DEBRE", "Name": "Bremen", "NameWoDiac": "Bremen", "Status": "AF", "outflows": 197153.69999199998 }, "geometry": { "type": "Point", "coordinates": [ 8.80717, 53.07582 ] } },
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{ "type": "Feature", "properties": { "Country": "Germany", "Function": "1234----", "LOCODE": "DEBRV", "Name": "Bremerhaven", "NameWoDiac": "Bremerhaven", "Status": "AF", "outflows": 21710907.495360006 }, "geometry": { "type": "Point", "coordinates": [ 8.59298, 53.53615 ] } },
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{ "type": "Feature", "properties": { "Country": "Germany", "Function": "12345---", "LOCODE": "DEHAM", "Name": "Hamburg", "NameWoDiac": "Hamburg", "Status": "AF", "outflows": 42669313.486039981 }, "geometry": { "type": "Point", "coordinates": [ 9.99302, 53.55073 ] } },
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{ "type": "Feature", "properties": { "Country": "Germany", "Function": "12345---", "LOCODE": "DELBC", "Name": "Lübeck", "NameWoDiac": "Lubeck", "Status": "AF", "outflows": 295233.5 }, "geometry": { "type": "Point", "coordinates": [ 10.68729, 53.86893 ] } },
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{ "type": "Feature", "properties": { "Country": "Germany", "Function": "123-----", "LOCODE": "DETRV", "Name": "Travemünde", "NameWoDiac": "Travemunde", "Status": "AF", "outflows": 73746.0 }, "geometry": { "type": "Point", "coordinates": [ 10.8709, 53.96304 ] } },
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{ "type": "Feature", "properties": { "Country": "Djibouti", "Function": "1--45---", "LOCODE": "DJJIB", "Name": "Djibouti", "NameWoDiac": "Djibouti", "Status": "AI", "outflows": 4852561.0352500007 }, "geometry": { "type": "Point", "coordinates": [ 43.14503, 11.58901 ] } },
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{ "type": "Feature", "properties": { "Country": "Denmark", "Function": "12345---", "LOCODE": "DKAAL", "Name": "Aalborg", "NameWoDiac": "Aalborg", "Status": "AF", "outflows": 74932.0 }, "geometry": { "type": "Point", "coordinates": [ 9.9187, 57.048 ] } },
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{ "type": "Feature", "properties": { "Country": "Denmark", "Function": "1234----", "LOCODE": "DKEBJ", "Name": "Esbjerg", "NameWoDiac": "Esbjerg", "Status": "AF", "outflows": 28620.0 }, "geometry": { "type": "Point", "coordinates": [ 8.45187, 55.47028 ] } },
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{ "type": "Feature", "properties": { "Country": "Denmark", "Function": "12--5---", "LOCODE": "DKFRC", "Name": "Fredericia", "NameWoDiac": "Fredericia", "Status": "AF", "outflows": 245869.0 }, "geometry": { "type": "Point", "coordinates": [ 9.75257, 55.56568 ] } },
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{ "type": "Feature", "properties": { "Country": "Denmark", "Function": "123-----", "LOCODE": "DKGRE", "Name": "Grenaa", "NameWoDiac": "Grenaa", "Status": "AF", "outflows": 16263.0 }, "geometry": { "type": "Point", "coordinates": [ 10.87825, 56.41578 ] } },
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{ "type": "Feature", "properties": { "Country": "Denmark", "Function": "123-----", "LOCODE": "DKHUN", "Name": "Hundested", "NameWoDiac": "Hundested", "Status": "AF", "outflows": 16263.0 }, "geometry": { "type": "Point", "coordinates": [ 11.85044, 55.96397 ] } },
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{ "type": "Feature", "properties": { "Country": "Denmark", "Function": "12------", "LOCODE": "DKSKA", "Name": "Skagen", "NameWoDiac": "Skagen", "Status": "AF", "outflows": 56420.0 }, "geometry": { "type": "Point", "coordinates": [ 10.58394, 57.72093 ] } },
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{ "type": "Feature", "properties": { "Country": "Dominica", "Function": "1-------", "LOCODE": "DMRSU", "Name": "Roseau", "NameWoDiac": "Roseau", "Status": "AI", "outflows": 370965.4 }, "geometry": { "type": "Point", "coordinates": [ -61.38808, 15.30174 ] } },
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{ "type": "Feature", "properties": { "Country": "Dominican Republic", "Function": "1-------", "LOCODE": "DOBCC", "Name": "Boca Chica", "NameWoDiac": "Boca Chica", "Status": "AI", "outflows": 333493.3333 }, "geometry": { "type": "Point", "coordinates": [ -69.6, 18.45 ] } },
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{ "type": "Feature", "properties": { "Country": "Dominican Republic", "Function": "1-------", "LOCODE": "DOPOP", "Name": "Puerto Plata", "NameWoDiac": "Puerto Plata", "Status": "AI", "outflows": 712651.3333000001 }, "geometry": { "type": "Point", "coordinates": [ -70.6884, 19.79344 ] } },
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{ "type": "Feature", "properties": { "Country": "Algeria", "Function": "1-------", "LOCODE": "DZMOS", "Name": "Mostaganem", "NameWoDiac": "Mostaganem", "Status": "QQ", "outflows": 20553.75 }, "geometry": { "type": "Point", "coordinates": [ 0.08918, 35.93115 ] } },
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{ "type": "Feature", "properties": { "Country": "Algeria", "Function": "1--4----", "LOCODE": "DZORN", "Name": "Oran", "NameWoDiac": "Oran", "Status": "AI", "outflows": 210402.15 }, "geometry": { "type": "Point", "coordinates": [ -0.63588, 35.69906 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1--4----", "LOCODE": "JPAXT", "Name": "Akita", "NameWoDiac": "Akita", "Status": "AF", "outflows": 278377.66667000001 }, "geometry": { "type": "Point", "coordinates": [ 140.11667, 39.71667 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPCHB", "Name": "Chiba", "NameWoDiac": "Chiba", "Status": "AF", "outflows": 607568.0 }, "geometry": { "type": "Point", "coordinates": [ 140.11667, 35.6 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1--4----", "LOCODE": "JPHIJ", "Name": "Hiroshima", "NameWoDiac": "Hiroshima", "Status": "AF", "outflows": 658970.0 }, "geometry": { "type": "Point", "coordinates": [ 132.45, 34.4 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPHSM", "Name": "Hososhima", "NameWoDiac": "Hososhima", "Status": "AF", "outflows": 354289.0 }, "geometry": { "type": "Point", "coordinates": [ 131.66667, 32.43333 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPIMI", "Name": "Imari", "NameWoDiac": "Imari", "Status": "AF", "outflows": 232752.0 }, "geometry": { "type": "Point", "coordinates": [ 129.87877, 33.27362 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPIWK", "Name": "Iwakuni", "NameWoDiac": "Iwakuni", "Status": "AF", "outflows": 248404.0 }, "geometry": { "type": "Point", "coordinates": [ 132.22, 34.16297 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPKNZ", "Name": "Kanazawa", "NameWoDiac": "Kanazawa", "Status": "AF", "outflows": 500785.99996999995 }, "geometry": { "type": "Point", "coordinates": [ 136.61667, 36.6 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPKSM", "Name": "Kashima, Ibaraki", "NameWoDiac": "Kashima, Ibaraki", "Status": "AF", "outflows": 103584.0 }, "geometry": { "type": "Point", "coordinates": [ 140.64474, 35.96536 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1--4----", "LOCODE": "JPKCZ", "Name": "Kochi", "NameWoDiac": "Kochi", "Status": "AF", "outflows": 97578.0 }, "geometry": { "type": "Point", "coordinates": [ 133.53333, 33.55 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1--4----", "LOCODE": "JPMYJ", "Name": "Matsuyama", "NameWoDiac": "Matsuyama", "Status": "AF", "outflows": 213629.0 }, "geometry": { "type": "Point", "coordinates": [ 132.76574, 33.83916 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPMII", "Name": "Miike, Fukuoka", "NameWoDiac": "Miike, Fukuoka", "Status": "AF", "outflows": 16640.0 }, "geometry": { "type": "Point", "coordinates": [ 130.47791, 33.05207 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPMIZ", "Name": "Mizushima", "NameWoDiac": "Mizushima", "Status": "AF", "outflows": 727415.0 }, "geometry": { "type": "Point", "coordinates": [ 133.73896, 34.5298 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPMUR", "Name": "Muroran", "NameWoDiac": "Muroran", "Status": "AF", "outflows": 115517.99996999998 }, "geometry": { "type": "Point", "coordinates": [ 140.98806, 42.31722 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1--4----", "LOCODE": "JPNGS", "Name": "Nagasaki", "NameWoDiac": "Nagasaki", "Status": "AF", "outflows": 44460.0 }, "geometry": { "type": "Point", "coordinates": [ 129.88333, 32.75 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1--45---", "LOCODE": "JPNGO", "Name": "Nagoya, Aichi", "NameWoDiac": "Nagoya, Aichi", "Status": "AF", "outflows": 14485316.083789002 }, "geometry": { "type": "Point", "coordinates": [ 136.90641, 35.18147 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1--45---", "LOCODE": "JPNAH", "Name": "Naha, Okinawa", "NameWoDiac": "Naha, Okinawa", "Status": "AF", "outflows": 770354.0 }, "geometry": { "type": "Point", "coordinates": [ 127.68333, 26.21667 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPNAO", "Name": "Naoetsu", "NameWoDiac": "Naoetsu", "Status": "AF", "outflows": 166443.33335 }, "geometry": { "type": "Point", "coordinates": [ 138.25, 37.18333 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPKIJ", "Name": "Niigata", "NameWoDiac": "Niigata", "Status": "AF", "outflows": 632488.99997 }, "geometry": { "type": "Point", "coordinates": [ 139.00589, 37.88637 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1--4----", "LOCODE": "JPOIT", "Name": "Oita", "NameWoDiac": "Oita", "Status": "AF", "outflows": 336869.0 }, "geometry": { "type": "Point", "coordinates": [ 131.6, 33.23333 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPOMZ", "Name": "Omaezaki", "NameWoDiac": "Omaezaki", "Status": "AF", "outflows": 642421.0 }, "geometry": { "type": "Point", "coordinates": [ 138.21934, 34.59882 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPONA", "Name": "Onahama", "NameWoDiac": "Onahama", "Status": "AF", "outflows": 204940.6667 }, "geometry": { "type": "Point", "coordinates": [ 140.9, 36.95 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPOTK", "Name": "Otake", "NameWoDiac": "Otake", "Status": "AF", "outflows": 36348.0 }, "geometry": { "type": "Point", "coordinates": [ 132.22063, 34.20754 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1--4----", "LOCODE": "JPOTR", "Name": "Otaru", "NameWoDiac": "Otaru", "Status": "AF", "outflows": 78000.0 }, "geometry": { "type": "Point", "coordinates": [ 141.00222, 43.18944 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPSMN", "Name": "Sakaiminato", "NameWoDiac": "Sakaiminato", "Status": "AF", "outflows": 329679.99997 }, "geometry": { "type": "Point", "coordinates": [ 133.23094, 35.53774 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPSKT", "Name": "Sakata", "NameWoDiac": "Sakata", "Status": "AF", "outflows": 421338.66667000001 }, "geometry": { "type": "Point", "coordinates": [ 139.855, 38.91667 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPSBS", "Name": "Shibushi", "NameWoDiac": "Shibushi", "Status": "AF", "outflows": 490971.0 }, "geometry": { "type": "Point", "coordinates": [ 131.10114, 31.476 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1--4----", "LOCODE": "JPTAK", "Name": "Takamatsu", "NameWoDiac": "Takamatsu", "Status": "AF", "outflows": 188292.0 }, "geometry": { "type": "Point", "coordinates": [ 134.05, 34.33333 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1--4----", "LOCODE": "JPTKS", "Name": "Tokushima", "NameWoDiac": "Tokushima", "Status": "AF", "outflows": 148044.0 }, "geometry": { "type": "Point", "coordinates": [ 134.56667, 34.06667 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPTKY", "Name": "Tokuyama", "NameWoDiac": "Tokuyama", "Status": "AF", "outflows": 456888.25 }, "geometry": { "type": "Point", "coordinates": [ 131.81667, 34.05 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1--4----", "LOCODE": "JPTMK", "Name": "Tomakomai", "NameWoDiac": "Tomakomai", "Status": "AF", "outflows": 929244.33331999998 }, "geometry": { "type": "Point", "coordinates": [ 141.60333, 42.63694 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPTHS", "Name": "Toyohashi", "NameWoDiac": "Toyohashi", "Status": "AF", "outflows": 181584.0 }, "geometry": { "type": "Point", "coordinates": [ 137.38333, 34.76667 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPTRG", "Name": "Tsuruga", "NameWoDiac": "Tsuruga", "Status": "AF", "outflows": 121550.0 }, "geometry": { "type": "Point", "coordinates": [ 136.0558, 35.64547 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1--4----", "LOCODE": "JPUBJ", "Name": "Ube", "NameWoDiac": "Ube", "Status": "AF", "outflows": 22490.0 }, "geometry": { "type": "Point", "coordinates": [ 131.25111, 33.94306 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPWAK", "Name": "Wakayama", "NameWoDiac": "Wakayama", "Status": "AF", "outflows": 63765.0 }, "geometry": { "type": "Point", "coordinates": [ 135.16667, 34.23333 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPYAT", "Name": "Yatsushiro", "NameWoDiac": "Yatsushiro", "Status": "AF", "outflows": 61100.0 }, "geometry": { "type": "Point", "coordinates": [ 130.59952, 32.50439 ] } },
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{ "type": "Feature", "properties": { "Country": "Japan", "Function": "1-------", "LOCODE": "JPYKK", "Name": "Yokkaichi", "NameWoDiac": "Yokkaichi", "Status": "AF", "outflows": 3523652.1667400002 }, "geometry": { "type": "Point", "coordinates": [ 136.61667, 34.96667 ] } },
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{ "type": "Feature", "properties": { "Country": "Kiribati", "Function": "1--4----", "LOCODE": "KITRW", "Name": "Tarawa", "NameWoDiac": "Tarawa", "Status": "AI", "outflows": 136326.0 }, "geometry": { "type": "Point", "coordinates": [ 172.97696, 1.3278 ] } },
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{ "type": "Feature", "properties": { "Country": "Comoros", "Function": "1--45---", "LOCODE": "KMYVA", "Name": "Moroni", "NameWoDiac": "Moroni", "Status": "AI", "outflows": 131275.33335 }, "geometry": { "type": "Point", "coordinates": [ 43.25506, -11.70216 ] } },
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{ "type": "Feature", "properties": { "Country": "Lebanon", "Function": "1--4----", "LOCODE": "LBKYE", "Name": "Tripoli", "NameWoDiac": "Tripoli", "Status": "AI", "outflows": 2038156.25 }, "geometry": { "type": "Point", "coordinates": [ 35.84415, 34.43352 ] } },
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{ "type": "Feature", "properties": { "Country": "Latvia", "Function": "1--45---", "LOCODE": "LVRIX", "Name": "Riga", "NameWoDiac": "Riga", "Status": "AI", "outflows": 944970.0 }, "geometry": { "type": "Point", "coordinates": [ 24.10589, 56.946 ] } },
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{ "type": "Feature", "properties": { "Country": "Libya", "Function": "1--45---", "LOCODE": "LYBEN", "Name": "Bingazi (Benghazi)", "NameWoDiac": "Bingazi (Benghazi)", "Status": "AI", "outflows": 296981.0 }, "geometry": { "type": "Point", "coordinates": [ 20.06859, 32.11486 ] } },
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{ "type": "Feature", "properties": { "Country": "Libya", "Function": "1--4----", "LOCODE": "LYMRA", "Name": "Misurata", "NameWoDiac": "Misurata", "Status": "AI", "outflows": 757750.00001000008 }, "geometry": { "type": "Point", "coordinates": [ 15.09254, 32.37535 ] } },
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{ "type": "Feature", "properties": { "Country": "Libya", "Function": "1--4----", "LOCODE": "LYTIP", "Name": "Tripoli", "NameWoDiac": "Tripoli", "Status": "AI", "outflows": 281045.0 }, "geometry": { "type": "Point", "coordinates": [ 13.18733, 32.88743 ] } },
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{ "type": "Feature", "properties": { "Country": "Morocco", "Function": "1--4----", "LOCODE": "MAAGA", "Name": "Agadir", "NameWoDiac": "Agadir", "Status": "AI", "outflows": 593660.57139000006 }, "geometry": { "type": "Point", "coordinates": [ -9.59815, 30.42018 ] } },
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{ "type": "Feature", "properties": { "Country": "Morocco", "Function": "1-------", "LOCODE": "MANDR", "Name": "Nador", "NameWoDiac": "Nador", "Status": "AI", "outflows": 45500.0 }, "geometry": { "type": "Point", "coordinates": [ -2.93352, 35.16813 ] } },
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{ "type": "Feature", "properties": { "Country": "Morocco", "Function": "123-----", "LOCODE": "MAPTM", "Name": "Tanger Med", "NameWoDiac": "Tanger Med", "Status": "AI", "outflows": 29213268.307420008 }, "geometry": { "type": "Point", "coordinates": [ -5.56323, 35.82674 ] } },
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{ "type": "Feature", "properties": { "Country": "Madagascar", "Function": "1--4----", "LOCODE": "MGDIE", "Name": "Antsiranana", "NameWoDiac": "Antsiranana", "Status": "AI", "outflows": 113468.0 }, "geometry": { "type": "Point", "coordinates": [ 49.29188, -12.31732 ] } },
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{ "type": "Feature", "properties": { "Country": "Madagascar", "Function": "1--4----", "LOCODE": "MGMJN", "Name": "Majunga (Mahajanga)", "NameWoDiac": "Majunga (Mahajanga)", "Status": "AI", "outflows": 125324.0 }, "geometry": { "type": "Point", "coordinates": [ 46.31667, -15.71667 ] } },
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{ "type": "Feature", "properties": { "Country": "Philippines", "Function": "1--4----", "LOCODE": "PHCBO", "Name": "Cotabato, Mindanao", "NameWoDiac": "Cotabato, Mindanao", "Status": "AI", "outflows": 29328.0 }, "geometry": { "type": "Point", "coordinates": [ 124.24639, 7.22361 ] } },
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{ "type": "Feature", "properties": { "Country": "Philippines", "Function": "1--4----", "LOCODE": "PHOZC", "Name": "Ozamis, Mindanao", "NameWoDiac": "Ozamis, Mindanao", "Status": "AI", "outflows": 10976.0 }, "geometry": { "type": "Point", "coordinates": [ 123.8405, 8.1481 ] } },
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{ "type": "Feature", "properties": { "Country": "Russian Federation", "Function": "1-------", "LOCODE": "RUDUD", "Name": "Dudinka", "NameWoDiac": "Dudinka", "Status": "QQ", "outflows": 16796.0 }, "geometry": { "type": "Point", "coordinates": [ 86.17778, 69.40583 ] } },
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{ "type": "Feature", "properties": { "Country": "Russian Federation", "Function": "1--4----", "LOCODE": "RUKGD", "Name": "Kaliningrad", "NameWoDiac": "Kaliningrad", "Status": "AI", "outflows": 133061.5 }, "geometry": { "type": "Point", "coordinates": [ 20.51095, 54.70649 ] } },
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{ "type": "Feature", "properties": { "Country": "Russian Federation", "Function": "1-------", "LOCODE": "RUKOR", "Name": "Korsakov", "NameWoDiac": "Korsakov", "Status": "QQ", "outflows": 19067.0 }, "geometry": { "type": "Point", "coordinates": [ 142.77722, 46.6342 ] } },
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{ "type": "Feature", "properties": { "Country": "Russian Federation", "Function": "---4----", "LOCODE": "RUGDX", "Name": "Magadan", "NameWoDiac": "Magadan", "Status": "AI", "outflows": 27664.0 }, "geometry": { "type": "Point", "coordinates": [ 150.80347, 59.5638 ] } },
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|
||||
{ "type": "Feature", "properties": { "Country": "Russian Federation", "Function": "1--4----", "LOCODE": "RUVVO", "Name": "Vladivostok", "NameWoDiac": "Vladivostok", "Status": "AI", "outflows": 1273681.4999099998 }, "geometry": { "type": "Point", "coordinates": [ 131.87353, 43.10562 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Saudi Arabia", "Function": "1-------", "LOCODE": "SAJUB", "Name": "Jubail", "NameWoDiac": "Jubail", "Status": "QQ", "outflows": 6234394.5950499978 }, "geometry": { "type": "Point", "coordinates": [ 49.62251, 27.0174 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Seychelles", "Function": "1-------", "LOCODE": "SCPOV", "Name": "Port Victoria", "NameWoDiac": "Port Victoria", "Status": "QQ", "outflows": 611771.76191000012 }, "geometry": { "type": "Point", "coordinates": [ 55.45501, -4.62001 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Sudan", "Function": "1--45---", "LOCODE": "SDPZU", "Name": "Port Sudan", "NameWoDiac": "Port Sudan", "Status": "AI", "outflows": 308535.0 }, "geometry": { "type": "Point", "coordinates": [ 37.21644, 19.61745 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Sweden", "Function": "12-4----", "LOCODE": "SEHEL", "Name": "Helsingborg", "NameWoDiac": "Helsingborg", "Status": "AI", "outflows": 634088.0 }, "geometry": { "type": "Point", "coordinates": [ 12.69437, 56.04673 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Sweden", "Function": "123-----", "LOCODE": "SEVAG", "Name": "Varberg", "NameWoDiac": "Varberg", "Status": "AA", "outflows": 82628.0 }, "geometry": { "type": "Point", "coordinates": [ 12.25078, 57.10557 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Singapore", "Function": "1--45---", "LOCODE": "SGSIN", "Name": "Singapore", "NameWoDiac": "Singapore", "Status": "AI", "outflows": 126673817.40886995 }, "geometry": { "type": "Point", "coordinates": [ 103.85007, 1.28967 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Slovenia", "Function": "1-------", "LOCODE": "SIKOP", "Name": "Koper", "NameWoDiac": "Koper", "Status": "RL", "outflows": 4814941.1666899994 }, "geometry": { "type": "Point", "coordinates": [ 13.72944, 45.54694 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Sierra Leone", "Function": "1--45---", "LOCODE": "SLFNA", "Name": "Freetown", "NameWoDiac": "Freetown", "Status": "AI", "outflows": 292305.0 }, "geometry": { "type": "Point", "coordinates": [ -13.2356, 8.48714 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Senegal", "Function": "1--45---", "LOCODE": "SNDKR", "Name": "Dakar", "NameWoDiac": "Dakar", "Status": "AI", "outflows": 2417263.262 }, "geometry": { "type": "Point", "coordinates": [ -17.44406, 14.6937 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Somalia", "Function": "1--4----", "LOCODE": "SOBBO", "Name": "Berbera", "NameWoDiac": "Berbera", "Status": "AI", "outflows": 215094.5 }, "geometry": { "type": "Point", "coordinates": [ 45.01432, 10.43959 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Somalia", "Function": "1--4----", "LOCODE": "SOKMU", "Name": "Kismayu", "NameWoDiac": "Kismayu", "Status": "AI", "outflows": 188773.0 }, "geometry": { "type": "Point", "coordinates": [ 42.54536, -0.35817 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Somalia", "Function": "1--45---", "LOCODE": "SOMGQ", "Name": "Mogadishu", "NameWoDiac": "Mogadishu", "Status": "AI", "outflows": 437501.99997999996 }, "geometry": { "type": "Point", "coordinates": [ 45.34375, 2.03711 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Suriname", "Function": "1--45---", "LOCODE": "SRPBM", "Name": "Paramaribo", "NameWoDiac": "Paramaribo", "Status": "AI", "outflows": 538931.33332199999 }, "geometry": { "type": "Point", "coordinates": [ -55.16682, 5.86638 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Suriname", "Function": "1--45---", "LOCODE": "SRPBM", "Name": "Paramaribo", "NameWoDiac": "Paramaribo", "Status": "AI", "outflows": 538931.33332199999 }, "geometry": { "type": "Point", "coordinates": [ -55.16682, 5.86638 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "El Salvador", "Function": "1-3-----", "LOCODE": "SVAQJ", "Name": "Acajutla", "NameWoDiac": "Acajutla", "Status": "AI", "outflows": 495947.4 }, "geometry": { "type": "Point", "coordinates": [ -89.8275, 13.59278 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "El Salvador", "Function": "1--45---", "LOCODE": "SVSAL", "Name": "San Salvador", "NameWoDiac": "San Salvador", "Status": "AI", "outflows": 388752.0 }, "geometry": { "type": "Point", "coordinates": [ -89.18718, 13.68935 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Togo", "Function": "1--45---", "LOCODE": "TGLFW", "Name": "Lome", "NameWoDiac": "Lome", "Status": "AI", "outflows": 6445382.4134400021 }, "geometry": { "type": "Point", "coordinates": [ 1.22154, 6.12874 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Thailand", "Function": "1-------", "LOCODE": "THSRI", "Name": "Sriracha", "NameWoDiac": "Sriracha", "Status": "QQ", "outflows": 58522.5 }, "geometry": { "type": "Point", "coordinates": [ 100.93111, 13.17372 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Tunisia", "Function": "1234----", "LOCODE": "TNBIZ", "Name": "Bizerte", "NameWoDiac": "Bizerte", "Status": "QQ", "outflows": 106117.5 }, "geometry": { "type": "Point", "coordinates": [ 9.87391, 37.27442 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Tunisia", "Function": "1234----", "LOCODE": "TNSFA", "Name": "Sfax", "NameWoDiac": "Sfax", "Status": "AI", "outflows": 72212.33334 }, "geometry": { "type": "Point", "coordinates": [ 10.76028, 34.74056 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Tunisia", "Function": "1234----", "LOCODE": "TNSUS", "Name": "Sousse", "NameWoDiac": "Sousse", "Status": "QQ", "outflows": 43545.0 }, "geometry": { "type": "Point", "coordinates": [ 10.63699, 35.82539 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Tunisia", "Function": "12345---", "LOCODE": "TNTUN", "Name": "Tunis", "NameWoDiac": "Tunis", "Status": "AI", "outflows": 59748.0 }, "geometry": { "type": "Point", "coordinates": [ 10.16579, 36.81897 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Turkey", "Function": "1-------", "LOCODE": "TRALI", "Name": "Aliaga", "NameWoDiac": "Aliaga", "Status": "RL", "outflows": 8740753.932889998 }, "geometry": { "type": "Point", "coordinates": [ 26.97203, 38.79975 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Turkey", "Function": "1-3-----", "LOCODE": "TRDRC", "Name": "Derince", "NameWoDiac": "Derince", "Status": "QQ", "outflows": 303927.0 }, "geometry": { "type": "Point", "coordinates": [ 29.81472, 40.75694 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Turkey", "Function": "1-3-----", "LOCODE": "TRHAY", "Name": "Haydarpasa", "NameWoDiac": "Haydarpasa", "Status": "QQ", "outflows": 220592.66669000004 }, "geometry": { "type": "Point", "coordinates": [ 29.02459, 40.99596 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Turkey", "Function": "1-------", "LOCODE": "TRYAR", "Name": "Yarimca", "NameWoDiac": "Yarimca", "Status": "QQ", "outflows": 895813.99998000008 }, "geometry": { "type": "Point", "coordinates": [ 31.14194, 39.08361 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--45---", "LOCODE": "USANC", "Name": "Anchorage", "NameWoDiac": "Anchorage", "Status": "AI", "outflows": 61671.99999 }, "geometry": { "type": "Point", "coordinates": [ -149.90028, 61.21806 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--4----", "LOCODE": "USBPT", "Name": "Beaumont", "NameWoDiac": "Beaumont", "Status": "AI", "outflows": 34041.0 }, "geometry": { "type": "Point", "coordinates": [ -94.10185, 30.08605 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--45---", "LOCODE": "USBOS", "Name": "Boston", "NameWoDiac": "Boston", "Status": "AI", "outflows": 1565893.3335999998 }, "geometry": { "type": "Point", "coordinates": [ -71.05977, 42.35843 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "--3-----", "LOCODE": "USBCK", "Name": "Brunswick", "NameWoDiac": "Brunswick", "Status": "RL", "outflows": 48681.0 }, "geometry": { "type": "Point", "coordinates": [ -74.45182, 40.48622 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "--3-----", "LOCODE": "USCAT", "Name": "Camden", "NameWoDiac": "Camden", "Status": "RQ", "outflows": 176498.0 }, "geometry": { "type": "Point", "coordinates": [ -75.11962, 39.92595 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--4----", "LOCODE": "USCHS", "Name": "Charleston", "NameWoDiac": "Charleston", "Status": "AI", "outflows": 23192728.69687001 }, "geometry": { "type": "Point", "coordinates": [ -79.924426675273111, 32.785017342562952 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "--3-----", "LOCODE": "USCAV", "Name": "Cleveland", "NameWoDiac": "Cleveland", "Status": "RQ", "outflows": 1974.0 }, "geometry": { "type": "Point", "coordinates": [ -81.69541, 41.4995 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--4----", "LOCODE": "USCRP", "Name": "Corpus Christi", "NameWoDiac": "Corpus Christi", "Status": "AI", "outflows": 53712.0 }, "geometry": { "type": "Point", "coordinates": [ -97.39638, 27.80058 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--4----", "LOCODE": "USDUT", "Name": "Dutch Harbor", "NameWoDiac": "Dutch Harbor", "Status": "AI", "outflows": 378795.99998999998 }, "geometry": { "type": "Point", "coordinates": [ -166.5422, 53.8898 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1-34----", "LOCODE": "USPAE", "Name": "Everett", "NameWoDiac": "Everett", "Status": "AI", "outflows": 152295.00003000002 }, "geometry": { "type": "Point", "coordinates": [ -122.20208, 47.97898 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "---4----", "LOCODE": "USFEP", "Name": "Freeport", "NameWoDiac": "Freeport", "Status": "AI", "outflows": 751787.11118999997 }, "geometry": { "type": "Point", "coordinates": [ -70.10311, 43.85702 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--4----", "LOCODE": "USGLS", "Name": "Galveston", "NameWoDiac": "Galveston", "Status": "AI", "outflows": 47326.5 }, "geometry": { "type": "Point", "coordinates": [ -94.7977, 29.30135 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1-3-----", "LOCODE": "USGLC", "Name": "Gloucester City", "NameWoDiac": "Gloucester City", "Status": "RN", "outflows": 59686.5 }, "geometry": { "type": "Point", "coordinates": [ -70.66313, 42.61405 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "---4----", "LOCODE": "USIJX", "Name": "Jacksonville", "NameWoDiac": "Jacksonville", "Status": "AI", "outflows": 5087986.3044199999 }, "geometry": { "type": "Point", "coordinates": [ -81.65565, 30.33218 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "---4----", "LOCODE": "USADQ", "Name": "Kodiak", "NameWoDiac": "Kodiak", "Status": "AI", "outflows": 61671.99999 }, "geometry": { "type": "Point", "coordinates": [ -152.40533, 57.78852 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--45---", "LOCODE": "USLAX", "Name": "Los Angeles", "NameWoDiac": "Los Angeles", "Status": "AI", "outflows": 12755714.048839999 }, "geometry": { "type": "Point", "coordinates": [ -118.24368, 34.05223 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--45---", "LOCODE": "USMIA", "Name": "Miami", "NameWoDiac": "Miami", "Status": "AI", "outflows": 6651073.40288 }, "geometry": { "type": "Point", "coordinates": [ -80.19366, 25.77427 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--4----", "LOCODE": "USMOB", "Name": "Mobile", "NameWoDiac": "Mobile", "Status": "AI", "outflows": 3378854.4003 }, "geometry": { "type": "Point", "coordinates": [ -88.04305, 30.69436 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1-3-----", "LOCODE": "USMRH", "Name": "Morehead City", "NameWoDiac": "Morehead City", "Status": "RN", "outflows": 44898.75 }, "geometry": { "type": "Point", "coordinates": [ -76.72604, 34.72294 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "12345---", "LOCODE": "USMSY", "Name": "New Orleans", "NameWoDiac": "New Orleans", "Status": "AI", "outflows": 8818359.6138159968 }, "geometry": { "type": "Point", "coordinates": [ -90.07507, 29.95465 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--4----", "LOCODE": "USPFN", "Name": "Panama City", "NameWoDiac": "Panama City", "Status": "AI", "outflows": 82722.0 }, "geometry": { "type": "Point", "coordinates": [ -85.65983, 30.15946 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--4----", "LOCODE": "USPWM", "Name": "Portland", "NameWoDiac": "Portland", "Status": "AI", "outflows": 27248.000001 }, "geometry": { "type": "Point", "coordinates": [ -122.67621, 45.52345 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--4----", "LOCODE": "USPDX", "Name": "Portland", "NameWoDiac": "Portland", "Status": "AI", "outflows": 336570.0 }, "geometry": { "type": "Point", "coordinates": [ -122.67621, 45.52345 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--4----", "LOCODE": "USSAV", "Name": "Savannah", "NameWoDiac": "Savannah", "Status": "AI", "outflows": 26558703.755599998 }, "geometry": { "type": "Point", "coordinates": [ -81.09983, 32.08354 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--45---", "LOCODE": "USSEA", "Name": "Seattle", "NameWoDiac": "Seattle", "Status": "AI", "outflows": 10283805.920580002 }, "geometry": { "type": "Point", "coordinates": [ -122.33207, 47.60621 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--4----", "LOCODE": "USTIW", "Name": "Tacoma", "NameWoDiac": "Tacoma", "Status": "AI", "outflows": 4139226.6189899999 }, "geometry": { "type": "Point", "coordinates": [ -122.44429, 47.25288 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--45---", "LOCODE": "USTPA", "Name": "Tampa", "NameWoDiac": "Tampa", "Status": "AI", "outflows": 1911998.4003 }, "geometry": { "type": "Point", "coordinates": [ -82.45843, 27.94752 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1-3-----", "LOCODE": "USVAN", "Name": "Vancouver", "NameWoDiac": "Vancouver", "Status": "RN", "outflows": 65700.0 }, "geometry": { "type": "Point", "coordinates": [ -122.66149, 45.63873 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--4----", "LOCODE": "USPBI", "Name": "West Palm Beach", "NameWoDiac": "West Palm Beach", "Status": "AI", "outflows": 222144.0 }, "geometry": { "type": "Point", "coordinates": [ -80.05337, 26.71534 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "United States", "Function": "1--4----", "LOCODE": "USILG", "Name": "Wilmington", "NameWoDiac": "Wilmington", "Status": "AI", "outflows": 290589.0 }, "geometry": { "type": "Point", "coordinates": [ -75.54659, 39.74595 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Uruguay", "Function": "1--45---", "LOCODE": "UYMVD", "Name": "Montevideo", "NameWoDiac": "Montevideo", "Status": "AF", "outflows": 11543641.215 }, "geometry": { "type": "Point", "coordinates": [ -56.18816, -34.90328 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Virgin Islands, U.S.", "Function": "1-------", "LOCODE": "VICHA", "Name": "Charlotte Amalie, Saint Thomas", "NameWoDiac": "Charlotte Amalie, Saint Thomas", "Status": "AI", "outflows": 307918.0 }, "geometry": { "type": "Point", "coordinates": [ -64.9307, 18.3419 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Viet Nam", "Function": "1-------", "LOCODE": "VNHPH", "Name": "Haiphong", "NameWoDiac": "Haiphong", "Status": "AI", "outflows": 10072807.932540001 }, "geometry": { "type": "Point", "coordinates": [ 106.68345, 20.86481 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Vanuatu", "Function": "1--45---", "LOCODE": "VUVLI", "Name": "Port Vila", "NameWoDiac": "Port Vila", "Status": "AI", "outflows": 453739.0 }, "geometry": { "type": "Point", "coordinates": [ 168.31366, -17.73648 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Vanuatu", "Function": "1-------", "LOCODE": "VUSAN", "Name": "Santo", "NameWoDiac": "Santo", "Status": "RQ", "outflows": 206498.5 }, "geometry": { "type": "Point", "coordinates": [ 167.16235, -15.51989 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Samoa", "Function": "1--45---", "LOCODE": "WSAPW", "Name": "Apia", "NameWoDiac": "Apia", "Status": "AI", "outflows": 339021.5 }, "geometry": { "type": "Point", "coordinates": [ -171.76666, -13.83333 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Yemen", "Function": "1--45---", "LOCODE": "YEADE", "Name": "Aden", "NameWoDiac": "Aden", "Status": "AI", "outflows": 126082.5 }, "geometry": { "type": "Point", "coordinates": [ 45.03667, 12.77944 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "Yemen", "Function": "1--4----", "LOCODE": "YEMKX", "Name": "Mukalla", "NameWoDiac": "Mukalla", "Status": "AI", "outflows": 30745.0 }, "geometry": { "type": "Point", "coordinates": [ 49.12424, 14.54248 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "South Africa", "Function": "1234----", "LOCODE": "ZAELS", "Name": "East London", "NameWoDiac": "East London", "Status": "AF", "outflows": 15600.0 }, "geometry": { "type": "Point", "coordinates": [ 27.91162, -33.01529 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "South Africa", "Function": "1--45---", "LOCODE": "ZAPLZ", "Name": "Port Elizabeth", "NameWoDiac": "Port Elizabeth", "Status": "AF", "outflows": 2557154.4621100002 }, "geometry": { "type": "Point", "coordinates": [ 25.61494, -33.96109 ] } },
|
||||
{ "type": "Feature", "properties": { "Country": "South Africa", "Function": "1--4----", "LOCODE": "ZARCB", "Name": "Richards Bay", "NameWoDiac": "Richards Bay", "Status": "AF", "outflows": 164538.86664000002 }, "geometry": { "type": "Point", "coordinates": [ 32.03768, -28.78301 ] } }
|
||||
]
|
||||
}
|
||||
34
data/district_heat_share.csv
Normal file
34
data/district_heat_share.csv
Normal file
@ -0,0 +1,34 @@
|
||||
country,share to satisfy heat demand (residential) in percent,capacity[MWth]
|
||||
AT,14,11200
|
||||
BG,16,6162
|
||||
BA,8,
|
||||
HR,6.3,2221
|
||||
CZ,40,
|
||||
DK,65,
|
||||
FI,38,23390
|
||||
FR,5,
|
||||
DE,13.8,
|
||||
HU,7.92875588637399,8549
|
||||
IS,90,8079000
|
||||
IE,0.8,
|
||||
IT,3,8727
|
||||
LV,73,2254
|
||||
LT,56,
|
||||
MK,23.7745607009008,636
|
||||
NO,4,3400
|
||||
PL,42,54912
|
||||
PT,0.070754716981132,34
|
||||
RS,25,5821
|
||||
SI,8.86,1739
|
||||
ES,0.251589260787732,1273
|
||||
SE,50.4,
|
||||
UK,2,
|
||||
BY,70,
|
||||
EE,52,5406
|
||||
KO,3,207
|
||||
RO,23,9962
|
||||
SK,54,15000
|
||||
NL,4,9800
|
||||
CH,4,2792
|
||||
AL,0,
|
||||
ME,0,
|
||||
|
31
data/existing_infrastructure/existing_heating_raw.csv
Normal file
31
data/existing_infrastructure/existing_heating_raw.csv
Normal file
@ -0,0 +1,31 @@
|
||||
,gas boiler,coal boiler,oil boiler,resistive heater,air heat pump,ground heat pump
|
||||
Austria,9.32,0.4,15.42,0,0.72,1.077
|
||||
Belgium,28.39,1.19,19.53,3.14,0.17,0.061
|
||||
Bulgaria,0.16,3.68,0.04,3.46,1.01,0.045
|
||||
Croatia,8.39,0.03,2.88,1.53,0,0
|
||||
Czech Republic,9.26,1.02,0.1,2.73,0.35,0.263
|
||||
Denmark,4.82,0,3.67,2.19,1.9,0.381
|
||||
Estonia,0.22,0.02,0.12,0.27,0.33,0.1
|
||||
Finland,0,0.04,3.79,10.3,1.98,0.58
|
||||
France,76.85,1.03,46.03,87.24,26.14,1.97
|
||||
Germany,131.09,0.44,132.04,0,2.38,3.29
|
||||
Greece,2.17,0.03,18.13,5.91,0,0
|
||||
Hungary,21.21,1.3,0.04,0.06,0.03,0.035
|
||||
Ireland,4.32,0.8,4.85,1.03,0.03,0.03
|
||||
Italy,112.68,1.89,3.33,6.61,54.98,0.6
|
||||
Latvia,1.53,0.4,0,0.03,0,0
|
||||
Lithuania,0,0,0,0,0.01,0.02
|
||||
Luxembourg,0.79,0,0.77,0.09,0.01,0.001
|
||||
Netherlands,81.41,0,0.1,0.1,1.82,0.849
|
||||
Poland,8.25,24.75,9.04,5.96,0.01,0.04
|
||||
Portugal,4.79,0,0.2,21.26,1.58,0.064
|
||||
Romania,16.56,0.32,0.03,0.72,0,0
|
||||
Slovakia,8.05,0.19,0.01,0.55,0.06,0.015
|
||||
Slovenia,0.4,0,1.08,0.4,0.03,0.056
|
||||
Spain,48.99,0.51,17.95,56.58,1.15,0.016
|
||||
Sweden,1.01,0,0.77,3.76,3.42,4.813
|
||||
United Kingdom,160.49,1.26,7.39,13.81,0.81,0.21
|
||||
Norway,,,,,2.91,0.334
|
||||
Switzerland,,,,,1,0.849
|
||||
Serbia,,,,,,
|
||||
Bosnia Herzegovina,,,,,,
|
||||
|
34
data/existing_infrastructure/offwind_capacity_IRENA.csv
Normal file
34
data/existing_infrastructure/offwind_capacity_IRENA.csv
Normal file
@ -0,0 +1,34 @@
|
||||
Country/area,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018
|
||||
Albania,,,,,,,,,,,,,,,,,,,
|
||||
Austria,,,,,,,,,,,,,,,,,,,
|
||||
Belgium,,,,,,,,,,31.5,196.5,196.5,381,707.7,707.7,712,712.2,877.2,1185.9
|
||||
Bosnia Herzg,,,,,,,,,,,,,,,,,,,
|
||||
Bulgaria,,,,,,,,,,,,,,,,,,,
|
||||
Croatia,,,,,,,,,,,,,,,,,,,
|
||||
Czechia,,,,,,,,,,,,,,,,,,,
|
||||
Denmark,50,50,214,423.4,423.4,423.4,423.4,423.4,423.4,660.9,867.9,871.5,921.9,1271.1,1271.1,1271.1,1271.1,1263.8,1700.8
|
||||
Estonia,,,,,,,,,,,,,,,,,,,
|
||||
Finland,,,,,,,,,24,24,26.3,26.3,26.3,26.3,26.3,32,32,72.7,72.7
|
||||
France,,,,,,,,,,,,,,,,,,2,2
|
||||
Germany,,,,,,,,,,35,80,188,268,508,994,3283,4132,5406,6396
|
||||
Greece,,,,,,,,,,,,,,,,,,,
|
||||
Hungary,,,,,,,,,,,,,,,,,,,
|
||||
Ireland,,,,,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2,25.2
|
||||
Italy,,,,,,,,,,,,,,,,,,,
|
||||
Latvia,,,,,,,,,,,,,,,,,,,
|
||||
Lithuania,,,,,,,,,,,,,,,,,,,
|
||||
Luxembourg,,,,,,,,,,,,,,,,,,,
|
||||
Montenegro,,,,,,,,,,,,,,,,,,,
|
||||
Netherlands,,,,,,,108,108,228,228,228,228,228,228,228,357,957,957,957
|
||||
North Macedonia,,,,,,,,,,,,,,,,,,,
|
||||
Norway,,,,,,,,,,2.3,2.3,2.3,2.3,2.3,2.3,2.3,2.3,2.3,2.3
|
||||
Poland,,,,,,,,,,,,,,,,,,,
|
||||
Portugal,,,,,,,,,,,,1.9,2,2,2,2,,,
|
||||
Romania,,,,,,,,,,,,,,,,,,,
|
||||
Serbia,,,,,,,,,,,,,,,,,,,
|
||||
Slovakia,,,,,,,,,,,,,,,,,,,
|
||||
Slovenia,,,,,,,,,,,,,,,,,,,
|
||||
Spain,,,,,,,,,,,,,,5,5,5,5,5,5
|
||||
Sweden,13,22,22,22,22,22,22,131,133,163,163,163,163,212,213,213,203,203,203
|
||||
Switzerland,,,,,,,,,,,,,,,,,,,
|
||||
UK,3.8,3.8,3.8,63.8,123.8,213.8,303.8,393.8,596.2,951.2,1341.5,1838.3,2995.5,3696,4501.3,5093.4,5293.4,6987.9,8216.5
|
||||
|
34
data/existing_infrastructure/onwind_capacity_IRENA.csv
Normal file
34
data/existing_infrastructure/onwind_capacity_IRENA.csv
Normal file
@ -0,0 +1,34 @@
|
||||
Country/area,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018
|
||||
Albania,,,,,,,,,,,,,,,,,,,
|
||||
Austria,50,67,109,322,581,825.2,968.3,991.2,992,1001,1015.8,1106,1337.2,1674.5,2110.3,2488.7,2730,2886.7,3132.7
|
||||
Belgium,14,26,31,67,96,167,212,276,324,576.5,715.5,872.5,989,1072.3,1236.3,1464,1657.8,1919.3,2074.8
|
||||
Bosnia Herzg,,,,,,,,,,,,0.3,0.3,0.3,0.3,0.3,0.3,0.3,50.9
|
||||
Bulgaria,,,,,1,8,27,30,114,333,488,541,677,683,699,699,699,698.4,698.9
|
||||
Croatia,,,,,6,6,17,17,17,70,79,130,180,254,339,418,483,576.1,586.3
|
||||
Czechia,2,,6.4,10.6,16.5,22,43.5,113.8,150,193,213,213,258,262,278,281,282,308.2,316.2
|
||||
Denmark,2340.1,2447.2,2680.6,2696.6,2700.4,2704.5,2712.3,2700.9,2739.5,2821.2,2934,3080.5,3240.1,3547.9,3615.4,3805.9,3974.5,4225.8,4419.8
|
||||
Estonia,,,1,3,7,31,31,50,77,104,108,180,266,248,275,300,310,311.8,310
|
||||
Finland,38,39,43,52,82,82,86,110,119,123,170.7,172.7,230.7,420.7,600.7,973,1533,1971.3,1968.3
|
||||
France,38,66,138,218,358,690,1412,2223,3403,4582,5912,6758,7607.5,8156,9201.4,10298.2,11566.6,13497.4,14898.1
|
||||
Germany,6095,8754,12001,14381,16419,18248,20474,22116,22794,25697,26823,28524,30711,32969,37620,41297,45303,50174,52447
|
||||
Greece,226,270,287,371,470,491,749,846,1022,1171,1298,1640,1753,1809,1978,2091,2370,2624,2877.5
|
||||
Hungary,,1,1,3,3,17,33,61,134,203,293,331,325,329,329,329,329,329,329
|
||||
Ireland,116.5,122.9,134.8,210.3,311.2,468.1,651.3,715.3,917.1,1226.1,1365.2,1559.4,1679.2,1983,2258.1,2426,2760.8,3292.8,3650.9
|
||||
Italy,363,664,780,874,1127,1635,1902,2702,3525,4879,5794,6918,8102,8542,8683,9137,9384,9736.6,10230.2
|
||||
Latvia,2,2,22,26,26,26,26,26,28,29,30,36,59,65.9,68.9,68.2,69.9,77.1,78.2
|
||||
Lithuania,,,,,1,1,31,47,54,98,133,202,275,279,288,436,509,518,533
|
||||
Luxembourg,14,13.9,13.9,20.5,34.9,34.9,34.9,34.9,42.9,42.9,43.7,44.5,58.3,58.3,58.3,63.8,119.7,119.7,122.9
|
||||
Montenegro,,,,,,,,,,,,,,,,,,72,118
|
||||
Netherlands,447,486,672,905,1075,1224,1453,1641,1921,1994,2009,2088,2205,2485,2637,3034,3300,3245,3436
|
||||
North Macedonia,,,,,,,,,,,,,,,37,37,37,37,37
|
||||
Norway,13,13,97,97,152,265,284,348,395,420.7,422.7,509.7,702.7,815.7,856.7,864.7,880.7,1204.7,1708
|
||||
Poland,4,19,32,35,40,121,172,306,526,709,1108,1800,2564,3429,3836,4886,5747,5759.4,5766.1
|
||||
Portugal,83,125,190,268,553,1064,1681,2201,2857,3326,3796,4254.4,4409.6,4607.9,4854.6,4934.8,5124.1,5124.1,5172.4
|
||||
Romania,,,,,,1,1,3,5,15,389,988,1822,2773,3244,3130,3025,3029.8,3032.3
|
||||
Serbia,,,,,,,,,,,,,0.5,0.5,0.5,10.4,17,25,25
|
||||
Slovakia,,,,3,3,5,5,5,5,3,3,3,3,5,3,3,3,4,3
|
||||
Slovenia,,,,,,,,,,,,,,4,4,5,5,5,5.2
|
||||
Spain,2206,3397,4891,5945,8317,9918,11722,14820,16555,19176,20693,21529,22789,22953,22920,22938,22985,23119.5,23400.1
|
||||
Sweden,196,273,335,395,453,500,563,692,956,1312,1854,2601,3443,3982,4875,5606,6232,6408,7097
|
||||
Switzerland,3,5,5,5,9,12,12,12,14,18,42,46,49,60,60,60,75,75,75
|
||||
UK,408.2,489.2,530.2,678.2,809.2,1351.2,1651.2,2083.2,2849.8,3470.8,4079.8,4758,6035,7586.3,8572.7,9212.2,10832.3,12596.9,13553.9
|
||||
|
34
data/existing_infrastructure/solar_capacity_IRENA.csv
Normal file
34
data/existing_infrastructure/solar_capacity_IRENA.csv
Normal file
@ -0,0 +1,34 @@
|
||||
Country/area,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018
|
||||
Albania,,0.1,0.2,0.2,0.2,0.2,0.2,0.2,0.2,0.3,0.4,0.6,0.7,0.8,0.9,1.1,1,1,1
|
||||
Austria,5,7,9,23,27,21,22.4,24.2,30.1,48.9,88.8,174.1,337.5,626,785.2,937.1,1096,1269,1437.6
|
||||
Belgium,,,1,1,1,2,2,20,62,386,1007,1979,2647,2902,3015.2,3131.7,3327,3616.2,3986.5
|
||||
Bosnia Herzg,,,,0.1,0.2,0.3,0.3,0.3,0.3,0.3,0.3,0.3,0.3,1.3,7.2,8.2,14.1,16,18.2
|
||||
Bulgaria,,,,,,,,0,0.1,2,25,154,1013,1020,1026,1029,1028,1035.6,1032.7
|
||||
Croatia,,,,,,,,,,0.3,0.3,0.3,4,19,33,47.8,55.8,60,67.7
|
||||
Czechia,0.1,0.1,0.2,0.3,0.4,0.6,0.8,4,39.5,464.6,1727,1913,2022,2063.5,2067.4,2074.9,2067.9,2069.5,2075.1
|
||||
Denmark,1,1,2,2,2,3,3,3,3,5,7,17,402,571,607,782.1,851,906.4,998
|
||||
Estonia,,,,,,,,,,0.1,0.1,0.2,0.4,1.5,3.3,6.5,10,15,31.9
|
||||
Finland,2,3,3,3,4,4,5,5,6,6,7,7,8,9,11,17,39,82,140
|
||||
France,7,7,8,9,11,13,15,26,80,277,1044,3003.6,4358.8,5277.3,6034.4,7137.5,7702.1,8610.4,9617
|
||||
Germany,114,195,260,435,1105,2056,2899,4170,6120,10564,18004,25914,34075,36708,37898,39222,40677,42291,45179
|
||||
Greece,,1,1,1,1,1,5,9,12,46,202,612,1536,2579,2596,2604,2604,2605.5,2651.6
|
||||
Hungary,,,,,,,,0.4,1,1,2,4,12,35,89,172,235,344,726
|
||||
Ireland,,,,,,,,,,0.6,0.7,0.8,0.9,1,1.6,2.4,5.9,15.7,24.2
|
||||
Italy,19,20,22,26,31,34,45,110,483,1264,3592,13131,16785,18185,18594,18901,19283,19682.3,20107.6
|
||||
Latvia,,,,,,,,,,,,,0.2,0.2,0.2,0.2,0.7,0.7,2
|
||||
Lithuania,,,,,,,,,0.1,0.1,0.1,0.3,7,68,69,69,70,73.8,82
|
||||
Luxembourg,,0.2,1.6,14.2,23.6,23.6,23.7,23.9,24.6,26.4,29.5,40.7,74.7,95,109.9,116.3,121.9,128.1,130.6
|
||||
Montenegro,,,,,,,0,0.2,0.4,0.4,0.6,0.8,0.9,1.1,2.1,2.7,3.1,3.4,3.4
|
||||
Netherlands,13,21,26,46,50,51,53,54,59,69,90,149,369,746,1048,1515,2049,2903,4522
|
||||
North Macedonia,,,,,,,,,,,0,2,4,7,15,17,16.7,16.7,20.6
|
||||
Norway,6,6,6,7,7,7,8,8,8.3,8.7,9.1,9.5,10,11,13,15,26.7,44.9,68.4
|
||||
Poland,,,,,,,,,,,,1.1,1.3,2.4,27.2,107.8,187.2,287.1,562
|
||||
Portugal,1,1,1,2,2,2,3,24,59,115,134,172,238,296,415,447,512.8,579.2,667.4
|
||||
Romania,,,,,,,,,0.1,0.1,0.1,1,41,761,1293,1326,1372,1374.1,1385.8
|
||||
Serbia,,,,,,0.1,0.2,0.4,0.9,1.2,1.3,1.5,3.1,4.7,6,9,11,10,10
|
||||
Slovakia,,,,,,,,,,,19,496,513,533,533,533,533,528,472
|
||||
Slovenia,,,0,0,0,0,0.2,0.6,1,4,12,57,142,187,223,238,233,246.8,221.3
|
||||
Spain,10,13,17,22,33,52,130,494,3384,3423,3873,4283,4569,4690,4697,4704,4713,4723,4763.5
|
||||
Sweden,3,3,3,4,4,4,5,6,8,9,11,12,24,43,60,104,153,402,492
|
||||
Switzerland,16,18,20,22,24,28,30,37,49,79,125,223,437,756,1061,1394,1664,1906,2171
|
||||
UK,2,3,4,6,8,11,14,18,23,27,95,1000,1753,2937,5528,9601.2,11930.5,12781.8,13118.3
|
||||
|
25
data/heat_load_profile.csv
Normal file
25
data/heat_load_profile.csv
Normal file
@ -0,0 +1,25 @@
|
||||
hour,residential space weekday,residential space weekend,residential water weekday,residential water weekend,services space weekday,services space weekend,services water weekday,services water weekend
|
||||
0,0.9181438689,0.9421512708,1,1,0.9181438689,0.9421512708,1,1
|
||||
1,0.9172359071,0.9400891069,1,1,0.9172359071,0.9400891069,1,1
|
||||
2,0.9269464481,0.9461062015,1,1,0.9269464481,0.9461062015,1,1
|
||||
3,0.9415047932,0.9535084941,1,1,0.9415047932,0.9535084941,1,1
|
||||
4,0.9656299507,0.9651094993,1,1,0.9656299507,0.9651094993,1,1
|
||||
5,1.0221166443,0.9834676747,1,1,1.0221166443,0.9834676747,1,1
|
||||
6,1.1553090493,1.0124171051,1,1,1.1553090493,1.0124171051,1,1
|
||||
7,1.2093411031,1.0446615927,1,1,1.2093411031,1.0446615927,1,1
|
||||
8,1.1470295942,1.088203419,1,1,1.1470295942,1.088203419,1,1
|
||||
9,1.0877191341,1.1110334576,1,1,1.0877191341,1.1110334576,1,1
|
||||
10,1.0418327372,1.0926752822,1,1,1.0418327372,1.0926752822,1,1
|
||||
11,1.0062977133,1.055488209,1,1,1.0062977133,1.055488209,1,1
|
||||
12,0.9837030359,1.0251266112,1,1,0.9837030359,1.0251266112,1,1
|
||||
13,0.9667570278,0.9990015154,1,1,0.9667570278,0.9990015154,1,1
|
||||
14,0.9548320932,0.9782897278,1,1,0.9548320932,0.9782897278,1,1
|
||||
15,0.9509232061,0.9698167237,1,1,0.9509232061,0.9698167237,1,1
|
||||
16,0.9636973319,0.974288587,1,1,0.9636973319,0.974288587,1,1
|
||||
17,0.9799372563,0.9886456216,1,1,0.9799372563,0.9886456216,1,1
|
||||
18,1.0046501848,1.0084159643,1,1,1.0046501848,1.0084159643,1,1
|
||||
19,1.0079452419,1.0171243296,1,1,1.0079452419,1.0171243296,1,1
|
||||
20,0.9860566481,0.9994722379,1,1,0.9860566481,0.9994722379,1,1
|
||||
21,0.9705228074,0.982761591,1,1,0.9705228074,0.982761591,1,1
|
||||
22,0.9586485819,0.9698167237,1,1,0.9586485819,0.9698167237,1,1
|
||||
23,0.9335023778,0.9515079292,1,1,0.9335023778,0.9515079292,1,1
|
||||
|
25
data/heat_load_profile_BDEW.csv
Normal file
25
data/heat_load_profile_BDEW.csv
Normal file
@ -0,0 +1,25 @@
|
||||
,residential space weekday,residential space weekend,services space weekday,services space weekend,residential water weekday,residential water weekend,services water weekday,services water weekend
|
||||
0,0.5437843306385036,0.5391846410003029,0.740230434593118,0.7918173557545402,1.0,1.0,1.0,1.0
|
||||
1,0.5690496225400243,0.5641534370440313,0.7642025524842398,0.7929627291950984,1.0,1.0,1.0,1.0
|
||||
2,0.5624023211873742,0.5575494117194042,0.8264420882344785,0.8961602364492307,1.0,1.0,1.0,1.0
|
||||
3,0.6120351867307156,0.6074588966300298,0.9338477492552973,1.066547622880321,1.0,1.0,1.0,1.0
|
||||
4,0.8210089232467712,0.8188451841881503,1.1288089786462463,1.2779268432155158,1.0,1.0,1.0,1.0
|
||||
5,1.2287073985428116,1.2315677844536332,1.3311522394966053,1.2808129834243316,1.0,1.0,1.0,1.0
|
||||
6,1.327953505819319,1.3349874311629708,1.3976491755316236,1.3076676145167292,1.0,1.0,1.0,1.0
|
||||
7,1.2533048874868005,1.2584095945395426,1.3529869654334066,1.239881414312941,1.0,1.0,1.0,1.0
|
||||
8,1.204661538907097,1.206562127967529,1.2631870820835946,1.157513929299677,1.0,1.0,1.0,1.0
|
||||
9,1.1511425365003825,1.152931252109671,1.183486516733693,1.1001631309844286,1.0,1.0,1.0,1.0
|
||||
10,1.0982914366923946,1.0987739728887453,1.1056637898031139,1.0553379006911972,1.0,1.0,1.0,1.0
|
||||
11,1.0602079991199889,1.0598534287519163,1.0536117591812475,0.9953570175561463,1.0,1.0,1.0,1.0
|
||||
12,1.0430483470403709,1.042552786631541,1.0075511014823457,0.9238971341830102,1.0,1.0,1.0,1.0
|
||||
13,1.023765876994618,1.0234573235486537,0.983633820661761,0.928978159404834,1.0,1.0,1.0,1.0
|
||||
14,1.0250355817085612,1.0241187665206792,0.973887563496691,0.9277637088455348,1.0,1.0,1.0,1.0
|
||||
15,1.0419068035344277,1.0407369052119213,0.968639109712126,0.940383626933661,1.0,1.0,1.0,1.0
|
||||
16,1.0886607269753739,1.0871365340901091,0.9776106671510321,0.9762628252848075,1.0,1.0,1.0,1.0
|
||||
17,1.1391891744979068,1.1377875788466947,0.9713068946564802,0.9923707220696051,1.0,1.0,1.0,1.0
|
||||
18,1.1813708458227477,1.1815796155786216,0.97710710371407,0.9822063279944322,1.0,1.0,1.0,1.0
|
||||
19,1.2048721952031847,1.2066686818939167,0.9620977486617706,0.9872726025741575,1.0,1.0,1.0,1.0
|
||||
20,1.1883594612741015,1.1911629803333679,0.9096499832485738,0.9736368622053816,1.0,1.0,1.0,1.0
|
||||
21,1.0841006081889941,1.0875548281900813,0.7954827338259405,0.8733383541170725,1.0,1.0,1.0,1.0
|
||||
22,0.8887378869444746,0.8893062174837649,0.7007233800713178,0.7753100551108082,1.0,1.0,1.0,1.0
|
||||
23,0.6584028044030574,0.6576606192147261,0.6910405618412271,0.756430842996538,1.0,1.0,1.0,1.0
|
||||
|
25
data/heat_load_profile_DK_AdamJensen.csv
Normal file
25
data/heat_load_profile_DK_AdamJensen.csv
Normal file
@ -0,0 +1,25 @@
|
||||
hour,weekday,weekend
|
||||
0,0.9181438689,0.9421512708
|
||||
1,0.9172359071,0.9400891069
|
||||
2,0.9269464481,0.9461062015
|
||||
3,0.9415047932,0.9535084941
|
||||
4,0.9656299507,0.9651094993
|
||||
5,1.0221166443,0.9834676747
|
||||
6,1.1553090493,1.0124171051
|
||||
7,1.2093411031,1.0446615927
|
||||
8,1.1470295942,1.088203419
|
||||
9,1.0877191341,1.1110334576
|
||||
10,1.0418327372,1.0926752822
|
||||
11,1.0062977133,1.055488209
|
||||
12,0.9837030359,1.0251266112
|
||||
13,0.9667570278,0.9990015154
|
||||
14,0.9548320932,0.9782897278
|
||||
15,0.9509232061,0.9698167237
|
||||
16,0.9636973319,0.974288587
|
||||
17,0.9799372563,0.9886456216
|
||||
18,1.0046501848,1.0084159643
|
||||
19,1.0079452419,1.0171243296
|
||||
20,0.9860566481,0.9994722379
|
||||
21,0.9705228074,0.982761591
|
||||
22,0.9586485819,0.9698167237
|
||||
23,0.9335023778,0.9515079292
|
||||
|
31
data/hydrogen_salt_cavern_potentials.csv
Normal file
31
data/hydrogen_salt_cavern_potentials.csv
Normal file
@ -0,0 +1,31 @@
|
||||
ct,TWh
|
||||
AT,
|
||||
BA,
|
||||
BE,
|
||||
BG,
|
||||
CH,
|
||||
CZ,
|
||||
DE,4500
|
||||
DK,700
|
||||
EE,
|
||||
ES,350
|
||||
FI,
|
||||
FR,
|
||||
GB,1050
|
||||
GR,120
|
||||
HR,
|
||||
HU,
|
||||
IE,
|
||||
IT,
|
||||
LT,
|
||||
LU,
|
||||
LV,
|
||||
NL,150
|
||||
NO,
|
||||
PL,120
|
||||
PT,400
|
||||
RO,
|
||||
RS,
|
||||
SE,
|
||||
SI,
|
||||
SK,
|
||||
|
3
data/override_component_attrs/buses.csv
Normal file
3
data/override_component_attrs/buses.csv
Normal file
@ -0,0 +1,3 @@
|
||||
attribute,type,unit,default,description,status
|
||||
location,string,n/a,n/a,Reference to original electricity bus,Input (optional)
|
||||
unit,string,n/a,MWh,Unit of the bus (descriptive only), Input (optional)
|
||||
|
4
data/override_component_attrs/generators.csv
Normal file
4
data/override_component_attrs/generators.csv
Normal file
@ -0,0 +1,4 @@
|
||||
attribute,type,unit,default,description,status
|
||||
carrier,string,n/a,n/a,carrier,Input (optional)
|
||||
lifetime,float,years,inf,lifetime,Input (optional)
|
||||
build_year,int,year ,0,build year,Input (optional)
|
||||
|
13
data/override_component_attrs/links.csv
Normal file
13
data/override_component_attrs/links.csv
Normal file
@ -0,0 +1,13 @@
|
||||
attribute,type,unit,default,description,status
|
||||
bus2,string,n/a,n/a,2nd bus,Input (optional)
|
||||
bus3,string,n/a,n/a,3rd bus,Input (optional)
|
||||
bus4,string,n/a,n/a,4th bus,Input (optional)
|
||||
efficiency2,static or series,per unit,1,2nd bus efficiency,Input (optional)
|
||||
efficiency3,static or series,per unit,1,3rd bus efficiency,Input (optional)
|
||||
efficiency4,static or series,per unit,1,4th bus efficiency,Input (optional)
|
||||
p2,series,MW,0,2nd bus output,Output
|
||||
p3,series,MW,0,3rd bus output,Output
|
||||
p4,series,MW,0,4th bus output,Output
|
||||
carrier,string,n/a,n/a,carrier,Input (optional)
|
||||
lifetime,float,years,inf,lifetime,Input (optional)
|
||||
build_year,int,year ,0,build year,Input (optional)
|
||||
|
2
data/override_component_attrs/loads.csv
Normal file
2
data/override_component_attrs/loads.csv
Normal file
@ -0,0 +1,2 @@
|
||||
attribute,type,unit,default,description,status
|
||||
carrier,string,n/a,n/a,carrier,Input (optional)
|
||||
|
4
data/override_component_attrs/stores.csv
Normal file
4
data/override_component_attrs/stores.csv
Normal file
@ -0,0 +1,4 @@
|
||||
attribute,type,unit,default,description,status
|
||||
carrier,string,n/a,n/a,carrier,Input (optional)
|
||||
lifetime,float,years,inf,lifetime,Input (optional)
|
||||
build_year,int,year ,0,build year,Input (optional)
|
||||
|
49
data/retro/comparative_level_investment.csv
Normal file
49
data/retro/comparative_level_investment.csv
Normal file
@ -0,0 +1,49 @@
|
||||
NA_ITEM,Price level indices (EU28=100),,,,,,,,,
|
||||
PPP_CAT,Actual individual consumption,,,,,,,,,
|
||||
,,,,,,,,,,
|
||||
GEO/TIME,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018
|
||||
European Union - 28 countries,100.0,100.0,100.0,100.0,100.0,100.0,100.0,100.0,100.0,100.0
|
||||
Belgium,113.6,111.9,112.4,111.5,111.0,108.9,106.3,110.3,112.3,112.5
|
||||
Bulgaria,47.1,45.7,45.5,45.0,44.2,42.6,42.2,43.2,45.1,46.3
|
||||
Czech Republic,64.5,66.6,68.9,66.9,63.3,58.3,58.4,60.5,62.4,65.0
|
||||
Denmark,141.7,140.0,139.9,140.0,139.3,138.5,135.0,140.0,138.9,138.1
|
||||
Germany,104.6,103.1,102.2,101.1,102.5,101.5,100.4,102.6,103.7,104.1
|
||||
Estonia,67.5,66.0,67.2,67.6,69.9,69.9,68.9,71.0,73.9,76.3
|
||||
Ireland,129.9,122.7,122.5,120.5,123.2,124.9,122.2,126.5,129.1,129.2
|
||||
Greece,93.6,95.4,94.9,91.9,87.8,83.8,81.0,82.3,83.0,81.8
|
||||
Spain,97.5,98.7,98.5,95.8,95.1,92.7,90.0,92.7,93.7,93.7
|
||||
France,111.2,109.9,109.6,108.7,107.0,106.0,104.0,105.8,107.1,107.4
|
||||
Croatia,70.2,70.1,68.1,65.5,64.5,62.5,60.7,61.3,63.0,64.0
|
||||
Italy,103.6,100.4,101.5,101.1,102.3,102.6,100.3,101.1,101.6,101.4
|
||||
Cyprus,92.0,94.6,95.8,96.0,95.2,92.0,88.5,89.8,91.2,90.6
|
||||
Latvia,68.1,62.3,65.5,65.9,66.0,66.0,64.2,66.9,68.3,69.5
|
||||
Lithuania,60.3,57.8,58.3,58.0,57.8,56.9,55.9,58.3,60.0,61.4
|
||||
Luxembourg,130.0,136.5,136.0,135.8,135.1,135.7,132.1,137.0,139.9,141.6
|
||||
Hungary,58.2,57.4,56.4,54.9,54.4,53.4,53.3,56.2,59.4,59.0
|
||||
Malta,75.8,76.6,78.0,78.0,80.8,80.5,79.8,81.4,81.9,83.4
|
||||
Netherlands,108.5,112.3,112.7,111.3,111.9,111.9,109.6,113.8,114.6,114.8
|
||||
Austria,109.9,109.2,110.1,108.9,109.1,109.1,107.2,110.2,112.8,113.7
|
||||
Poland,53.1,55.2,53.7,52.1,52.4,52.5,51.1,50.9,53.5,54.3
|
||||
Portugal,85.2,85.0,85.3,82.7,81.1,80.4,78.7,81.6,83.5,84.6
|
||||
Romania,49.1,46.9,47.7,45.6,47.8,47.6,47.2,46.8,48.0,48.6
|
||||
Slovenia,85.3,84.3,83.7,81.8,82.1,81.5,79.8,82.3,82.7,83.8
|
||||
Slovakia,66.6,62.5,63.4,63.4,63.4,63.3,62.3,63.6,65.4,66.1
|
||||
Finland,121.0,120.3,121.6,121.8,124.0,122.9,119.6,122.8,123.3,123.4
|
||||
Sweden,109.5,124.6,131.7,134.3,140.5,133.6,128.8,135.3,134.5,126.9
|
||||
United Kingdom,107.5,111.4,111.3,118.6,117.0,123.6,134.7,123.5,117.6,117.7
|
||||
Iceland,94.9,107.6,109.6,111.6,116.0,123.4,132.5,154.5,172.3,163.7
|
||||
Norway,142.4,158.8,165.3,172.5,166.9,157.2,152.2,155.0,157.3,155.4
|
||||
Switzerland,131.6,146.4,161.7,160.6,155.1,153.0,167.0,169.8,167.1,159.1
|
||||
Candidate and potential candidate countries except Turkey and Kosovo (under United Nations Security Council Resolution 1244/99),48.0,45.6,47.1,44.8,46.4,45.2,43.4,44.4,46.0,47.5
|
||||
Montenegro,52.3,49.5,49.3,50.1,50.5,49.3,48.0,48.7,50.5,51.1
|
||||
North Macedonia,41.4,41.3,42.7,42.1,42.5,41.9,40.9,41.7,43.2,43.3
|
||||
Albania,46.2,42.8,42.1,40.6,41.9,41.5,39.8,43.0,43.5,46.6
|
||||
Serbia,48.3,45.0,48.0,44.5,47.3,45.5,43.1,43.8,46.1,47.9
|
||||
Turkey,55.4,61.2,54.7,58.5,57.7,51.6,50.5,50.2,45.4,37.0
|
||||
Bosnia and Herzegovina,51.6,50.7,50.6,49.2,49.1,48.4,47.0,47.5,48.2,48.9
|
||||
Kosovo (under United Nations Security Council Resolution 1244/99),:,:,:,:,:,:,:,:,:,:
|
||||
United States,92.4,98,93.3,101.2,100.3,99,115.9,121.1,120.8,115.2
|
||||
Japan,115.1,126.1,127.8,133.8,101.7,94.8,96.5,113,109.4,103.9
|
||||
,,,,,,,,,,
|
||||
"Source: Eurostat Purchasing power parities (PPPs), price level indices and real expenditures for ESA 2010 aggregates (2019)",,,,,,,,,,
|
||||
https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Comparative_price_levels_for_investment,,,,,,,,,,
|
||||
|
63129
data/retro/data_building_stock.csv
Normal file
63129
data/retro/data_building_stock.csv
Normal file
File diff suppressed because it is too large
Load Diff
164
data/retro/electricity_taxes_eu.csv
Normal file
164
data/retro/electricity_taxes_eu.csv
Normal file
@ -0,0 +1,164 @@
|
||||
Electricity prices for household consumers - bi-annual data (from 2007 onwards) [nrg_pc_204],,,,
|
||||
,,,,
|
||||
Last update,30.10.19,,,
|
||||
Extracted on,14.11.19,,,
|
||||
Source of data,Eurostat,,,
|
||||
,,,,
|
||||
PRODUCT,Electrical energy,,,
|
||||
CONSOM,Band DC : 2 500 kWh < Consumption < 5 000 kWh,,,
|
||||
UNIT,Kilowatt-hour,,,
|
||||
TIME,2018S1,,,
|
||||
,,,,
|
||||
CURRENCY,Euro,Euro,Euro,
|
||||
GEO/TAX,Excluding taxes and levies,Excluding VAT and other recoverable taxes and levies,All taxes and levies included,% cost without taxes
|
||||
European Union - 28 countries,0.1285,0.1756,0.2052,0.626218323586745
|
||||
"Euro area (EA11-2000, EA12-2006, EA13-2007, EA15-2008, EA16-2010, EA17-2013, EA18-2014, EA19)",0.1331,0.1855,0.2188,0.608318098720293
|
||||
Belgium,0.1903,0.2279,0.2733,0.696304427369191
|
||||
Bulgaria,0.0816,0.0816,0.0979,0.833503575076609
|
||||
Czech Republic,0.1286,0.1298,0.1573,0.817546090273363
|
||||
Denmark,0.1011,0.2501,0.3126,0.32341650671785
|
||||
Germany,0.1379,0.2510,0.2987,0.461667224640107
|
||||
Estonia,0.0989,0.1123,0.1348,0.733679525222552
|
||||
Ireland,0.1846,0.2087,0.2369,0.779231743351625
|
||||
Greece,0.1132,0.1482,0.1672,0.677033492822967
|
||||
Spain,0.1873,0.1969,0.2383,0.785984053713806
|
||||
France,0.1134,0.1492,0.1748,0.648741418764302
|
||||
Croatia,0.1020,0.1160,0.1311,0.778032036613272
|
||||
Italy,0.1285,0.1873,0.2067,0.621673923560716
|
||||
Cyprus,0.1445,0.1606,0.1893,0.763338615953513
|
||||
Latvia,0.1035,0.1266,0.1531,0.676028739386022
|
||||
Lithuania,0.0771,0.0906,0.1097,0.702825888787603
|
||||
Luxembourg,0.1283,0.1547,0.1671,0.767803710353082
|
||||
Hungary,0.0885,0.0885,0.1123,0.78806767586821
|
||||
Malta,0.1209,0.1224,0.1285,0.940856031128405
|
||||
Netherlands,0.1187,0.1410,0.1706,0.6957796014068
|
||||
Austria,0.1232,0.1638,0.1966,0.626653102746694
|
||||
Poland,0.0906,0.1146,0.1410,0.642553191489362
|
||||
Portugal,0.1007,0.1826,0.2246,0.448352626892253
|
||||
Romania,0.0990,0.1120,0.1333,0.742685671417854
|
||||
Slovenia,0.1108,0.1322,0.1613,0.686918784872908
|
||||
Slovakia,0.0942,0.1305,0.1566,0.601532567049808
|
||||
Finland,0.1074,0.1300,0.1612,0.666253101736973
|
||||
Sweden,0.1202,0.1513,0.1891,0.635642517186674
|
||||
United Kingdom,0.1347,0.1797,0.1887,0.713831478537361
|
||||
Iceland,0.1222,0.1246,0.1545,0.790938511326861
|
||||
Liechtenstein,:,:,:,#VALUE!
|
||||
Norway,0.1254,0.1434,0.1751,0.716162193032553
|
||||
Montenegro,0.0828,0.0844,0.1024,0.80859375
|
||||
North Macedonia,0.0662,0.0662,0.0781,0.847631241997439
|
||||
Albania,:,:,:,#VALUE!
|
||||
Serbia,0.0539,0.0587,0.0705,0.764539007092199
|
||||
Turkey,0.0727,0.0766,0.0904,0.804203539823009
|
||||
Bosnia and Herzegovina,0.0722,0.0738,0.0864,0.835648148148148
|
||||
Kosovo (under United Nations Security Council Resolution 1244/99),0.0569,0.0586,0.0633,0.898894154818325
|
||||
Moldova,0.1020,0.1020,0.1020,1
|
||||
Ukraine,0.0342,0.0342,0.0410,0.834146341463415
|
||||
,,,0.157271052631579,
|
||||
Special value:,,,,
|
||||
:,not available,,,
|
||||
,,,,
|
||||
PRODUCT,Electrical energy,,,
|
||||
CONSOM,Band DC : 2 500 kWh < Consumption < 5 000 kWh,,,
|
||||
UNIT,Kilowatt-hour,,,
|
||||
TIME,2018S2,,,
|
||||
,,,,
|
||||
CURRENCY,Euro,Euro,Euro,
|
||||
GEO/TAX,Excluding taxes and levies,Excluding VAT and other recoverable taxes and levies,All taxes and levies included,
|
||||
European Union - 28 countries,0.1329,0.1810,0.2113,
|
||||
"Euro area (EA11-2000, EA12-2006, EA13-2007, EA15-2008, EA16-2010, EA17-2013, EA18-2014, EA19)",0.1376,0.1902,0.2242,
|
||||
Belgium,0.1998,0.2429,0.2937,
|
||||
Bulgaria,0.0838,0.0838,0.1005,
|
||||
Czechia,0.1299,0.1311,0.1586,
|
||||
Denmark,0.1116,0.2499,0.3123,
|
||||
Germany (until 1990 former territory of the FRG),0.1378,0.2521,0.3000,
|
||||
Estonia,0.1048,0.1182,0.1418,
|
||||
Ireland,0.2006,0.2237,0.2539,
|
||||
Greece,0.1125,0.1458,0.1646,
|
||||
Spain,0.1947,0.2047,0.2477,
|
||||
France,0.1168,0.1537,0.1799,
|
||||
Croatia,0.1028,0.1169,0.1321,
|
||||
Italy,0.1416,0.1964,0.2161,
|
||||
Cyprus,0.1745,0.1850,0.2183,
|
||||
Latvia,0.1041,0.1249,0.1511,
|
||||
Lithuania,0.0771,0.0906,0.1097,
|
||||
Luxembourg,0.1302,0.1566,0.1691,
|
||||
Hungary,0.0880,0.0880,0.1118,
|
||||
Malta,0.1229,0.1244,0.1306,
|
||||
Netherlands,0.1212,0.1420,0.1707,
|
||||
Austria,0.1265,0.1676,0.2012,
|
||||
Poland,0.0889,0.1135,0.1396,
|
||||
Portugal,0.1028,0.1864,0.2293,
|
||||
Romania,0.0964,0.1107,0.1317,
|
||||
Slovenia,0.1125,0.1342,0.1638,
|
||||
Slovakia,0.0849,0.1218,0.1462,
|
||||
Finland,0.1144,0.1369,0.1698,
|
||||
Sweden,0.1287,0.1592,0.1990,
|
||||
United Kingdom,0.1401,0.1927,0.2024,
|
||||
Iceland,0.1152,0.1175,0.1457,
|
||||
Liechtenstein,:,:,:,
|
||||
Norway,0.1382,0.1562,0.1907,
|
||||
Montenegro,0.0829,0.0848,0.1030,
|
||||
North Macedonia,0.0667,0.0667,0.0787,
|
||||
Albania,0.0759,0.0759,0.0910,
|
||||
Serbia,0.0542,0.0591,0.0709,
|
||||
Turkey,0.0688,0.0726,0.0857,
|
||||
Bosnia and Herzegovina,0.0729,0.0744,0.0871,
|
||||
Kosovo (under United Nations Security Council Resolution 1244/99),0.0579,0.0591,0.0638,
|
||||
Moldova,0.0960,0.0960,0.1029,
|
||||
Ukraine,0.0342,0.0342,0.0410,
|
||||
,,,,
|
||||
Special value:,,,,
|
||||
:,not available,,,
|
||||
,,,,
|
||||
PRODUCT,Electrical energy,,,
|
||||
CONSOM,Band DC : 2 500 kWh < Consumption < 5 000 kWh,,,
|
||||
UNIT,Kilowatt-hour,,,
|
||||
TIME,2019S1,,,
|
||||
,,,,
|
||||
CURRENCY,Euro,Euro,Euro,
|
||||
GEO/TAX,Excluding taxes and levies,Excluding VAT and other recoverable taxes and levies,All taxes and levies included,
|
||||
European Union - 28 countries,0.1351,0.1841,0.2147,
|
||||
"Euro area (EA11-2000, EA12-2006, EA13-2007, EA15-2008, EA16-2010, EA17-2013, EA18-2014, EA19)",0.1396,0.1928,0.2270,
|
||||
Belgium,0.1965,0.2355,0.2839,
|
||||
Bulgaria,0.0831,0.0831,0.0997,
|
||||
Czechia,0.1433,0.1444,0.1748,
|
||||
Denmark,0.1084,0.2387,0.2984,
|
||||
Germany (until 1990 former territory of the FRG),0.1473,0.2595,0.3088,
|
||||
Estonia,0.0982,0.1131,0.1357,
|
||||
Ireland,0.2027,0.2134,0.2423,
|
||||
Greece,0.1139,0.1482,0.1650,
|
||||
Spain,0.1889,0.1986,0.2403,
|
||||
France,0.1138,0.1508,0.1765,
|
||||
Croatia,0.1028,0.1169,0.1321,
|
||||
Italy,0.1432,0.2090,0.2301,
|
||||
Cyprus,0.1762,0.1867,0.2203,
|
||||
Latvia,0.1136,0.1347,0.1629,
|
||||
Lithuania,0.0947,0.1037,0.1255,
|
||||
Luxembourg,0.1326,0.1666,0.1798,
|
||||
Hungary,0.0882,0.0882,0.1120,
|
||||
Malta,0.1228,0.1243,0.1305,
|
||||
Netherlands,0.1357,0.1708,0.2052,
|
||||
Austria,0.1316,0.1695,0.2034,
|
||||
Poland,0.0884,0.1092,0.1343,
|
||||
Portugal,0.1103,0.1751,0.2154,
|
||||
Romania,0.0983,0.1141,0.1358,
|
||||
Slovenia,0.1125,0.1339,0.1634,
|
||||
Slovakia,0.0962,0.1314,0.1577,
|
||||
Finland,0.1173,0.1398,0.1734,
|
||||
Sweden,0.1297,0.1612,0.2015,
|
||||
United Kingdom,0.1450,0.2021,0.2122,
|
||||
Iceland,0.1112,0.1134,0.1406,
|
||||
Liechtenstein,:,:,:,
|
||||
Norway,0.1360,0.1529,0.1867,
|
||||
Montenegro,0.0834,0.0850,0.1032,
|
||||
North Macedonia,:,:,:,
|
||||
Albania,:,:,:,
|
||||
Serbia,0.0541,0.0589,0.0706,
|
||||
Turkey,0.0684,0.0718,0.0847,
|
||||
Bosnia and Herzegovina,0.0729,0.0746,0.0873,
|
||||
Kosovo (under United Nations Security Council Resolution 1244/99),0.0537,0.0556,0.0600,
|
||||
Moldova,0.0936,0.0936,0.0936,
|
||||
Ukraine,0.0369,0.0369,0.0442,
|
||||
,,,,
|
||||
Special value:,,,,
|
||||
:,not available,,,
|
||||
|
17
data/retro/floor_area_missing.csv
Normal file
17
data/retro/floor_area_missing.csv
Normal file
@ -0,0 +1,17 @@
|
||||
country,sector,estimated,value,source,,comments,population [in Million],
|
||||
AL,residential,0,64,p.13 1.6 million m² = 2.5% of total floor area,https://www.buildup.eu/sites/default/files/content/sled_albania_residential_building_eng.pdf,,,
|
||||
AL,services,0,,,,,,
|
||||
BA,residential,0,125.89,Tabula,https://episcope.eu/building-typology/country/ba/,strong differences ? other source claims more than 300 Million m²,,https://www.buildup.eu/sites/default/files/content/sled_serbia_building_eng.pdf
|
||||
BA,services,0,,,,,,
|
||||
RS,residential,0,72.3,Odyssee(2011),https://odyssee.enerdata.net/database/,,,
|
||||
RS,services,0,,,,,,
|
||||
MK,residential,0,,"Worldbank p.7 Skopje 75% residential, 25% commercial",http://documents.albankaldawli.org/curated/ar/838951574180734318/pdf/Project-Information-Document-North-Macedonia-Public-Sector-Energy-Efficiency-Project-P149990.pdf,15 % live in illegal constructed buildings ? not part of the statistics,2.1,
|
||||
MK,services,0,,,,,,
|
||||
ME,residential,0,19.625,p.13 0.314 million m² = 1.6% of total floor area,buildup.eu/sites/default/files/content/sled_montenegro_building_eng.pdf,Only 50 % of the floor area is heated p.12,,buildup.eu/sites/default/files/content/sled_montenegro_building_eng.pdf
|
||||
ME,services,0,,,,,,
|
||||
CH,residential,0,99.45,Odyssee(2015),,,,
|
||||
CH,services,1,78.1392857142857,p.8 44%floor area is services,https://bta.climate-kic.org/wp-content/uploads/2018/04/171123-CK-BTA-DEF-BMB_SWITZERLAND_.pdf,,,
|
||||
NO,residential,0,121.55,Odyssee(2015),,,,
|
||||
NO,services,0,115.21,Odyssee(2015),,,,
|
||||
PL,residential,0,1028.41,EU Building Database,,,,
|
||||
PL,services,0,498.84,EU Building Database,,,,
|
||||
|
7
data/retro/retro_cost_germany.csv
Normal file
7
data/retro/retro_cost_germany.csv
Normal file
@ -0,0 +1,7 @@
|
||||
component,cost_fix,cost_var,life_time,comment,additional source
|
||||
wall,70.34,2.36,40,Agora Energiewende p.110,
|
||||
floor,39.39,1.3,40,Agora Energiewende p.110,
|
||||
roof,75.61,1.3,40,Agora Energiewende p.110,https://www.baulinks.de/webplugin/2018/1524.php4
|
||||
window,nan,nan,35,,
|
||||
source: p.37 https://www.umweltbundesamt.de/sites/default/files/medien/1410/publikationen/2019-10-29_texte_132-2019_energieaufwand-gebaeudekonzepte.pdf,,,https://www.agora-energiewende.de/en/publications/building-sector-efficiency-a-crucial-component-of-the-energy-transition/,,
|
||||
,,,p.115,,
|
||||
|
9
data/retro/u_values_poland.csv
Normal file
9
data/retro/u_values_poland.csv
Normal file
@ -0,0 +1,9 @@
|
||||
component,Before 1945,1945 - 1969,1970 - 1979,1980 - 1989,1990 - 1999,2000 - 2010,Post 2010,sector
|
||||
Walls,1.7,1.4,0.9,0.9,0.6,0.4,1.7,residential
|
||||
Windows,4.6,3.6,2.6,2.6,2.1,2.1,2.1,residential
|
||||
Roof,0.8,0.7,0.6,0.6,0.6,0.4,0.33,residential
|
||||
Floor,1.9,1.4,1.2,1.1,0.9,0.6,0.45,residential
|
||||
Walls,1.3,1.3,1.3,0.8,0.6,0.6,0.6,services
|
||||
Windows,4.7,3.7,2.6,2.6,2.3,2.1,2.1,services
|
||||
Roof,1,0.9,0.7,0.5,0.3,0.3,0.3,services
|
||||
Floor,1.6,1.2,1.2,1.1,1,0.7,0.7,services
|
||||
|
8
data/retro/window_assumptions.csv
Normal file
8
data/retro/window_assumptions.csv
Normal file
@ -0,0 +1,8 @@
|
||||
strength,u_value,cost,u_limit,comment
|
||||
[m],[W/m^2K],EUR/m^2,[W/m^2K],
|
||||
0.076,1.34,180.08,3.5,Double-glazing
|
||||
0.197,0.8,225,1.3,Triple-glazing
|
||||
,,,,
|
||||
"source: https://www.agora-energiewende.de/en/publications/building-sector-efficiency-a-crucial-component-of-the-energy-transition/
|
||||
p.115
|
||||
",,,,
|
||||
|
30
data/urban_percent.csv
Normal file
30
data/urban_percent.csv
Normal file
@ -0,0 +1,30 @@
|
||||
AT,66
|
||||
BA,40
|
||||
BE,98
|
||||
BG,74
|
||||
CH,74
|
||||
CZ,73
|
||||
DE,75
|
||||
DK,88
|
||||
EE,68
|
||||
ES,80
|
||||
FI,84
|
||||
FR,80
|
||||
GB,83
|
||||
GR,78
|
||||
HR,59
|
||||
HU,71
|
||||
IE,63
|
||||
IT,69
|
||||
LT,67
|
||||
LU,90
|
||||
LV,67
|
||||
NL,90
|
||||
NO,80
|
||||
PL,61
|
||||
PT,63
|
||||
RO,55
|
||||
RS,56
|
||||
SE,86
|
||||
SI,50
|
||||
SK,54
|
||||
|
14
doc/conf.py
14
doc/conf.py
@ -18,7 +18,6 @@
|
||||
# serve to show the default.
|
||||
|
||||
import os
|
||||
import shlex
|
||||
import sys
|
||||
|
||||
# If extensions (or modules to document with autodoc) are in another directory,
|
||||
@ -37,11 +36,13 @@ sys.path.insert(0, os.path.abspath("../scripts"))
|
||||
extensions = [
|
||||
#'sphinx.ext.autodoc',
|
||||
#'sphinx.ext.autosummary',
|
||||
"sphinx.ext.autosectionlabel",
|
||||
"sphinx.ext.intersphinx",
|
||||
"sphinx.ext.todo",
|
||||
"sphinx.ext.mathjax",
|
||||
"sphinx.ext.napoleon",
|
||||
"sphinx.ext.graphviz",
|
||||
"sphinxcontrib.bibtex",
|
||||
#'sphinx.ext.pngmath',
|
||||
#'sphinxcontrib.tikz',
|
||||
#'rinoh.frontend.sphinx',
|
||||
@ -51,6 +52,9 @@ extensions = [
|
||||
autodoc_default_flags = ["members"]
|
||||
autosummary_generate = True
|
||||
|
||||
bibtex_bibfiles = ["publications.bib"]
|
||||
bibtex_default_style = "unsrt"
|
||||
|
||||
# Add any paths that contain templates here, relative to this directory.
|
||||
templates_path = ["_templates"]
|
||||
|
||||
@ -67,8 +71,8 @@ master_doc = "index"
|
||||
|
||||
# General information about the project.
|
||||
project = "PyPSA-Eur"
|
||||
copyright = "2017-2023 Jonas Hoersch (KIT, FIAS), Fabian Hofmann (TUB, FIAS), David Schlachtberger (FIAS), Tom Brown (TUB, KIT, FIAS); 2019-2023 Fabian Neumann (TUB, KIT)"
|
||||
author = "Jonas Hoersch (KIT, FIAS), Fabian Hofmann (TUB, FIAS), David Schlachtberger (FIAS), Tom Brown (TUB, KIT, FIAS), Fabian Neumann (TUB, KIT)"
|
||||
copyright = "2017-2023 Tom Brown (KIT, TUB, FIAS), Jonas Hoersch (KIT, FIAS), Fabian Hofmann (TUB, FIAS), Fabian Neumann (TUB, KIT), Marta Victoria (Aarhus University), Lisa Zeyen (KIT, TUB)"
|
||||
author = "Tom Brown (KIT, TUB, FIAS), Jonas Hoersch (KIT, FIAS), Fabian Hofmann (TUB, FIAS), Fabian Neumann (TUB, KIT), Marta Victoria (Aarhus University), Lisa Zeyen (KIT, TUB)"
|
||||
|
||||
# The version info for the project you're documenting, acts as replacement for
|
||||
# |version| and |release|, also used in various other places throughout the
|
||||
@ -136,7 +140,7 @@ html_theme = "sphinx_book_theme"
|
||||
html_theme_options = {
|
||||
"repository_url": "https://github.com/pypsa/pypsa-eur",
|
||||
"use_repository_button": True,
|
||||
"show_navbar_depth": 2,
|
||||
"show_navbar_depth": 1,
|
||||
}
|
||||
|
||||
|
||||
@ -148,7 +152,7 @@ html_theme_options = {
|
||||
html_title = "PyPSA-Eur"
|
||||
|
||||
# A shorter title for the navigation bar. Default is the same as html_title.
|
||||
# html_short_title = None
|
||||
html_short_title = "PyPSA-Eur"
|
||||
|
||||
# The name of an image file (relative to this directory) to place at the top
|
||||
# of the sidebar.
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
,Unit,Values,Description
|
||||
default_cutout,--,str,"Defines a default cutout."
|
||||
nprocesses,--,int,"Number of parallel processes in cutout preparation"
|
||||
show_progress,bool,true/false,"Whether progressbar for atlite conversion processes should be shown. False saves time."
|
||||
cutouts,,,
|
||||
|
||||
|
3
doc/configtables/conventional.csv
Normal file
3
doc/configtables/conventional.csv
Normal file
@ -0,0 +1,3 @@
|
||||
,Unit,Values,Description
|
||||
{name},--,"string","For any carrier/technology overwrite attributes as listed below."
|
||||
-- {attribute},--,"string or float","For any attribute, can specify a float or reference to a file path to a CSV file giving floats for each country (2-letter code)."
|
||||
|
10
doc/configtables/enable.csv
Normal file
10
doc/configtables/enable.csv
Normal file
@ -0,0 +1,10 @@
|
||||
,Unit,Values,Description
|
||||
prepare_links_p_nom,bool,"{true, false}","Switch to retrieve current HVDC projects from `Wikipedia <https://en.wikipedia.org/wiki/List_of_HVDC_projects>`_"
|
||||
retrieve_databundle,bool,"{true, false}","Switch to retrieve databundle from zenodo via the rule :mod:`retrieve_databundle` or whether to keep a custom databundle located in the corresponding folder."
|
||||
retrieve_sector_databundle,bool,"{true, false}","Switch to retrieve sector databundle from zenodo via the rule :mod:`retrieve_sector_databundle` or whether to keep a custom databundle located in the corresponding folder."
|
||||
retrieve_cost_data,bool,"{true, false}","Switch to retrieve technology cost data from `technology-data repository <https://github.com/PyPSA/technology-data>`_."
|
||||
build_cutout,bool,"{true, false}","Switch to enable the building of cutouts via the rule :mod:`build_cutout`."
|
||||
retrieve_cutout,bool,"{true, false}","Switch to enable the retrieval of cutouts from zenodo with :mod:`retrieve_cutout`."
|
||||
build_natura_raster,bool,"{true, false}","Switch to enable the creation of the raster ``natura.tiff`` via the rule :mod:`build_natura_raster`."
|
||||
retrieve_natura_raster,bool,"{true, false}","Switch to enable the retrieval of ``natura.tiff`` from zenodo with :mod:`retrieve_natura_raster`."
|
||||
custom_busmap,bool,"{true, false}","Switch to enable the use of custom busmaps in rule :mod:`cluster_network`. If activated the rule looks for provided busmaps at ``data/custom_busmap_elec_s{simpl}_{clusters}.csv`` which should have the same format as ``resources/busmap_elec_s{simpl}_{clusters}.csv``, i.e. the index should contain the buses of ``networks/elec_s{simpl}.nc``."
|
||||
|
28
doc/configtables/licenses-sector.csv
Normal file
28
doc/configtables/licenses-sector.csv
Normal file
@ -0,0 +1,28 @@
|
||||
description,file/folder,licence,source
|
||||
JRC IDEES database,jrc-idees-2015/,CC BY 4.0,https://ec.europa.eu/jrc/en/potencia/jrc-idees
|
||||
urban/rural fraction,urban_percent.csv,unknown,unknown
|
||||
JRC biomass potentials,biomass/,unknown,https://doi.org/10.2790/39014
|
||||
JRC ENSPRESO biomass potentials,remote,CC BY 4.0,https://data.jrc.ec.europa.eu/dataset/74ed5a04-7d74-4807-9eab-b94774309d9f
|
||||
EEA emission statistics,eea/UNFCCC_v23.csv,EEA standard re-use policy,https://www.eea.europa.eu/data-and-maps/data/national-emissions-reported-to-the-unfccc-and-to-the-eu-greenhouse-gas-monitoring-mechanism-16
|
||||
Eurostat Energy Balances,eurostat-energy_balances-*/,Eurostat,https://ec.europa.eu/eurostat/web/energy/data/energy-balances
|
||||
Swiss energy statistics from Swiss Federal Office of Energy,switzerland-sfoe/,unknown,http://www.bfe.admin.ch/themen/00526/00541/00542/02167/index.html?dossier_id=02169
|
||||
BASt emobility statistics,emobility/,unknown,http://www.bast.de/DE/Verkehrstechnik/Fachthemen/v2-verkehrszaehlung/Stundenwerte.html?nn=626916
|
||||
BDEW heating profile,heat_load_profile_BDEW.csv,unknown,https://github.com/oemof/demandlib
|
||||
heating profiles for Aarhus,heat_load_profile_DK_AdamJensen.csv,unknown,Adam Jensen MA thesis at Aarhus University
|
||||
George Lavidas wind/wave costs,WindWaveWEC_GLTB.xlsx,unknown,George Lavidas
|
||||
co2 budgets,co2_budget.csv,CC BY 4.0,https://arxiv.org/abs/2004.11009
|
||||
existing heating potentials,existing_infrastructure/existing_heating_raw.csv,unknown,https://ec.europa.eu/energy/studies/mapping-and-analyses-current-and-future-2020-2030-heatingcooling-fuel-deployment_en?redir=1
|
||||
IRENA existing VRE capacities,existing_infrastructure/{solar|onwind|offwind}_capcity_IRENA.csv,unknown,https://www.irena.org/Statistics/Download-Data
|
||||
USGS ammonia production,myb1-2017-nitro.xls,unknown,https://www.usgs.gov/centers/nmic/nitrogen-statistics-and-information
|
||||
hydrogen salt cavern potentials,h2_salt_caverns_GWh_per_sqkm.geojson,CC BY 4.0,https://doi.org/10.1016/j.ijhydene.2019.12.161 https://doi.org/10.20944/preprints201910.0187.v1
|
||||
international port trade volumes,attributed_ports.json,CC BY 4.0,https://datacatalog.worldbank.org/search/dataset/0038118/Global---International-Ports
|
||||
hotmaps industrial site database,Industrial_Database.csv,CC BY 4.0,https://gitlab.com/hotmaps/industrial_sites/industrial_sites_Industrial_Database
|
||||
Hotmaps building stock data,data_building_stock.csv,CC BY 4.0,https://gitlab.com/hotmaps/building-stock
|
||||
U-values Poland,u_values_poland.csv,unknown,https://data.europa.eu/euodp/de/data/dataset/building-stock-observatory
|
||||
Floor area missing in hotmaps building stock data,floor_area_missing.csv,unknown,https://data.europa.eu/euodp/de/data/dataset/building-stock-observatory
|
||||
Comparative level investment,comparative_level_investment.csv,Eurostat,https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Comparative_price_levels_for_investment
|
||||
Electricity taxes,electricity_taxes_eu.csv,Eurostat,https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=nrg_pc_204&lang=en
|
||||
Building topologies and corresponding standard values,tabula-calculator-calcsetbuilding.csv,unknown,https://episcope.eu/fileadmin/tabula/public/calc/tabula-calculator.xlsx
|
||||
Retrofitting thermal envelope costs for Germany,retro_cost_germany.csv,unknown,https://www.iwu.de/forschung/handlungslogiken/kosten-energierelevanter-bau-und-anlagenteile-bei-modernisierung/
|
||||
District heating most countries,jrc-idees-2015/,CC BY 4.0,https://ec.europa.eu/jrc/en/potencia/jrc-idees,,
|
||||
District heating missing countries,district_heat_share.csv,unknown,https://www.euroheat.org/knowledge-hub/country-profiles,,
|
||||
|
Can't render this file because it has a wrong number of fields in line 27.
|
@ -1,10 +1,6 @@
|
||||
,Unit,Values,Description
|
||||
map,,,
|
||||
-- figsize,--,"[width, height]; e.g. [7,7]","Figure size in inches."
|
||||
-- boundaries,°,"[x1,x2,y1,y2]","Boundaries of the map plots in degrees latitude (y) and longitude (x)"
|
||||
-- p_nom,,,
|
||||
-- -- bus_size_factor,--,float,"Factor by which values determining bus sizes are scaled to fit well in the plot."
|
||||
-- -- linewidth_factor,--,float,"Factor by which values determining bus sizes are scaled to fit well in the plot."
|
||||
costs_max,bn Euro,float,"Upper y-axis limit in cost bar plots."
|
||||
costs_threshold,bn Euro,float,"Threshold below which technologies will not be shown in cost bar plots."
|
||||
energy_max,TWh,float,"Upper y-axis limit in energy bar plots."
|
||||
|
||||
|
5
doc/configtables/run.csv
Normal file
5
doc/configtables/run.csv
Normal file
@ -0,0 +1,5 @@
|
||||
,Unit,Values,Description
|
||||
name,--,"any string","Specify a name for your run. Results will be stored under this name."
|
||||
disable_progrssbar,bool,"{true, false}","Switch to select whether progressbar should be disabled."
|
||||
shared_resources,bool,"{true, false}","Switch to select whether resources should be shared across runs."
|
||||
shared_cutouts,bool,"{true, false}","Switch to select whether cutouts should be shared across runs."
|
||||
|
@ -3,3 +3,5 @@ simpl,--,cf. :ref:`simpl`,"List of ``{simpl}`` wildcards to run."
|
||||
clusters,--,cf. :ref:`clusters`,"List of ``{clusters}`` wildcards to run."
|
||||
ll,--,cf. :ref:`ll`,"List of ``{ll}`` wildcards to run."
|
||||
opts,--,cf. :ref:`opts`,"List of ``{opts}`` wildcards to run."
|
||||
sector_opts,--,cf. :ref:`sector_opts`,"List of ``{sector_opts}`` wildcards to run."
|
||||
planning_horizons,--,cf. :ref:`planning_horizons`,"List of ``{planning_horizon}`` wildcards to run."
|
||||
|
||||
|
11
doc/configtables/sector-opts.csv
Normal file
11
doc/configtables/sector-opts.csv
Normal file
@ -0,0 +1,11 @@
|
||||
Trigger, Description, Definition, Status
|
||||
``nH``, i.e. ``2H``-``6H``, Resample the time-resolution by averaging over every ``n`` snapshots, ``prepare_network``: `average_every_nhours() <https://github.com/PyPSA/pypsa-eur/blob/6b964540ed39d44079cdabddee8333f486d0cd63/scripts/prepare_network.py#L110>`_ and its `caller <https://github.com/PyPSA/pypsa-eur/blob/6b964540ed39d44079cdabddee8333f486d0cd63/scripts/prepare_network.py#L146>`__), In active use
|
||||
``Co2L``, Add an overall absolute carbon-dioxide emissions limit configured in ``electricity: co2limit``. If a float is appended an overall emission limit relative to the emission level given in ``electricity: co2base`` is added (e.g. ``Co2L0.05`` limits emissisions to 5% of what is given in ``electricity: co2base``), ``prepare_network``: `add_co2limit() <https://github.com/PyPSA/pypsa-eur/blob/6b964540ed39d44079cdabddee8333f486d0cd63/scripts/prepare_network.py#L19>`_ and its `caller <https://github.com/PyPSA/pypsa-eur/blob/6b964540ed39d44079cdabddee8333f486d0cd63/scripts/prepare_network.py#L154>`__, In active use
|
||||
``carrier+{c|p|m}factor``,"Alter the capital cost (``c``), installable potential (``p``) or marginal costs (``m``) of a carrier by a factor. Example: ``solar+c0.5`` reduces the capital cost of solar to 50\% of original values.", ``prepare_network``, In active use
|
||||
``T``,Add land transport sector,,In active use
|
||||
``H``,Add heating sector,,In active use
|
||||
``B``,Add biomass,,In active use
|
||||
``I``,Add industry sector,,In active use
|
||||
``A``,Add agriculture sector,,In active use
|
||||
``dist``+``n``,Add distribution grid with investment costs of ``n`` times costs in ``data/costs_{cost_year}.csv``,,In active use
|
||||
``seq``+``n``,Sets the CO2 sequestration potential to ``n`` Mt CO2 per year,,In active use
|
||||
|
Can't render this file because it has a wrong number of fields in line 2.
|
@ -1,10 +0,0 @@
|
||||
,Unit,Values,Description
|
||||
formulation,--,"Any of {'angles', 'kirchhoff', 'cycles', 'ptdf'}","Specifies which variant of linearized power flow formulations to use in the optimisation problem. Recommended is 'kirchhoff'. Explained in `this article <https://arxiv.org/abs/1704.01881>`_."
|
||||
load_shedding,bool,"{'true','false'}","Add generators with a prohibitively high marginal cost to simulate load shedding and avoid problem infeasibilities."
|
||||
noisy_costs,bool,"{'true','false'}","Add random noise to marginal cost of generators by :math:`\mathcal{U}(0.009,0,011)` and capital cost of lines and links by :math:`\mathcal{U}(0.09,0,11)`."
|
||||
min_iterations,--,int,"Minimum number of solving iterations in between which resistance and reactence (``x/r``) are updated for branches according to ``s_nom_opt`` of the previous run."
|
||||
max_iterations,--,int,"Maximum number of solving iterations in between which resistance and reactence (``x/r``) are updated for branches according to ``s_nom_opt`` of the previous run."
|
||||
nhours,--,int,"Specifies the :math:`n` first snapshots to take into account. Must be less than the total number of snapshots. Rather recommended only for debugging."
|
||||
clip_p_max_pu,p.u.,float,"To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero."
|
||||
skip_iterations,bool,"{'true','false'}","Skip iterating, do not update impedances of branches. Defaults to true."
|
||||
track_iterations,bool,"{'true','false'}","Flag whether to store the intermediate branch capacities and objective function values are recorded for each iteration in ``network.lines['s_nom_opt_X']`` (where ``X`` labels the iteration)"
|
||||
|
@ -1,3 +0,0 @@
|
||||
,Unit,Values,Description
|
||||
name,--,"One of {'gurobi', 'cplex', 'cbc', 'glpk', 'ipopt'}; potentially more possible","Solver to use for optimisation problems in the workflow; e.g. clustering and linear optimal power flow."
|
||||
opts,--,"Parameter list for `Gurobi <https://www.gurobi.com/documentation/8.1/refman/parameters.html>`_ and `CPLEX <https://www.ibm.com/docs/en/icos/20.1.0?topic=cplex-topical-list-parameters>`_","Solver specific parameter settings."
|
||||
|
17
doc/configtables/solving.csv
Normal file
17
doc/configtables/solving.csv
Normal file
@ -0,0 +1,17 @@
|
||||
,Unit,Values,Description
|
||||
options,,,
|
||||
-- formulation,--,"Any of {'angles', 'kirchhoff', 'cycles', 'ptdf'}","Specifies which variant of linearized power flow formulations to use in the optimisation problem. Recommended is 'kirchhoff'. Explained in `this article <https://arxiv.org/abs/1704.01881>`_."
|
||||
-- load_shedding,bool,"{'true','false'}","Add generators with a prohibitively high marginal cost to simulate load shedding and avoid problem infeasibilities."
|
||||
-- noisy_costs,bool,"{'true','false'}","Add random noise to marginal cost of generators by :math:`\mathcal{U}(0.009,0,011)` and capital cost of lines and links by :math:`\mathcal{U}(0.09,0,11)`."
|
||||
-- min_iterations,--,int,"Minimum number of solving iterations in between which resistance and reactence (``x/r``) are updated for branches according to ``s_nom_opt`` of the previous run."
|
||||
-- max_iterations,--,int,"Maximum number of solving iterations in between which resistance and reactence (``x/r``) are updated for branches according to ``s_nom_opt`` of the previous run."
|
||||
-- nhours,--,int,"Specifies the :math:`n` first snapshots to take into account. Must be less than the total number of snapshots. Rather recommended only for debugging."
|
||||
-- clip_p_max_pu,p.u.,float,"To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero."
|
||||
-- skip_iterations,bool,"{'true','false'}","Skip iterating, do not update impedances of branches. Defaults to true."
|
||||
-- track_iterations,bool,"{'true','false'}","Flag whether to store the intermediate branch capacities and objective function values are recorded for each iteration in ``network.lines['s_nom_opt_X']`` (where ``X`` labels the iteration)"
|
||||
-- seed,--,int,"Random seed for increased deterministic behaviour."
|
||||
solver,,,
|
||||
-- name,--,"One of {'gurobi', 'cplex', 'cbc', 'glpk', 'ipopt'}; potentially more possible","Solver to use for optimisation problems in the workflow; e.g. clustering and linear optimal power flow."
|
||||
-- options,--,"Key listed under ``solver_options``.","Link to specific parameter settings."
|
||||
solver_options,,"dict","Dictionaries with solver-specific parameter settings."
|
||||
mem,MB,"int","Estimated maximum memory requirement for solving networks."
|
||||
|
@ -4,17 +4,7 @@ tutorial,bool,"{true, false}","Switch to retrieve the tutorial data set instead
|
||||
logging,,,
|
||||
-- level,--,"Any of {'INFO', 'WARNING', 'ERROR'}","Restrict console outputs to all infos, warning or errors only"
|
||||
-- format,--,"","Custom format for log messages. See `LogRecord <https://docs.python.org/3/library/logging.html#logging.LogRecord>`_ attributes."
|
||||
run,,,
|
||||
-- name,--,"any string","Specify a name for your run. Results will be stored under this name."
|
||||
-- shared_cutouts,bool,"{true, false}","Switch to select whether cutouts should be shared across runs."
|
||||
foresight,string,"{overnight, myopic, perfect}","Defaults to overnight scenarios."
|
||||
countries,--,"Subset of {'AL', 'AT', 'BA', 'BE', 'BG', 'CH', 'CZ', 'DE', 'DK', 'EE', 'ES', 'FI', 'FR', 'GB', 'GR', 'HR', 'HU', 'IE', 'IT', 'LT', 'LU', 'LV', 'ME', 'MK', 'NL', 'NO', 'PL', 'PT', 'RO', 'RS', 'SE', 'SI', 'SK'}","European countries defined by their `Two-letter country codes (ISO 3166-1) <https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2>`_ which should be included in the energy system model."
|
||||
focus_weights,--,"Keys should be two-digit country codes (e.g. DE) and values should range between 0 and 1","Ratio of total clusters for particular countries. the remaining weight is distributed according to mean load. An example: ``focus_weights: 'DE': 0.6 'FR': 0.2``."
|
||||
enable,,,
|
||||
-- prepare_links_p_nom,bool,"{true, false}","Switch to retrieve current HVDC projects from `Wikipedia <https://en.wikipedia.org/wiki/List_of_HVDC_projects>`_"
|
||||
-- retrieve_databundle,bool,"{true, false}","Switch to retrieve databundle from zenodo via the rule :mod:`retrieve_databundle` or whether to keep a custom databundle located in the corresponding folder."
|
||||
-- retrieve_cost_data,bool,"{true, false}","Switch to retrieve technology cost data from `technology-data repository <https://github.com/PyPSA/technology-data>`_."
|
||||
-- build_cutout,bool,"{true, false}","Switch to enable the building of cutouts via the rule :mod:`build_cutout`."
|
||||
-- retrieve_cutout,bool,"{true, false}","Switch to enable the retrieval of cutouts from zenodo with :mod:`retrieve_cutout`."
|
||||
-- build_natura_raster,bool,"{true, false}","Switch to enable the creation of the raster ``natura.tiff`` via the rule :mod:`build_natura_raster`."
|
||||
-- retrieve_natura_raster,bool,"{true, false}","Switch to enable the retrieval of ``natura.tiff`` from zenodo with :mod:`retrieve_natura_raster`."
|
||||
-- custom_busmap,bool,"{true, false}","Switch to enable the use of custom busmaps in rule :mod:`cluster_network`. If activated the rule looks for provided busmaps at ``data/custom_busmap_elec_s{simpl}_{clusters}.csv`` which should have the same format as ``resources/busmap_elec_s{simpl}_{clusters}.csv``, i.e. the index should contain the buses of ``networks/elec_s{simpl}.nc``."
|
||||
co2_budget,--,"Dictionary with planning horizons as keys.","CO2 budget as a fraction of 1990 emissions. Overwritten if ``CO2Lx`` or ``cb`` are set in ``{sector_opts}`` wildcard"
|
||||
|
||||
|
@ -18,7 +18,7 @@ Top-level configuration
|
||||
|
||||
.. literalinclude:: ../config.default.yaml
|
||||
:language: yaml
|
||||
:lines: 5-11,23,30-38
|
||||
:lines: 5-11,18-19,62,80-90
|
||||
|
||||
|
||||
.. csv-table::
|
||||
@ -40,8 +40,12 @@ The ``run`` section is used for running and storing scenarios with different con
|
||||
.. literalinclude:: ../config.default.yaml
|
||||
:language: yaml
|
||||
:start-at: run:
|
||||
:end-before: scenario:
|
||||
:end-before: foresight:
|
||||
|
||||
.. csv-table::
|
||||
:header-rows: 1
|
||||
:widths: 25,7,22,30
|
||||
:file: configtables/run.csv
|
||||
|
||||
``scenario``
|
||||
============
|
||||
@ -52,9 +56,21 @@ facilitate running multiple scenarios through a single command
|
||||
|
||||
.. code:: bash
|
||||
|
||||
snakemake -call solve_all_networks
|
||||
# for electricity-only studies
|
||||
snakemake -call solve_elec_networks
|
||||
|
||||
For each wildcard, a **list of values** is provided. The rule ``solve_all_networks`` will trigger the rules for creating ``results/networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc`` for **all combinations** of the provided wildcard values as defined by Python's `itertools.product(...) <https://docs.python.org/2/library/itertools.html#itertools.product>`_ function that snakemake's `expand(...) function <https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#targets>`_ uses.
|
||||
# for sector-coupling studies
|
||||
snakemake -call solve_sector_networks
|
||||
|
||||
For each wildcard, a **list of values** is provided. The rule
|
||||
``solve_all_elec_networks`` will trigger the rules for creating
|
||||
``results/networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc`` for **all
|
||||
combinations** of the provided wildcard values as defined by Python's
|
||||
`itertools.product(...)
|
||||
<https://docs.python.org/2/library/itertools.html#itertools.product>`_ function
|
||||
that snakemake's `expand(...) function
|
||||
<https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#targets>`_
|
||||
uses.
|
||||
|
||||
An exemplary dependency graph (starting from the simplification rules) then looks like this:
|
||||
|
||||
@ -87,6 +103,23 @@ Specifies the temporal range to build an energy system model for as arguments to
|
||||
:widths: 25,7,22,30
|
||||
:file: configtables/snapshots.csv
|
||||
|
||||
.. _enable_cf:
|
||||
|
||||
``enable``
|
||||
==========
|
||||
|
||||
Switches for some rules and optional features.
|
||||
|
||||
.. literalinclude:: ../config.default.yaml
|
||||
:language: yaml
|
||||
:start-at: enable:
|
||||
:end-before: co2_budget:
|
||||
|
||||
.. csv-table::
|
||||
:header-rows: 1
|
||||
:widths: 25,7,22,30
|
||||
:file: configtables/enable.csv
|
||||
|
||||
.. _electricity_cf:
|
||||
|
||||
``electricity``
|
||||
@ -194,13 +227,22 @@ Define and specify the ``atlite.Cutout`` used for calculating renewable potentia
|
||||
``conventional``
|
||||
================
|
||||
|
||||
Define additional generator attribute for conventional carrier types. If a scalar value is given it is applied to all generators. However if a string starting with "data/" is given, the value is interpreted as a path to a csv file with country specific values. Then, the values are read in and applied to all generators of the given carrier in the given country. Note that the value(s) overwrite the existing values in the corresponding section of the ``generators`` dataframe.
|
||||
Define additional generator attribute for conventional carrier types. If a
|
||||
scalar value is given it is applied to all generators. However if a string
|
||||
starting with "data/" is given, the value is interpreted as a path to a csv file
|
||||
with country specific values. Then, the values are read in and applied to all
|
||||
generators of the given carrier in the given country. Note that the value(s)
|
||||
overwrite the existing values.
|
||||
|
||||
.. literalinclude:: ../config.default.yaml
|
||||
:language: yaml
|
||||
:start-at: conventional:
|
||||
:end-before: lines:
|
||||
|
||||
.. csv-table::
|
||||
:header-rows: 1
|
||||
:widths: 25,7,22,30
|
||||
:file: configtables/conventional.csv
|
||||
|
||||
``lines``
|
||||
=============
|
||||
@ -252,8 +294,8 @@ Define additional generator attribute for conventional carrier types. If a scala
|
||||
|
||||
.. literalinclude:: ../config.default.yaml
|
||||
:language: yaml
|
||||
:start-at: load:
|
||||
:end-before: costs:
|
||||
:start-after: type:
|
||||
:end-at: scaling_factor:
|
||||
|
||||
.. csv-table::
|
||||
:header-rows: 1
|
||||
@ -267,7 +309,7 @@ Define additional generator attribute for conventional carrier types. If a scala
|
||||
|
||||
.. literalinclude:: ../config.default.yaml
|
||||
:language: yaml
|
||||
:start-after: scaling_factor:
|
||||
:start-at: costs:
|
||||
:end-before: clustering:
|
||||
|
||||
.. csv-table::
|
||||
@ -275,10 +317,6 @@ Define additional generator attribute for conventional carrier types. If a scala
|
||||
:widths: 25,7,22,30
|
||||
:file: configtables/costs.csv
|
||||
|
||||
.. note::
|
||||
To change cost assumptions in more detail (i.e. other than ``marginal_cost`` and ``capital_cost``), consider modifying cost assumptions directly in ``resources/costs.csv`` as this is not yet supported through the config file.
|
||||
You can also build multiple different cost databases. Make a renamed copy of ``resources/costs.csv`` (e.g. ``data/costs-optimistic.csv``) and set the variable ``COSTS=data/costs-optimistic.csv`` in the ``Snakefile``.
|
||||
|
||||
|
||||
.. _clustering_cf:
|
||||
|
||||
@ -287,7 +325,7 @@ Define additional generator attribute for conventional carrier types. If a scala
|
||||
|
||||
.. literalinclude:: ../config.default.yaml
|
||||
:language: yaml
|
||||
:start-after: co2:
|
||||
:start-at: clustering:
|
||||
:end-before: solving:
|
||||
|
||||
.. csv-table::
|
||||
@ -296,42 +334,131 @@ Define additional generator attribute for conventional carrier types. If a scala
|
||||
:file: configtables/clustering.csv
|
||||
|
||||
|
||||
.. _energy_cf:
|
||||
|
||||
``energy``
|
||||
=======================
|
||||
|
||||
.. note::
|
||||
Only used for sector-coupling studies.
|
||||
|
||||
.. warning::
|
||||
More comprehensive documentation for this segment will be released soon.
|
||||
|
||||
.. literalinclude:: ../config.default.yaml
|
||||
:language: yaml
|
||||
:start-at: energy:
|
||||
:end-before: biomass:
|
||||
|
||||
|
||||
.. _biomass_cf:
|
||||
|
||||
``biomass``
|
||||
=======================
|
||||
|
||||
.. note::
|
||||
Only used for sector-coupling studies.
|
||||
|
||||
.. warning::
|
||||
More comprehensive documentation for this segment will be released soon.
|
||||
|
||||
.. literalinclude:: ../config.default.yaml
|
||||
:language: yaml
|
||||
:start-at: biomass:
|
||||
:end-before: solar_thermal:
|
||||
|
||||
.. _solar_thermal_cf:
|
||||
|
||||
``solar_thermal``
|
||||
=======================
|
||||
|
||||
.. note::
|
||||
Only used for sector-coupling studies.
|
||||
|
||||
.. warning::
|
||||
More comprehensive documentation for this segment will be released soon.
|
||||
|
||||
.. literalinclude:: ../config.default.yaml
|
||||
:language: yaml
|
||||
:start-at: solar_thermal:
|
||||
:end-before: existing_capacities:
|
||||
|
||||
.. _existing_capacities_cf:
|
||||
|
||||
``existing_capacities``
|
||||
=======================
|
||||
|
||||
.. note::
|
||||
Only used for sector-coupling studies.
|
||||
|
||||
.. warning::
|
||||
More comprehensive documentation for this segment will be released soon.
|
||||
|
||||
.. literalinclude:: ../config.default.yaml
|
||||
:language: yaml
|
||||
:start-at: existing_capacities:
|
||||
:end-before: sector:
|
||||
|
||||
.. _sector_cf:
|
||||
|
||||
``sector``
|
||||
=======================
|
||||
|
||||
.. note::
|
||||
Only used for sector-coupling studies.
|
||||
|
||||
.. warning::
|
||||
More comprehensive documentation for this segment will be released soon.
|
||||
|
||||
.. literalinclude:: ../config.default.yaml
|
||||
:language: yaml
|
||||
:start-at: sector:
|
||||
:end-before: industry:
|
||||
|
||||
.. _industry_cf:
|
||||
|
||||
``industry``
|
||||
=======================
|
||||
|
||||
.. note::
|
||||
Only used for sector-coupling studies.
|
||||
|
||||
.. warning::
|
||||
More comprehensive documentation for this segment will be released soon.
|
||||
|
||||
.. literalinclude:: ../config.default.yaml
|
||||
:language: yaml
|
||||
:start-at: industry:
|
||||
:end-before: costs:
|
||||
|
||||
.. _solving_cf:
|
||||
|
||||
``solving``
|
||||
=============
|
||||
|
||||
``options``
|
||||
-----------
|
||||
|
||||
.. literalinclude:: ../config.default.yaml
|
||||
:language: yaml
|
||||
:start-at: solving:
|
||||
:end-before: solver:
|
||||
|
||||
.. csv-table::
|
||||
:header-rows: 1
|
||||
:widths: 25,7,22,30
|
||||
:file: configtables/solving-options.csv
|
||||
|
||||
``solver``
|
||||
----------
|
||||
|
||||
.. literalinclude:: ../config.default.yaml
|
||||
:language: yaml
|
||||
:start-at: solver:
|
||||
:end-before: plotting:
|
||||
|
||||
.. csv-table::
|
||||
:header-rows: 1
|
||||
:widths: 25,7,22,30
|
||||
:file: configtables/solving-solver.csv
|
||||
:file: configtables/solving.csv
|
||||
|
||||
.. csv-table::
|
||||
:header-rows: 1
|
||||
:widths: 25,7,22,30
|
||||
:file: configtables/solving.csv
|
||||
|
||||
.. _plotting_cf:
|
||||
|
||||
``plotting``
|
||||
=============
|
||||
|
||||
.. warning::
|
||||
More comprehensive documentation for this segment will be released soon.
|
||||
|
||||
.. literalinclude:: ../config.default.yaml
|
||||
:language: yaml
|
||||
:start-at: plotting:
|
||||
|
||||
@ -21,16 +21,17 @@ For linting, formatting and checking your code contributions
|
||||
against our guidelines (e.g. we use `Black <https://github.com/psf/black>`_ as code style
|
||||
use `pre-commit <https://pre-commit.com/index.html>`_:
|
||||
|
||||
1. Installation ``conda install -c conda-forge pre-commit`` or ``pip install pre-commit``
|
||||
1. Installation ``mamba install -c conda-forge pre-commit`` or ``pip install pre-commit``
|
||||
2. Usage:
|
||||
* To automatically activate ``pre-commit`` on every ``git commit``: Run ``pre-commit install``
|
||||
* To manually run it: ``pre-commit run --all``
|
||||
|
||||
Note that installing `pre-commit` locally is not strictly necessary. If you create a Pull Request the `pre-commit CI` will be triggered automatically and take care of the checks.
|
||||
.. note::
|
||||
Note that installing ``pre-commit`` locally is not strictly necessary. If you create a Pull Request the ``pre-commit CI`` will be triggered automatically and take care of the checks.
|
||||
|
||||
For all code contributions we follow the four eyes principle (two person principle), i.e. all suggested code
|
||||
including our own are reviewed by a second person before they are incorporated into our repository.
|
||||
|
||||
If you are unfamiliar with pull requests, the GitHub help pages have a nice `guide <https://help.github.com/en/articles/about-pull-requests>`_.
|
||||
|
||||
To ask and answer general usage questions, join the `PyPSA and PyPSA-Eur mailing list <https://groups.google.com/forum/#!forum/pypsa>`_.
|
||||
To ask and answer general usage questions, join the `PyPSA mailing list <https://groups.google.com/forum/#!forum/pypsa>`_.
|
||||
|
||||
@ -3,18 +3,22 @@
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
##################
|
||||
Cost Assumptions
|
||||
##################
|
||||
############################
|
||||
Techno-Economic Assumptions
|
||||
############################
|
||||
|
||||
The database of cost assumptions is retrieved from the repository
|
||||
`PyPSA/technology-data <https://github.com/pypsa/technology-data>`_ and then
|
||||
saved to ``resources/costs.csv``.
|
||||
saved to a file ``data/costs_{year}.csv``. The ``config.yaml`` provides options
|
||||
to choose a reference year and use a specific version of the repository.
|
||||
|
||||
The ``config.yaml`` provides options to choose a reference year (``costs: year:``) and use a specific version of the repository ``costs: version:``.
|
||||
.. literalinclude:: ../config.default.yaml
|
||||
:language: yaml
|
||||
:start-at: costs:
|
||||
:end-at: version:
|
||||
|
||||
It includes cost assumptions for all included technologies for specific
|
||||
years from various sources, namely for
|
||||
The file includes cost assumptions for all included technologies for specific
|
||||
years compiled from various sources, namely for
|
||||
|
||||
- discount rate,
|
||||
- lifetime,
|
||||
@ -25,6 +29,10 @@ years from various sources, namely for
|
||||
- efficiency, and
|
||||
- carbon-dioxide intensity.
|
||||
|
||||
Many values are taken from a database published by the Danish Energy Agency (`DEA
|
||||
<https://ens.dk/en/our-services/projections-and-models/technology-data>`_).
|
||||
|
||||
|
||||
The given overnight capital costs are annualised to net present costs
|
||||
with a discount rate of :math:`r` over the economic lifetime :math:`n` using the annuity factor
|
||||
|
||||
@ -32,14 +40,18 @@ with a discount rate of :math:`r` over the economic lifetime :math:`n` using the
|
||||
|
||||
a = \frac{1-(1+r)^{-n}}{r}.
|
||||
|
||||
Based on the parameters above the ``marginal_cost`` and ``capital_cost`` of the system components are calculated.
|
||||
Based on the parameters above the ``marginal_cost`` and ``capital_cost`` of the
|
||||
system components are automatically calculated.
|
||||
|
||||
|
||||
Modifying Cost Assumptions
|
||||
==========================
|
||||
Modifying Assumptions
|
||||
=====================
|
||||
|
||||
Some cost assumptions (e.g. marginal cost and capital cost) can be directly overwritten in the ``config.yaml`` (cf. Section :ref:`costs_cf` in :ref:`config`).
|
||||
Some cost assumptions (e.g. marginal cost and capital cost) can be directly
|
||||
set in the ``config.yaml`` (cf. Section :ref:`costs_cf` in
|
||||
:ref:`config`). To change cost assumptions in more detail, make a copy of
|
||||
``data/costs_{year}.csv`` and reference the new cost file in the ``Snakefile``:
|
||||
|
||||
To change cost assumptions in more detail, modify cost assumptions directly in ``resources/costs.csv`` as this is not yet supported through the config file.
|
||||
|
||||
You can also build multiple different cost databases. Make a renamed copy of ``resources/costs.csv`` (e.g. ``data/costs-optimistic.csv``) and set the variable ``COSTS=data/costs-optimistic.csv`` in the ``Snakefile``.
|
||||
.. literalinclude:: ../Snakefile
|
||||
:start-at: COSTS
|
||||
:end-at: COSTS
|
||||
|
||||
271
doc/foresight.rst
Normal file
271
doc/foresight.rst
Normal file
@ -0,0 +1,271 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2021-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _foresight:
|
||||
|
||||
#####################
|
||||
Foresight Options
|
||||
#####################
|
||||
|
||||
.. _overnight:
|
||||
|
||||
Overnight (greenfield) scenarios
|
||||
================================
|
||||
|
||||
The default is to calculate a rebuilding of the energy system to meet demand, a so-called overnight or greenfield approach.
|
||||
|
||||
In this case, the ``planning_horizons`` parameter specifies the reference year for exogenously given transition paths (e.g. the level of steel recycling).
|
||||
It does not affect the year for cost and technology assumptions, which is set separately in the config.
|
||||
|
||||
.. code:: yaml
|
||||
|
||||
scenario:
|
||||
planning_horizons:
|
||||
- 2050
|
||||
|
||||
costs:
|
||||
year: 2030
|
||||
|
||||
For running overnight scenarios, use in the ``config.yaml``:
|
||||
|
||||
.. code:: yaml
|
||||
|
||||
foresight: overnight
|
||||
|
||||
.. _perfect:
|
||||
|
||||
Perfect foresight scenarios
|
||||
===========================
|
||||
|
||||
.. warning::
|
||||
|
||||
Perfect foresight is currently under development and not yet implemented.
|
||||
|
||||
For running perfect foresight scenarios, in future versions you will be able to
|
||||
set in the ``config.yaml``:
|
||||
|
||||
.. code:: yaml
|
||||
|
||||
foresight: perfect
|
||||
|
||||
|
||||
.. _myopic:
|
||||
|
||||
Myopic foresight scenarios
|
||||
=============================
|
||||
|
||||
The myopic code can be used to investigate progressive changes in a network, for
|
||||
instance, those taking place throughout a transition path. The capacities
|
||||
installed in a certain time step are maintained in the network until their
|
||||
operational lifetime expires.
|
||||
|
||||
The myopic approach was initially developed and used in the paper `Early
|
||||
decarbonisation of the European Energy system pays off (2020)
|
||||
<https://www.nature.com/articles/s41467-020-20015-4>`__ and later further
|
||||
extended in `Speed of technological transformations required in Europe to
|
||||
achieve different climate goals (2022)
|
||||
<https://doi.org/10.1016/j.joule.2022.04.016>`__. The current implementation
|
||||
complies with the PyPSA-Eur-Sec standard working flow and is compatible with
|
||||
using the higher resolution electricity transmission model `PyPSA-Eur
|
||||
<https://github.com/PyPSA/pypsa-eur>`__ rather than a one-node-per-country
|
||||
model.
|
||||
|
||||
The current code applies the myopic approach to generators, storage technologies
|
||||
and links in the power sector. It furthermore applies it to the space and water
|
||||
heating sector (e.g., the share of district heating and reduced space heat
|
||||
demand), industry processes (e.g., steel, direct reduced iron, and aluminum
|
||||
production via primary route), the share of fuel cell and battery electric
|
||||
vehicles in land transport, and the hydrogen share in shipping (see
|
||||
:doc:`supply_demand` for further information).
|
||||
|
||||
The following subjects within the land transport and biomass currently do not
|
||||
evolve with the myopic approach:
|
||||
|
||||
- The percentage of electric vehicles that allow demand-side management and
|
||||
vehicle-to-grid services.
|
||||
|
||||
- The annual biomass potential (default year and scenario for which potential is
|
||||
taken is 2030, defined `here
|
||||
<https://github.com/PyPSA/pypsa-eur-sec/blob/413254e241fb37f55b41caba7264644805ad8e97/config.default.yaml#L109>`_)
|
||||
|
||||
|
||||
Configuration
|
||||
--------------
|
||||
|
||||
For running myopic foresight transition scenarios, set in ``config.yaml``:
|
||||
|
||||
.. code:: yaml
|
||||
|
||||
foresight: myopic
|
||||
|
||||
The following options included in the config.yaml file are relevant for the
|
||||
myopic code.
|
||||
|
||||
The ``{planning_horizons}`` wildcard indicates the year in which the network is
|
||||
optimized. For a myopic optimization, this is equivalent to the investment year.
|
||||
To set the investment years which are sequentially simulated for the myopic
|
||||
investment planning, select for example:
|
||||
|
||||
.. literalinclude:: ../test/config.myopic.yaml
|
||||
:language: yaml
|
||||
:start-at: planning_horizons:
|
||||
:end-before: countries:
|
||||
|
||||
|
||||
**existing capacities**
|
||||
|
||||
Grouping years indicates the bins limits for grouping the existing capacities of
|
||||
different technologies. Note that separate bins are defined for the power and
|
||||
heating plants due to different data sources.
|
||||
|
||||
``grouping_years_power: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020,
|
||||
2025, 2030]``
|
||||
|
||||
``grouping_years_heat: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2019]``
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
**threshold capacity**
|
||||
|
||||
If for a technology, node, and grouping bin, the capacity is lower than
|
||||
threshold_capacity, it is ignored.
|
||||
|
||||
``threshold_capacity: 10``
|
||||
|
||||
|
||||
|
||||
|
||||
**conventional carriers**
|
||||
|
||||
Conventional carriers indicate carriers used in the existing conventional
|
||||
technologies.
|
||||
|
||||
conventional_carriers:
|
||||
|
||||
\- lignite
|
||||
|
||||
\- coal
|
||||
|
||||
\- oil
|
||||
|
||||
\- uranium
|
||||
|
||||
|
||||
|
||||
|
||||
Options
|
||||
--------------
|
||||
|
||||
The total carbon budget for the entire transition path can be indicated in the
|
||||
`sector_opts
|
||||
<https://github.com/PyPSA/pypsa-eur-sec/blob/f13902510010b734c510c38c4cae99356f683058/config.default.yaml#L25>`_
|
||||
in ``config.yaml``. The carbon budget can be split among the
|
||||
``planning_horizons`` following an exponential or beta decay. E.g. ``'cb40ex0'``
|
||||
splits a carbon budget equal to 40 Gt :math:`_{CO_2}` following an exponential
|
||||
decay whose initial linear growth rate r is zero. They can also follow some
|
||||
user-specified path, if defined `here
|
||||
<https://github.com/PyPSA/pypsa-eur-sec/blob/413254e241fb37f55b41caba7264644805ad8e97/config.default.yaml#L56>`_.
|
||||
The paper `Speed of technological transformations required in Europe to achieve
|
||||
different climate goals (2022) <https://doi.org/10.1016/j.joule.2022.04.016>`__
|
||||
defines CO_2 budgets corresponding to global temperature increases (1.5C – 2C)
|
||||
as response to the emissions. Here, global carbon budgets are converted to
|
||||
European budgets assuming equal-per capita distribution which translates into a
|
||||
6.43% share for Europe. The carbon budgets are in this paper distributed
|
||||
throughout the transition paths assuming an exponential decay. Emissions e(t) in
|
||||
every year t are limited by
|
||||
|
||||
.. math::
|
||||
e(t) = e_0 (1+ (r+m)t) e^{-mt}
|
||||
|
||||
where r is the initial linear growth rate, which here is assumed to be r=0, and
|
||||
the decay parameter m is determined by imposing the integral of the path to be
|
||||
equal to the budget for Europe. Following this approach, the CO_2 budget is
|
||||
defined. Following the same approach as in this paper, add the following to the
|
||||
``scenario.sector_opts`` E.g. ``-cb25.7ex0`` (1.5C increase) Or ``cb73.9ex0``
|
||||
(2C increase). See details in Supplemental Note S1 `Speed of technological
|
||||
transformations required in Europe to achieve different climate goals (2022)
|
||||
<https://doi.org/10.1016/j.joule.2022.04.016>`__.
|
||||
|
||||
|
||||
General myopic code structure
|
||||
---------------------------------
|
||||
|
||||
The myopic code solves the network for the time steps included in
|
||||
``planning_horizons`` in a recursive loop, so that:
|
||||
|
||||
1. The existing capacities (those installed before the base year are added as
|
||||
fixed capacities with p_nom=value, p_nom_extendable=False). E.g. for
|
||||
baseyear=2020, capacities installed before 2020 are added. In addition, the
|
||||
network comprises additional generator, storage, and link capacities with
|
||||
p_nom_extendable=True. The non-solved network is saved in
|
||||
``results/run_name/networks/prenetworks-brownfield``.
|
||||
The base year is the first element in ``planning_horizons``. Step 1 is
|
||||
implemented with the rule add_baseyear for the base year and with the rule
|
||||
add_brownfield for the remaining planning_horizons.
|
||||
|
||||
2. The 2020 network is optimized. The solved network is saved in
|
||||
``results/run_name/networks/postnetworks``
|
||||
|
||||
3. For the next planning horizon, e.g. 2030, the capacities from a previous time
|
||||
step are added if they are still in operation (i.e., if they fulfil planning
|
||||
horizon <= commissioned year + lifetime). In addition, the network comprises
|
||||
additional generator, storage, and link capacities with
|
||||
p_nom_extendable=True. The non-solved network is saved in
|
||||
``results/run_name/networks/prenetworks-brownfield``.
|
||||
|
||||
Steps 2 and 3 are solved recursively for all the planning_horizons included in
|
||||
``config.yaml``.
|
||||
|
||||
Rule overview
|
||||
--------------
|
||||
|
||||
- rule add_existing baseyear
|
||||
|
||||
The rule add_existing_baseyear loads the network in
|
||||
‘results/run_name/networks/prenetworks’ and performs the following operations:
|
||||
|
||||
1. Add the conventional, wind and solar power generators that were installed
|
||||
before the base year.
|
||||
|
||||
2. Add the heating capacities that were installed before the base year.
|
||||
|
||||
The existing conventional generators are retrieved from the `powerplants.csv
|
||||
file
|
||||
<https://pypsa-eur.readthedocs.io/en/latest/preparation/build_powerplants.html?highlight=powerplants>`__
|
||||
generated by pypsa-eur which, in turn, is based on the `powerplantmatching
|
||||
<https://github.com/FRESNA/powerplantmatching>`__ database.
|
||||
|
||||
Existing wind and solar capacities are retrieved from `IRENA annual statistics
|
||||
<https://www.irena.org/Statistics/Download-Data>`__ and distributed among the
|
||||
nodes in a country proportional to capacity factor. (This will be updated to
|
||||
include capacity distributions closer to reality.)
|
||||
|
||||
Existing heating capacities are retrieved from the report `Mapping and
|
||||
analyses of the current and future (2020 - 2030) heating/cooling fuel
|
||||
deployment (fossil/renewables)
|
||||
<https://ec.europa.eu/energy/studies/mapping-and-analyses-current-and-future-2020-2030-heatingcooling-fuel-deployment_en?redir=1>`__.
|
||||
|
||||
The heating capacities are assumed to have a lifetime indicated by the
|
||||
parameter lifetime in the configuration file, e.g 25 years. They are assumed
|
||||
to be decommissioned linearly starting on the base year, e.g., from 2020 to
|
||||
2045.
|
||||
|
||||
Then, the resulting network is saved in
|
||||
``results/run_name/networks/prenetworks-brownfield``.
|
||||
|
||||
- rule add_brownfield
|
||||
|
||||
The rule add_brownfield loads the network in
|
||||
``results/run_name/networks/prenetworks`` and performs the following
|
||||
operation:
|
||||
|
||||
1. Read the capacities optimized in the previous time step and add them to the
|
||||
network if they are still in operation (i.e., if they fulfill planning
|
||||
horizon < commissioned year + lifetime)
|
||||
|
||||
Then, the resulting network is saved in
|
||||
``results/run_name/networks/prenetworks_brownfield``.
|
||||
BIN
doc/img/intro-workflow.png
Normal file
BIN
doc/img/intro-workflow.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 200 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 206 KiB |
304
doc/index.rst
304
doc/index.rst
@ -3,8 +3,9 @@
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
PyPSA-Eur: An Open Optimisation Model of the European Transmission System
|
||||
=========================================================================
|
||||
##################################################################################
|
||||
PyPSA-Eur: A Sector-Coupled Open Optimisation Model of the European Energy System
|
||||
##################################################################################
|
||||
|
||||
.. image:: https://img.shields.io/github/v/release/pypsa/pypsa-eur?include_prereleases
|
||||
:alt: GitHub release (latest by date including pre-releases)
|
||||
@ -14,7 +15,7 @@ PyPSA-Eur: An Open Optimisation Model of the European Transmission System
|
||||
|
||||
.. image:: https://readthedocs.org/projects/pypsa-eur/badge/?version=latest
|
||||
:target: https://pypsa-eur.readthedocs.io/en/latest/?badge=latest
|
||||
:alt: Documentation Status
|
||||
:alt: Documentation
|
||||
|
||||
.. image:: https://img.shields.io/github/repo-size/pypsa/pypsa-eur
|
||||
:alt: GitHub repo size
|
||||
@ -22,35 +23,103 @@ PyPSA-Eur: An Open Optimisation Model of the European Transmission System
|
||||
.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3520874.svg
|
||||
:target: https://doi.org/10.5281/zenodo.3520874
|
||||
|
||||
.. image:: https://img.shields.io/badge/snakemake-≥5.0.0-brightgreen.svg?style=flat
|
||||
.. image:: https://img.shields.io/badge/snakemake-≥7.19-brightgreen.svg?style=flat
|
||||
:target: https://snakemake.readthedocs.io
|
||||
:alt: Snakemake
|
||||
|
||||
.. image:: https://api.reuse.software/badge/github.com/pypsa/pypsa-eur
|
||||
:target: https://api.reuse.software/info/github.com/pypsa/pypsa-eur
|
||||
:alt: REUSE status
|
||||
:alt: REUSE
|
||||
|
||||
PyPSA-Eur is an open model dataset of the European power system at the
|
||||
transmission network level that covers the full ENTSO-E area.
|
||||
|
|
||||
|
||||
It contains alternating current lines at and above 220 kV voltage level and all high voltage direct current lines, substations, an open database of conventional power plants, time series for electrical demand and variable renewable generator availability, and geographic potentials for the expansion of wind and solar power.
|
||||
PyPSA-Eur is an open model dataset of the European energy system at the
|
||||
transmission network level that covers the full ENTSO-E area. It covers demand
|
||||
and supply for all energy sectors. From version v0.8.0, PyPSA-Eur includes all
|
||||
the features from PyPSA-Eur-Sec, which is now deprecated.
|
||||
|
||||
The model is suitable both for operational studies and generation and transmission expansion planning studies. The continental scope and highly resolved spatial scale enables a proper description of the long-range smoothing effects for renewable power generation and their varying resource availability.
|
||||
Electricity System
|
||||
==================
|
||||
|
||||
The electricity system representation contains alternating current lines at
|
||||
and above 220 kV voltage level and all high voltage direct current lines,
|
||||
substations, an open database of conventional power plants, time series for
|
||||
electrical demand and variable renewable generator availability, geographic
|
||||
potentials for the expansion of wind and solar power.
|
||||
|
||||
The model is suitable both for operational studies and generation and
|
||||
transmission expansion planning studies. The continental scope and highly
|
||||
resolved spatial scale enables a proper description of the long-range smoothing
|
||||
effects for renewable power generation and their varying resource availability.
|
||||
|
||||
.. image:: img/elec.png
|
||||
:width: 50%
|
||||
:width: 70%
|
||||
:align: center
|
||||
|
||||
The restriction to freely available and open data encourages the open exchange of model data developments and eases the comparison of model results. It provides a full, automated software pipeline to assemble the load-flow-ready model from the original datasets, which enables easy replacement and improvement of the individual parts.
|
||||
|
|
||||
|
||||
PyPSA-Eur is designed to be imported into the open toolbox `PyPSA <https://www.pypsa.org>`_ for which `documentation <https://pypsa.org/doc>`_ is available as well.
|
||||
Sector-Coupled Energy System
|
||||
============================
|
||||
|
||||
A sector-coupled extension (previously known as **PyPSA-Eur-Sec**, which is now
|
||||
deprecated) adds demand and supply for the following sectors: transport, space
|
||||
and water heating, biomass, energy consumption in the agriculture, industry and
|
||||
industrial feedstocks, carbon management, carbon capture and
|
||||
usage/sequestration. This completes the energy system and includes all
|
||||
greenhouse gas emitters except waste management, agriculture, forestry and land
|
||||
use. The diagram below gives an overview of the sectors and the links between
|
||||
them:
|
||||
|
||||
.. image:: ../graphics/multisector_figure.png
|
||||
:width: 70%
|
||||
:align: center
|
||||
|
||||
.. note::
|
||||
You can find showcases of the model's capabilities in the Supplementary Materials of the
|
||||
preprint `Benefits of a Hydrogen Network in Europe
|
||||
<https://arxiv.org/abs/2207.05816>`_, the Supplementary Materials of the `paper in Joule with a
|
||||
description of the industry sector
|
||||
<https://arxiv.org/abs/2109.09563>`_, or in `a 2021 presentation
|
||||
at EMP-E <https://nworbmot.org/energy/brown-empe.pdf>`_.
|
||||
The sector-coupled extension of PyPSA-Eur was
|
||||
initially described in the paper `Synergies of sector coupling and transmission
|
||||
reinforcement in a cost-optimised, highly renewable European energy system
|
||||
<https://arxiv.org/abs/1801.05290>`_ (2018) but it differs by being based on the
|
||||
higher resolution electricity transmission model `PyPSA-Eur
|
||||
<https://github.com/PyPSA/pypsa-eur>`_ rather than a one-node-per-country model,
|
||||
and by including biomass, industry, industrial feedstocks, aviation, shipping,
|
||||
better carbon management, carbon capture and usage/sequestration, and gas
|
||||
networks.
|
||||
|
||||
About
|
||||
=====
|
||||
|
||||
PyPSA-Eur is designed to be imported into the open energy system modelling
|
||||
framework `PyPSA <https://www.pypsa.org>`_ for which `documentation
|
||||
<https://pypsa.readthedocs.io>`_ is available as well. However, since the
|
||||
workflow is modular, it should be easy to adapt the data workflow to other
|
||||
modelling frameworks.
|
||||
|
||||
The restriction to freely available and open data encourages the open exchange
|
||||
of model data developments and eases the comparison of model results. It
|
||||
provides a full, automated software pipeline to assemble the load-flow-ready
|
||||
model from the original datasets, which enables easy replacement and improvement
|
||||
of the individual parts.
|
||||
|
||||
.. warning::
|
||||
PyPSA-Eur is under active development and has several
|
||||
:doc:`limitations` which
|
||||
you should understand before using the model. The Github repository
|
||||
`issues <https://github.com/PyPSA/pypsa-eur/issues>`_ collect known
|
||||
topics we are working on. Please feel free to help or make suggestions.
|
||||
|
||||
This project is currently maintained by the `Department of Digital
|
||||
Transformation in Energy Systems <https:/www.ensys.tu-berlin.de>`_ at the
|
||||
`Technische Universität Berlin <https://www.tu.berlin>`_. Previous versions were
|
||||
developed within the `IAI <http://www.iai.kit.edu>`_ at the `Karlsruhe Institute of
|
||||
Technology (KIT) <http://www.kit.edu/english/index.php>`_ and by the `Renewable
|
||||
Energy Group
|
||||
developed within the `IAI <http://www.iai.kit.edu>`_ at the `Karlsruhe Institute
|
||||
of Technology (KIT) <http://www.kit.edu/english/index.php>`_ which was funded by
|
||||
the `Helmholtz Association <https://www.helmholtz.de/en/>`_, and by the
|
||||
`Renewable Energy Group
|
||||
<https://fias.uni-frankfurt.de/physics/schramm/renewable-energy-system-and-network-analysis/>`_
|
||||
at `FIAS <https://fias.uni-frankfurt.de/>`_ to carry out simulations for the
|
||||
`CoNDyNet project <http://condynet.de/>`_, financed by the `German Federal
|
||||
@ -58,129 +127,83 @@ Ministry for Education and Research (BMBF) <https://www.bmbf.de/en/index.html>`_
|
||||
as part of the `Stromnetze Research Initiative
|
||||
<http://forschung-stromnetze.info/projekte/grundlagen-und-konzepte-fuer-effiziente-dezentrale-stromnetze/>`_.
|
||||
|
||||
A version of the model that adds building heating, transport and industry sectors to the model,
|
||||
as well as gas networks, is currently being developed in the `PyPSA-Eur-Sec repository <https://github.com/pypsa/pypsa-eur-sec>`_.
|
||||
|
||||
Documentation
|
||||
=============
|
||||
|
||||
**Getting Started**
|
||||
|
||||
* :doc:`introduction`
|
||||
* :doc:`installation`
|
||||
* :doc:`tutorial`
|
||||
|
||||
.. toctree::
|
||||
:hidden:
|
||||
:maxdepth: 1
|
||||
:caption: Getting Started
|
||||
|
||||
introduction
|
||||
installation
|
||||
tutorial
|
||||
|
||||
**Configuration**
|
||||
|
||||
* :doc:`wildcards`
|
||||
* :doc:`configuration`
|
||||
* :doc:`costs`
|
||||
|
||||
.. toctree::
|
||||
:hidden:
|
||||
:maxdepth: 1
|
||||
:caption: Configuration
|
||||
|
||||
wildcards
|
||||
configuration
|
||||
costs
|
||||
|
||||
**Rules Overview**
|
||||
|
||||
* :doc:`preparation`
|
||||
* :doc:`simplification`
|
||||
* :doc:`solving`
|
||||
* :doc:`plotting`
|
||||
|
||||
.. toctree::
|
||||
:hidden:
|
||||
:maxdepth: 1
|
||||
:caption: Rules Overview
|
||||
|
||||
preparation
|
||||
simplification
|
||||
solving
|
||||
plotting
|
||||
|
||||
**References**
|
||||
|
||||
* :doc:`release_notes`
|
||||
* :doc:`limitations`
|
||||
* :doc:`contributing`
|
||||
|
||||
.. toctree::
|
||||
:hidden:
|
||||
:maxdepth: 1
|
||||
:caption: References
|
||||
|
||||
release_notes
|
||||
limitations
|
||||
contributing
|
||||
|
||||
Warnings
|
||||
Workflow
|
||||
========
|
||||
|
||||
Please read the `limitations <https://pypsa-eur.readthedocs.io/en/latest/limitations.html>`_ section of the
|
||||
documentation and paper carefully before using the model. We do not
|
||||
recommend to use the full resolution network model for simulations. At
|
||||
high granularity the assignment of loads and generators to the nearest
|
||||
network node may not be a correct assumption, depending on the topology of the underlying distribution grid,
|
||||
and local grid
|
||||
bottlenecks may cause unrealistic load-shedding or generator
|
||||
curtailment. We recommend to cluster the network to a couple of
|
||||
hundred nodes to remove these local inconsistencies.
|
||||
.. image:: ../graphics/workflow.png
|
||||
:class: full-width
|
||||
:align: center
|
||||
|
||||
.. note::
|
||||
The graph above was generated using
|
||||
``snakemake --rulegraph -F | sed -n "/digraph/,/}/p" | dot -Tpng -o workflow.png``
|
||||
|
||||
|
||||
Learning Energy System Modelling
|
||||
================================
|
||||
|
||||
If you are (relatively) new to energy system modelling and optimisation
|
||||
and plan to use PyPSA-Eur, the following resources are *one way* to get started
|
||||
in addition to reading this documentation.
|
||||
If you are (relatively) new to energy system modelling and optimisation and plan
|
||||
to use PyPSA-Eur, the following resources are one way to get started in addition
|
||||
to reading this documentation.
|
||||
|
||||
- Documentation of `PyPSA <https://pypsa.readthedocs.io>`__, the package for
|
||||
simulating and optimising modern power systems which PyPSA-Eur uses under the hood.
|
||||
- Course on `Energy Systems <https://nworbmot.org/courses/es-22/>`_,
|
||||
Technical University of Berlin (TUB), `Prof. Dr. Tom Brown <https://nworbmot.org>`_
|
||||
- Course on `Data Science for Energy System Modelling <https://fneum.github.io/data-science-for-esm/intro.html>`_,
|
||||
Technical University of Berlin (TUB), `Dr. Fabian Neumann <https://neumann.fyi>`_
|
||||
modelling energy systems which PyPSA-Eur uses under the hood.
|
||||
- Course on `Energy Systems <https://nworbmot.org/courses/es-22/>`_ given at
|
||||
Technical University of Berlin by `Prof. Dr. Tom Brown <https://nworbmot.org>`_.
|
||||
- Course on `Data Science for Energy System Modelling <https://fneum.github.io/data-science-for-esm/intro.html>`_
|
||||
given at Technical University of Berlin by `Dr. Fabian Neumann <https://neumann.fyi>`_.
|
||||
|
||||
|
||||
Citing PyPSA-Eur
|
||||
================
|
||||
|
||||
If you use PyPSA-Eur for your research, we would appreciate it if you would cite the following paper:
|
||||
If you use PyPSA-Eur for your research, we would appreciate it if you would cite one of the following papers:
|
||||
|
||||
- Jonas Hörsch, Fabian Hofmann, David Schlachtberger, and Tom Brown. `PyPSA-Eur: An open optimisation model of the European transmission system <https://arxiv.org/abs/1806.01613>`_. Energy Strategy Reviews, 22:207-215, 2018. `arXiv:1806.01613 <https://arxiv.org/abs/1806.01613>`_, `doi:10.1016/j.esr.2018.08.012 <https://doi.org/10.1016/j.esr.2018.08.012>`_.
|
||||
|
||||
Please use the following BibTeX: ::
|
||||
For electricity-only studies: ::
|
||||
|
||||
@article{PyPSAEur,
|
||||
author = "Jonas Hoersch and Fabian Hofmann and David Schlachtberger and Tom Brown",
|
||||
title = "PyPSA-Eur: An open optimisation model of the European transmission system",
|
||||
journal = "Energy Strategy Reviews",
|
||||
volume = "22",
|
||||
pages = "207 - 215",
|
||||
pages = "207--215",
|
||||
year = "2018",
|
||||
issn = "2211-467X",
|
||||
doi = "10.1016/j.esr.2018.08.012",
|
||||
eprint = "1806.01613"
|
||||
}
|
||||
|
||||
For sector-coupling studies: ::
|
||||
|
||||
If you want to cite a specific PyPSA-Eur version, each release of PyPSA-Eur is stored on Zenodo with a release-specific DOI.
|
||||
This can be found linked from the overall PyPSA-Eur Zenodo DOI:
|
||||
@misc{PyPSAEurSec,
|
||||
author = "Fabian Neumann and Elisabeth Zeyen and Marta Victoria and Tom Brown",
|
||||
title = "The Potential Role of a Hydrogen Network in Europe",
|
||||
year = "2022",
|
||||
eprint = "2207.05816",
|
||||
url = "https://arxiv.org/abs/2207.05816",
|
||||
}
|
||||
|
||||
For sector-coupling studies with pathway optimisation: ::
|
||||
|
||||
@article{SpeedTechnological2022,
|
||||
title = "Speed of technological transformations required in {Europe} to achieve different climate goals",
|
||||
author = "Marta Victoria and Elisabeth Zeyen and Tom Brown",
|
||||
journal = "Joule",
|
||||
volume = "6",
|
||||
number = "5",
|
||||
pages = "1066--1086",
|
||||
year = "2022",
|
||||
doi = "10.1016/j.joule.2022.04.016",
|
||||
eprint = "2109.09563",
|
||||
}
|
||||
|
||||
|
||||
If you want to cite a specific PyPSA-Eur version, each release of PyPSA-Eur is stored on Zenodo with a release-specific DOI:
|
||||
|
||||
.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3520874.svg
|
||||
:target: https://doi.org/10.5281/zenodo.3520874
|
||||
|
||||
|
||||
Pre-Built Networks as a Dataset
|
||||
===============================
|
||||
|
||||
@ -198,26 +221,57 @@ The included ``.nc`` files are PyPSA network files which can be imported with Py
|
||||
filename = "elec_s_1024_ec.nc" # example
|
||||
n = pypsa.Network(filename)
|
||||
|
||||
Licence
|
||||
=======
|
||||
|
||||
PyPSA-Eur work is released under multiple licenses:
|
||||
|
||||
* All original source code is licensed as free software under `MIT <LICENSES/MIT.txt>`_.
|
||||
* The documentation is licensed under `CC-BY-4.0 <LICENSES/CC-BY-4.0.txt>`_.
|
||||
* Configuration files are mostly licensed under `CC0-1.0 <LICENSES/CC0-1.0.txt>`_.
|
||||
* Data files are licensed under `CC-BY-4.0 <LICENSES/CC-BY-4.0.txt>`_.
|
||||
|
||||
See the individual files and the `dep5 <.reuse/dep5>`_ file for license details.
|
||||
|
||||
Additionally, different licenses and terms of use also apply to the various input data, which are summarised below.
|
||||
More details are included in
|
||||
`the description of the data bundles on zenodo <https://zenodo.org/record/3517935#.XbGeXvzRZGo>`_.
|
||||
.. toctree::
|
||||
:hidden:
|
||||
:maxdepth: 1
|
||||
:caption: Getting Started
|
||||
|
||||
.. csv-table::
|
||||
:header-rows: 1
|
||||
:file: configtables/licenses.csv
|
||||
introduction
|
||||
installation
|
||||
tutorial
|
||||
tutorial_sector
|
||||
|
||||
* *BY: Attribute Source*
|
||||
* *NC: Non-Commercial Use Only*
|
||||
* *SA: Share Alike*
|
||||
.. toctree::
|
||||
:hidden:
|
||||
:maxdepth: 1
|
||||
:caption: Configuration
|
||||
|
||||
wildcards
|
||||
configuration
|
||||
foresight
|
||||
costs
|
||||
|
||||
.. toctree::
|
||||
:hidden:
|
||||
:maxdepth: 1
|
||||
:caption: Rules Overview
|
||||
|
||||
retrieve
|
||||
preparation
|
||||
simplification
|
||||
sector
|
||||
solving
|
||||
plotting
|
||||
|
||||
.. toctree::
|
||||
:hidden:
|
||||
:maxdepth: 1
|
||||
:caption: Implementation details for sector-coupled systems
|
||||
|
||||
spatial_resolution
|
||||
supply_demand
|
||||
|
||||
.. toctree::
|
||||
:hidden:
|
||||
:maxdepth: 1
|
||||
:caption: References
|
||||
|
||||
release_notes
|
||||
licenses
|
||||
limitations
|
||||
contributing
|
||||
publications
|
||||
|
||||
@ -15,15 +15,13 @@ directory in which the commands following the ``%`` should be entered.
|
||||
Clone the Repository
|
||||
====================
|
||||
|
||||
First of all, clone the `PyPSA-Eur repository <https://github.com/PyPSA/pypsa-eur>`_ using the version control system ``git``.
|
||||
The path to the directory into which the ``git repository`` is cloned, must **not** have any spaces!
|
||||
If you do not have ``git`` installed, follow installation instructions `here <https://git-scm.com/book/en/v2/Getting-Started-Installing-Git>`_.
|
||||
First of all, clone the `PyPSA-Eur repository <https://github.com/PyPSA/pypsa-eur>`_ using the version control system ``git`` in the command line.
|
||||
|
||||
.. code:: bash
|
||||
|
||||
/some/other/path % cd /some/path/without/spaces
|
||||
/some/other/path % cd /some/path
|
||||
|
||||
/some/path/without/spaces % git clone https://github.com/PyPSA/pypsa-eur.git
|
||||
/some/path % git clone https://github.com/PyPSA/pypsa-eur.git
|
||||
|
||||
|
||||
.. _deps:
|
||||
@ -32,98 +30,108 @@ Install Python Dependencies
|
||||
===============================
|
||||
|
||||
PyPSA-Eur relies on a set of other Python packages to function.
|
||||
We recommend using the package manager and environment management system ``conda`` to install them.
|
||||
Install `miniconda <https://docs.conda.io/en/latest/miniconda.html>`_, which is a mini version of `Anaconda <https://www.anaconda.com/>`_ that includes only ``conda`` and its dependencies or make sure ``conda`` is already installed on your system.
|
||||
For instructions for your operating system follow the ``conda`` `installation guide <https://docs.conda.io/projects/conda/en/latest/user-guide/install/>`_.
|
||||
We recommend using the package manager `mamba <https://mamba.readthedocs.io/en/latest/>`_ to install them and manage your environments.
|
||||
For instructions for your operating system follow the ``mamba`` `installation guide <https://mamba.readthedocs.io/en/latest/installation.html>`_.
|
||||
You can also use ``conda`` equivalently.
|
||||
|
||||
The python package requirements are curated in the `envs/environment.yaml <https://github.com/PyPSA/pypsa-eur/blob/master/envs/environment.yaml>`_ file.
|
||||
The package requirements are curated in the `envs/environment.yaml <https://github.com/PyPSA/pypsa-eur/blob/master/envs/environment.yaml>`_ file.
|
||||
The environment can be installed and activated using
|
||||
|
||||
.. code:: bash
|
||||
|
||||
.../pypsa-eur % conda env create -f envs/environment.yaml
|
||||
.../pypsa-eur % mamba create -f envs/environment.yaml
|
||||
|
||||
.../pypsa-eur % conda activate pypsa-eur
|
||||
|
||||
Note that activation is local to the currently open shell!
|
||||
After opening a new terminal window, one needs to reissue the second command!
|
||||
.../pypsa-eur % mamba activate pypsa-eur
|
||||
|
||||
.. note::
|
||||
If you have troubles with a slow ``conda`` installation, we recommend to install
|
||||
`mamba <https://github.com/QuantStack/mamba>`_ as a fast drop-in replacement via
|
||||
The equivalent commands for ``conda`` would be
|
||||
|
||||
.. code:: bash
|
||||
|
||||
conda install -c conda-forge mamba
|
||||
.../pypsa-eur % conda env create -f envs/environment.yaml
|
||||
|
||||
and then install the environment with
|
||||
.../pypsa-eur % conda activate pypsa-eur
|
||||
|
||||
.. code:: bash
|
||||
|
||||
mamba env create -f envs/environment.yaml
|
||||
|
||||
Install a Solver
|
||||
================
|
||||
|
||||
PyPSA passes the PyPSA-Eur network model to an external solver for performing a total annual system cost minimization with optimal power flow.
|
||||
PyPSA passes the PyPSA-Eur network model to an external solver for performing the optimisation.
|
||||
PyPSA is known to work with the free software
|
||||
|
||||
- `Ipopt <https://coin-or.github.io/Ipopt/INSTALL.html>`_
|
||||
- `HiGHS <https://highs.dev/>`_
|
||||
- `Cbc <https://projects.coin-or.org/Cbc#DownloadandInstall>`_
|
||||
- `GLPK <https://www.gnu.org/software/glpk/>`_ (`WinGLKP <http://winglpk.sourceforge.net/>`_)
|
||||
- `HiGHS <https://highs.dev/>`_
|
||||
- `Ipopt <https://coin-or.github.io/Ipopt/INSTALL.html>`_
|
||||
|
||||
and the non-free, commercial software (for some of which free academic licenses are available)
|
||||
|
||||
- `Gurobi <https://www.gurobi.com/documentation/quickstart.html>`_
|
||||
- `CPLEX <https://www.ibm.com/products/ilog-cplex-optimization-studio>`_
|
||||
- `FICO® Xpress Solver <https://www.fico.com/de/products/fico-xpress-solver>`_
|
||||
- `FICO Xpress Solver <https://www.fico.com/de/products/fico-xpress-solver>`_
|
||||
|
||||
For installation instructions of these solvers for your operating system, follow the links above.
|
||||
Commercial solvers such as Gurobi and CPLEX currently significantly outperform open-source solvers for large-scale problems.
|
||||
It might be the case that you can only retrieve solutions by using a commercial solver.
|
||||
Commercial solvers such as Gurobi and CPLEX currently significantly outperform open-source solvers for large-scale problems, and
|
||||
it might be the case that you can only retrieve solutions by using a commercial solver.
|
||||
Nevertheless, you can still use open-source solvers for smaller problems.
|
||||
|
||||
.. seealso::
|
||||
`Getting a solver in the PyPSA documentation <https://pypsa.readthedocs.io/en/latest/installation.html#getting-a-solver-for-linear-optimisation>`_
|
||||
`Instructions how to install a solver in the documentation of PyPSA <https://pypsa.readthedocs.io/en/latest/installation.html#getting-a-solver-for-linear-optimisation>`_
|
||||
|
||||
.. note::
|
||||
The rules :mod:`cluster_network` and :mod:`simplify_network` solve a quadratic optimisation problem for clustering.
|
||||
The open-source solvers Cbc and GlPK cannot handle this. A fallback to Ipopt is implemented in this case, but requires
|
||||
also Ipopt to be installed. For an open-source solver setup install in your ``conda`` environment on OSX/Linux
|
||||
it to be installed. For an open-source solver setup install in your ``conda`` environment on OSX/Linux
|
||||
|
||||
.. code:: bash
|
||||
|
||||
conda activate pypsa-eur
|
||||
conda install -c conda-forge ipopt coincbc
|
||||
mamba activate pypsa-eur
|
||||
mamba install -c conda-forge ipopt coincbc
|
||||
|
||||
and on Windows
|
||||
|
||||
.. code:: bash
|
||||
|
||||
conda activate pypsa-eur
|
||||
conda install -c conda-forge ipopt glpk
|
||||
mamba activate pypsa-eur
|
||||
mamba install -c conda-forge ipopt glpk
|
||||
|
||||
or
|
||||
For HiGHS, run
|
||||
|
||||
.. code:: bash
|
||||
|
||||
conda activate pypsa-eur
|
||||
mamba activate pypsa-eur
|
||||
mamba install -c conda-forge ipopt
|
||||
pip install highspy
|
||||
|
||||
For Gurobi, run
|
||||
|
||||
.. code:: bash
|
||||
|
||||
mamba activate pypsa-eur
|
||||
mamba install -c gurobi gurobi
|
||||
|
||||
Additionally, you need to setup your `Gurobi license <https://www.gurobi.com/solutions/licensing/>`_.
|
||||
|
||||
|
||||
.. _defaultconfig:
|
||||
|
||||
Set Up the Default Configuration
|
||||
================================
|
||||
Handling Configuration Files
|
||||
============================
|
||||
|
||||
PyPSA-Eur has several configuration options that must be specified in a ``config.yaml`` file located in the root directory.
|
||||
An example configuration ``config.default.yaml`` is maintained in the repository.
|
||||
More details on the configuration options are in :ref:`config`.
|
||||
PyPSA-Eur has several configuration options that must be specified in a
|
||||
``config.yaml`` file located in the root directory. An example configuration
|
||||
``config.default.yaml`` is maintained in the repository, which will be used to
|
||||
automatically create your customisable ``config.yaml`` on first use. More
|
||||
details on the configuration options are in :ref:`config`.
|
||||
|
||||
Before first use, create a ``config.yaml`` by copying the example.
|
||||
You can also use ``snakemake`` to specify another file, e.g.
|
||||
``config.mymodifications.yaml``, to update the settings of the ``config.yaml``.
|
||||
|
||||
.. code:: bash
|
||||
|
||||
.../pypsa-eur % cp config.default.yaml config.yaml
|
||||
.../pypsa-eur % snakemake -call --configfile config.mymodifications.yaml
|
||||
|
||||
Users are advised to regularly check their own ``config.yaml`` against changes in the ``config.default.yaml``
|
||||
when pulling a new version from the remote repository.
|
||||
.. warning::
|
||||
Users are advised to regularly check their own ``config.yaml`` against changes
|
||||
in the ``config.default.yaml`` when pulling a new version from the remote
|
||||
repository.
|
||||
|
||||
@ -13,58 +13,89 @@
|
||||
|
||||
<iframe width="832" height="468" src="https://www.youtube.com/embed/ty47YU1_eeQ" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
|
||||
|
||||
Find the introductory slides `here <https://docs.google.com/presentation/d/e/2PACX-1vQGQZD7KIVdocRZzRVu8Uk-JC_ltEow5zjtIarhyws46IMJpaqGuux695yincmJA_i5bVEibEs7z2eo/pub?start=false&loop=true&delayms=3000>`_.
|
||||
.. note::
|
||||
Find the introductory slides `here <https://docs.google.com/presentation/d/e/2PACX-1vQGQZD7KIVdocRZzRVu8Uk-JC_ltEow5zjtIarhyws46IMJpaqGuux695yincmJA_i5bVEibEs7z2eo/pub?start=false&loop=true&delayms=3000>`_.
|
||||
|
||||
.. warning::
|
||||
The video only introduces the electricity-only part of PyPSA-Eur.
|
||||
|
||||
Workflow
|
||||
=========
|
||||
|
||||
The generation of the model is controlled by the workflow management system
|
||||
`Snakemake <https://snakemake.bitbucket.io/>`_.
|
||||
In a nutshell, the ``Snakefile`` declares for each python script in the ``scripts`` directory a rule which describes which files the scripts consume and produce (their corresponding input and output files).
|
||||
The ``snakemake`` tool then runs the scripts in the correct order according to the rules' input/output dependencies.
|
||||
Moreover, it is able to track, what parts of the workflow have to be regenerated, when a data file or a script is modified/updated.
|
||||
The generation of the model is controlled by the open workflow management system
|
||||
`Snakemake <https://snakemake.github.io/>`_. In a nutshell, the ``Snakefile``
|
||||
declares for each script in the ``scripts`` directory a rule which describes
|
||||
which files the scripts consume and produce (their corresponding input and
|
||||
output files). The ``snakemake`` tool then runs the scripts in the correct order
|
||||
according to the rules' input and output dependencies. Moreover, ``snakemake``
|
||||
will track what parts of the workflow have to be regenerated when files or
|
||||
scripts were modified.
|
||||
|
||||
For instance an invocation to
|
||||
For instance, an invocation to
|
||||
|
||||
.. code:: bash
|
||||
|
||||
.../pypsa-eur % snakemake -call results/networks/elec_s_128_ec_lvopt_Co2L-3H.nc
|
||||
|
||||
follows this dependency graph:
|
||||
follows this dependency graph
|
||||
|
||||
.. image:: img/workflow.png
|
||||
.. image:: img/intro-workflow.png
|
||||
:class: full-width
|
||||
|
||||
The **blocks** represent the individual rules which are required to create the file ``networks/elec_s_128.nc``. The **arrows** indicate the outputs from preceding rules which a particular rule takes as input data.
|
||||
to solve an electricity system model.
|
||||
|
||||
The **blocks** represent the individual rules which are required to create the
|
||||
file referenced in the command above. The **arrows** indicate the outputs from
|
||||
preceding rules which another rule takes as input data.
|
||||
|
||||
.. note::
|
||||
The dependency graph shown above was generated using
|
||||
``snakemake --dag results/networks/elec_s_128_ec_lvopt_Co2L-3H.nc -F | sed -n "/digraph/,/}/p" | dot -Tpng -o workflow.png``
|
||||
The dependency graph was generated using
|
||||
``snakemake --dag results/networks/elec_s_128_ec_lvopt_Co2L-3H.nc -F | sed -n "/digraph/,/}/p" | dot -Tpng -o doc/img/intro-workflow.png``
|
||||
|
||||
For the use of ``snakemake``, it makes sense to familiarize oneself quickly with its `basic tutorial <https://snakemake.readthedocs.io/en/stable/tutorial/basics.html>`_ and then read carefully through the section `Executing Snakemake <https://snakemake.readthedocs.io/en/stable/executable.html>`_, noting the arguments ``-j``, ``-n``, ``-r``, but also ``--dag``, ``-R`` and ``-t``.
|
||||
For the use of ``snakemake``, it makes sense to familiarize yourself quickly
|
||||
with the `basic tutorial
|
||||
<https://snakemake.readthedocs.io/en/stable/tutorial/basics.html>`_ and then
|
||||
read carefully through the documentation of the `command line interface
|
||||
<https://snakemake.readthedocs.io/en/stable/executing/cli.html>`_, noting the
|
||||
arguments ``-j``, ``-c``, ``-f``, ``-F``, ``-n``, ``-r``, ``--dag`` and ``-t``
|
||||
in particular.
|
||||
|
||||
Scenarios, Configuration and Modification
|
||||
=========================================
|
||||
|
||||
It is easy to run PyPSA-Eur for multiple scenarios using the `wildcards feature <https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#wildcards>`_ of ``snakemake``. Wildcards allow to generalise a rule to produce all files that follow a `regular expression <https://en.wikipedia.org/wiki/Regular_expression>`_ pattern, which e.g. defines one particular scenario. One can think of a wildcard as a parameter that shows up in the input/output file names and thereby determines which rules to run, what data to retrieve and what files to produce. **Details are explained in** :ref:`wildcards` **and** :ref:`scenario`.
|
||||
It is easy to run PyPSA-Eur for multiple scenarios using the `wildcards feature
|
||||
<https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#wildcards>`_
|
||||
of ``snakemake``. Wildcards allow to generalise a rule to produce all files that
|
||||
follow a `regular expression
|
||||
<https://en.wikipedia.org/wiki/Regular_expression>`_ pattern, which defines
|
||||
a particular scenario. One can think of a wildcard as a parameter that shows
|
||||
up in the input/output file names and thereby determines which rules to run,
|
||||
what data to retrieve and what files to produce. Details are explained in
|
||||
:ref:`wildcards` and :ref:`scenario`.
|
||||
|
||||
The model also has several further configuration options collected in the ``config.yaml`` file
|
||||
located in the root directory, which that are not part of the scenarios. **All options are explained in detail in** :ref:`config`.
|
||||
The model also has several further configuration options collected in the
|
||||
``config.yaml`` file located in the root directory, which that are not part of
|
||||
the scenarios. Options are explained in :ref:`config`.
|
||||
|
||||
Folder Structure
|
||||
================
|
||||
|
||||
- ``data``: Includes input data that is not produced by any ``snakemake`` rule.
|
||||
- ``scripts``: Includes all the Python scripts executed by the ``snakemake`` rules.
|
||||
- ``rules``: Includes all the ``snakemake`` rules loaded in the ``Snakefile``.
|
||||
- ``envs``: Includes all the ``conda`` environment specifications to run the workflow.
|
||||
- ``data``: Includes input data that is not produced by any ``snakemake`` rule.
|
||||
- ``cutouts``: Stores raw weather data cutouts from ``atlite``.
|
||||
- ``resources``: Stores intermediate results of the workflow which can be picked up again by subsequent rules.
|
||||
- ``networks``: Stores intermediate, unsolved stages of the PyPSA network that describes the energy system model.
|
||||
- ``results``: Stores the solved PyPSA network data, summary files and plots.
|
||||
- ``logs``: Stores log files.
|
||||
- ``benchmarks``: Stores ``snakemake`` benchmarks.
|
||||
- ``logs``: Stores log files about solving, including the solver output, console output and the output of a memory logger.
|
||||
- ``test``: Includes the test configuration files used for continuous integration.
|
||||
- ``doc``: Includes the documentation of PyPSA-Eur.
|
||||
|
||||
System Requirements
|
||||
===================
|
||||
|
||||
Building the model with the scripts in this repository runs on a normal computer.
|
||||
But computing optimal investment and operation scenarios requires a strong interior-point solver
|
||||
Building the model with the scripts in this repository runs on a regular computer.
|
||||
But optimising for investment and operation decisions across many scenarios requires a strong interior-point solver
|
||||
like `Gurobi <http://www.gurobi.com/>`_ or `CPLEX <https://www.ibm.com/analytics/cplex-optimizer>`_ with more memory.
|
||||
Open-source solvers like `HiGHS <https://highs.dev>` can also be used for smaller problems.
|
||||
|
||||
44
doc/licenses.rst
Normal file
44
doc/licenses.rst
Normal file
@ -0,0 +1,44 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
##########################################
|
||||
Licenses
|
||||
##########################################
|
||||
|
||||
|
||||
PyPSA-Eur is released under multiple licenses:
|
||||
|
||||
* All original source code is licensed as free software under `MIT <LICENSES/MIT.txt>`_.
|
||||
* The documentation is licensed under `CC-BY-4.0 <LICENSES/CC-BY-4.0.txt>`_.
|
||||
* Configuration files are mostly licensed under `CC0-1.0 <LICENSES/CC0-1.0.txt>`_.
|
||||
* Data files are licensed under `CC-BY-4.0 <LICENSES/CC-BY-4.0.txt>`_.
|
||||
|
||||
See the individual files and the `dep5 <.reuse/dep5>`_ file for license details.
|
||||
|
||||
Additionally, different licenses and terms of use also apply to the various
|
||||
input data for both electricity-only and sector-coupled modelling exercises,
|
||||
which are summarised below.
|
||||
|
||||
Electricity Systems Databundle
|
||||
==============================
|
||||
|
||||
.. note::
|
||||
More details are included in `the description of the
|
||||
data bundles on zenodo <https://zenodo.org/record/3517935#.XbGeXvzRZGo>`_.
|
||||
|
||||
.. csv-table::
|
||||
:header-rows: 1
|
||||
:file: configtables/licenses.csv
|
||||
|
||||
* BY: Attribute Source
|
||||
* NC: Non-Commercial Use Only
|
||||
* SA: Share Alike
|
||||
|
||||
Sector-Coupled Systems Databundle
|
||||
=================================
|
||||
|
||||
.. csv-table::
|
||||
:header-rows: 1
|
||||
:file: configtables/licenses-sector.csv
|
||||
@ -7,15 +7,21 @@
|
||||
Limitations
|
||||
##########################################
|
||||
|
||||
|
||||
While the benefit of an openly available, functional and partially validated
|
||||
model of the European transmission system is high, many approximations have
|
||||
model of the European energy system is high, many approximations have
|
||||
been made due to missing data.
|
||||
The limitations of the dataset are listed below,
|
||||
both as a warning to the user and as an encouragement to assist in
|
||||
improving the approximations.
|
||||
|
||||
- **Network topology:**
|
||||
.. warning::
|
||||
|
||||
This list of limitations is incomplete and will be added to over time.
|
||||
|
||||
.. seealso::
|
||||
See also the `GitHub repository issues <https://github.com/PyPSA/pypsa-eur/issues>`_.
|
||||
|
||||
- **Electricity transmission network topology:**
|
||||
The grid data is based on a map of the ENTSO-E area that is known
|
||||
to contain small distortions to improve readability. Since the exact impedances
|
||||
of the lines are unknown, approximations based on line lengths and standard
|
||||
@ -23,14 +29,27 @@ improving the approximations.
|
||||
particular lines. There is no openly available data on busbar configurations, switch
|
||||
locations, transformers or reactive power compensation assets.
|
||||
|
||||
- **Distribution networks:**
|
||||
- **Assignment of electricity demand to transmission nodes:**
|
||||
Using Voronoi cells to aggregate load and generator data to transmission
|
||||
network substations ignores the topology of the underlying distribution network,
|
||||
meaning that assets may be connected to the wrong substation.
|
||||
|
||||
- **Power Demand:**
|
||||
- **Incomplete information on existing assets:** Approximations have
|
||||
been made for missing data, including: existing distribution grid
|
||||
capacities and costs, existing space and water heating supply,
|
||||
existing industry facilities, existing transport vehicle fleets.
|
||||
|
||||
- **Exogenous pathways for transformation of transport and industry:**
|
||||
To avoid penny-switching the transformation of transport and
|
||||
industry away from fossil fuels is determined exogenously.
|
||||
|
||||
- **Industry materials production constant and inelastic:**
|
||||
For industry, the production of different materials per country is
|
||||
assumed to remain constant and no industry demand elasticity is included in the modelled.
|
||||
|
||||
- **Energy demand distribution within countries:**
|
||||
Assumptions
|
||||
have been made about the distribution of load in each country proportional to
|
||||
have been made about the distribution of demand in each country proportional to
|
||||
population and GDP that may not reflect local circumstances.
|
||||
Openly available
|
||||
data on load time series may not correspond to the true vertical load and is
|
||||
@ -56,3 +75,6 @@ improving the approximations.
|
||||
Belarus, Ukraine, Turkey and Morocco have not been taken into account;
|
||||
islands which are not connected to the main European system, such as Malta,
|
||||
Crete and Cyprus, are also excluded from the model.
|
||||
|
||||
- **Demand sufficiency:** Further measures of demand reduction may be
|
||||
possible beyond the assumptions made here.
|
||||
|
||||
106
doc/plotting.rst
106
doc/plotting.rst
@ -4,79 +4,13 @@
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
##########################################
|
||||
Plotting and Summary
|
||||
Plotting and Summaries
|
||||
##########################################
|
||||
|
||||
.. warning:: The corresponding code is currently under revision and has only minimal documentation.
|
||||
|
||||
.. _plot_potentials:
|
||||
|
||||
Rule ``plot_p_nom_max``
|
||||
==========================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="8,5"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
0 [color="0.42 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=plot_p_nom_max,
|
||||
style=filled];
|
||||
1 [color="0.58 0.6 0.85",
|
||||
label=cluster_network];
|
||||
1 -> 0;
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: plot_p_nom_max
|
||||
|
||||
.. _summary:
|
||||
|
||||
Rule ``make_summary``
|
||||
========================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="8,5"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
0 [color="0.47 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=make_summary,
|
||||
style=filled];
|
||||
1 [color="0.11 0.6 0.85",
|
||||
label=solve_network];
|
||||
1 -> 0;
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: make_summary
|
||||
|
||||
.. _summary_plot:
|
||||
@ -84,13 +18,6 @@ Rule ``make_summary``
|
||||
Rule ``plot_summary``
|
||||
========================
|
||||
|
||||
.. .. graphviz::
|
||||
.. :align: center
|
||||
|
||||
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: plot_summary
|
||||
|
||||
.. _map_plot:
|
||||
@ -98,35 +25,4 @@ Rule ``plot_summary``
|
||||
Rule ``plot_network``
|
||||
========================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="8,5"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
0 [color="0.00 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=plot_network,
|
||||
style=filled];
|
||||
1 [color="0.50 0.6 0.85",
|
||||
label=solve_network];
|
||||
1 -> 0;
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: plot_network
|
||||
|
||||
.. image:: img/tech-colors.png
|
||||
:align: center
|
||||
|
||||
@ -4,7 +4,7 @@
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
##########################################
|
||||
Preparing Networks
|
||||
Building Electricity Networks
|
||||
##########################################
|
||||
|
||||
The preparation process of the PyPSA-Eur energy system model consists of a group of ``snakemake``
|
||||
@ -35,19 +35,92 @@ Then the process continues by calculating conventional power plant capacities, p
|
||||
The central rule :mod:`add_electricity` then ties all the different data inputs
|
||||
together into a detailed PyPSA network stored in ``networks/elec.nc``.
|
||||
|
||||
.. toctree::
|
||||
:caption: Overview
|
||||
.. _busregions:
|
||||
|
||||
preparation/retrieve
|
||||
preparation/build_shapes
|
||||
preparation/build_load_data
|
||||
preparation/build_cutout
|
||||
preparation/build_natura_raster
|
||||
preparation/build_ship_raster
|
||||
preparation/prepare_links_p_nom
|
||||
preparation/base_network
|
||||
preparation/build_bus_regions
|
||||
preparation/build_powerplants
|
||||
preparation/build_renewable_profiles
|
||||
preparation/build_hydro_profile
|
||||
preparation/add_electricity
|
||||
Rule ``build_bus_regions``
|
||||
=============================
|
||||
|
||||
.. automodule:: build_bus_regions
|
||||
|
||||
.. _cutout:
|
||||
|
||||
Rule ``build_cutout``
|
||||
=============================
|
||||
|
||||
.. automodule:: build_cutout
|
||||
|
||||
|
||||
Rule ``prepare_links_p_nom``
|
||||
===============================
|
||||
|
||||
.. automodule:: prepare_links_p_nom
|
||||
|
||||
.. _natura:
|
||||
|
||||
Rule ``build_natura_raster``
|
||||
===============================
|
||||
|
||||
.. automodule:: build_natura_raster
|
||||
|
||||
|
||||
.. _base:
|
||||
|
||||
Rule ``base_network``
|
||||
=============================
|
||||
|
||||
.. automodule:: base_network
|
||||
|
||||
.. _shapes:
|
||||
|
||||
Rule ``build_shapes``
|
||||
=============================
|
||||
|
||||
.. automodule:: build_shapes
|
||||
|
||||
|
||||
.. _powerplants:
|
||||
|
||||
Rule ``build_powerplants``
|
||||
=============================
|
||||
|
||||
.. automodule:: build_powerplants
|
||||
|
||||
|
||||
.. _load_data:
|
||||
|
||||
Rule ``build_load_data``
|
||||
=============================
|
||||
|
||||
|
||||
.. automodule:: build_load_data
|
||||
|
||||
.. _ship:
|
||||
|
||||
Rule ``build_ship_raster``
|
||||
===============================
|
||||
|
||||
|
||||
.. automodule:: build_ship_raster
|
||||
|
||||
|
||||
.. _renewableprofiles:
|
||||
|
||||
Rule ``build_renewable_profiles``
|
||||
====================================
|
||||
|
||||
.. automodule:: build_renewable_profiles
|
||||
|
||||
|
||||
.. _hydroprofiles:
|
||||
|
||||
Rule ``build_hydro_profile``
|
||||
===============================
|
||||
|
||||
.. automodule:: build_hydro_profile
|
||||
|
||||
.. _electricity:
|
||||
|
||||
Rule ``add_electricity``
|
||||
=============================
|
||||
|
||||
.. automodule:: add_electricity
|
||||
|
||||
@ -1,57 +0,0 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _electricity:
|
||||
|
||||
Rule ``add_electricity``
|
||||
=============================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="8,5"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
3 [color="0.25 0.6 0.85",
|
||||
label=simplify_network];
|
||||
4 [color="0.50 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=add_electricity,
|
||||
style=filled];
|
||||
4 -> 3;
|
||||
5 [color="0.36 0.6 0.85",
|
||||
label=build_bus_regions];
|
||||
5 -> 4;
|
||||
6 [color="0.58 0.6 0.85",
|
||||
label=base_network];
|
||||
6 -> 4;
|
||||
7 [color="0.31 0.6 0.85",
|
||||
label=build_powerplants];
|
||||
7 -> 4;
|
||||
8 [color="0.28 0.6 0.85",
|
||||
label=build_shapes];
|
||||
8 -> 4;
|
||||
9 [color="0.22 0.6 0.85",
|
||||
label=build_renewable_profiles];
|
||||
9 -> 4;
|
||||
10 [color="0.44 0.6 0.85",
|
||||
label=build_hydro_profile];
|
||||
10 -> 4;
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: add_electricity
|
||||
@ -1,54 +0,0 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _base:
|
||||
|
||||
Rule ``base_network``
|
||||
=============================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="8,5"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
4 [color="0.50 0.6 0.85",
|
||||
label=add_electricity];
|
||||
5 [color="0.36 0.6 0.85",
|
||||
label=build_bus_regions];
|
||||
6 [color="0.58 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=base_network,
|
||||
style=filled];
|
||||
6 -> 4;
|
||||
6 -> 5;
|
||||
7 [color="0.31 0.6 0.85",
|
||||
label=build_powerplants];
|
||||
6 -> 7;
|
||||
9 [color="0.22 0.6 0.85",
|
||||
label=build_renewable_profiles];
|
||||
6 -> 9;
|
||||
8 [color="0.28 0.6 0.85",
|
||||
label=build_shapes];
|
||||
8 -> 6;
|
||||
11 [color="0.03 0.6 0.85",
|
||||
label=prepare_links_p_nom];
|
||||
11 -> 6;
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: base_network
|
||||
@ -1,51 +0,0 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _busregions:
|
||||
|
||||
Rule ``build_bus_regions``
|
||||
=============================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="8,5"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
3 [color="0.25 0.6 0.85",
|
||||
label=simplify_network];
|
||||
4 [color="0.50 0.6 0.85",
|
||||
label=add_electricity];
|
||||
5 [color="0.36 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=build_bus_regions,
|
||||
style=filled];
|
||||
5 -> 3;
|
||||
5 -> 4;
|
||||
9 [color="0.22 0.6 0.85",
|
||||
label=build_renewable_profiles];
|
||||
5 -> 9;
|
||||
6 [color="0.58 0.6 0.85",
|
||||
label=base_network];
|
||||
6 -> 5;
|
||||
8 [color="0.28 0.6 0.85",
|
||||
label=build_shapes];
|
||||
8 -> 5;
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: build_bus_regions
|
||||
@ -1,42 +0,0 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _cutout:
|
||||
|
||||
Rule ``build_cutout``
|
||||
=============================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="8,5"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
9 [color="0.22 0.6 0.85",
|
||||
label=build_renewable_profiles];
|
||||
10 [color="0.44 0.6 0.85",
|
||||
label=build_hydro_profile];
|
||||
13 [color="0.17 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=build_cutout,
|
||||
style=filled];
|
||||
13 -> 9;
|
||||
13 -> 10;
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: build_cutout
|
||||
@ -1,45 +0,0 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _hydroprofiles:
|
||||
|
||||
Rule ``build_hydro_profile``
|
||||
===============================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="8,5"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
4 [color="0.61 0.6 0.85",
|
||||
label=add_electricity];
|
||||
8 [color="0.00 0.6 0.85",
|
||||
label=build_shapes];
|
||||
10 [color="0.11 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=build_hydro_profile,
|
||||
style=filled];
|
||||
8 -> 10;
|
||||
10 -> 4;
|
||||
13 [color="0.56 0.6 0.85",
|
||||
label=build_cutout];
|
||||
13 -> 10;
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: build_hydro_profile
|
||||
@ -1,12 +0,0 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2020-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _load_data:
|
||||
|
||||
Rule ``build_load_data``
|
||||
=============================
|
||||
|
||||
|
||||
.. automodule:: build_load_data
|
||||
@ -1,39 +0,0 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _natura:
|
||||
|
||||
Rule ``build_natura_raster``
|
||||
===============================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="8,5"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
9 [color="0.22 0.6 0.85",
|
||||
label=build_renewable_profiles];
|
||||
12 [color="0.31 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=build_natura_raster,
|
||||
style=filled];
|
||||
12 -> 9;
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: build_natura_raster
|
||||
@ -1,42 +0,0 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _powerplants:
|
||||
|
||||
Rule ``build_powerplants``
|
||||
=============================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="8,5"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
4 [color="0.61 0.6 0.85",
|
||||
label=add_electricity];
|
||||
6 [color="0.17 0.6 0.85",
|
||||
label=base_network];
|
||||
7 [color="0.58 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=build_powerplants,
|
||||
style=filled];
|
||||
6 -> 7;
|
||||
7 -> 4;
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: build_powerplants
|
||||
@ -1,54 +0,0 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _renewableprofiles:
|
||||
|
||||
Rule ``build_renewable_profiles``
|
||||
====================================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="8,5"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
4 [color="0.61 0.6 0.85",
|
||||
label=add_electricity];
|
||||
5 [color="0.19 0.6 0.85",
|
||||
label=build_bus_regions];
|
||||
9 [color="0.22 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=build_renewable_profiles,
|
||||
style=filled];
|
||||
5 -> 9;
|
||||
9 -> 4;
|
||||
6 [color="0.17 0.6 0.85",
|
||||
label=base_network];
|
||||
6 -> 9;
|
||||
8 [color="0.00 0.6 0.85",
|
||||
label=build_shapes];
|
||||
8 -> 9;
|
||||
12 [color="0.31 0.6 0.85",
|
||||
label=build_natura_raster];
|
||||
12 -> 9;
|
||||
13 [color="0.56 0.6 0.85",
|
||||
label=build_cutout];
|
||||
13 -> 9;
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: build_renewable_profiles
|
||||
@ -1,51 +0,0 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _shapes:
|
||||
|
||||
Rule ``build_shapes``
|
||||
=============================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="8,5"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
4 [color="0.61 0.6 0.85",
|
||||
label=add_electricity];
|
||||
5 [color="0.19 0.6 0.85",
|
||||
label=build_bus_regions];
|
||||
6 [color="0.17 0.6 0.85",
|
||||
label=base_network];
|
||||
8 [color="0.00 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=build_shapes,
|
||||
style=filled];
|
||||
8 -> 4;
|
||||
8 -> 5;
|
||||
8 -> 6;
|
||||
9 [color="0.22 0.6 0.85",
|
||||
label=build_renewable_profiles];
|
||||
8 -> 9;
|
||||
10 [color="0.11 0.6 0.85",
|
||||
label=build_hydro_profile];
|
||||
8 -> 10;
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: build_shapes
|
||||
@ -1,12 +0,0 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _ship:
|
||||
|
||||
Rule ``build_ship_raster``
|
||||
===============================
|
||||
|
||||
|
||||
.. automodule:: build_ship_raster
|
||||
@ -1,39 +0,0 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _links:
|
||||
|
||||
Rule ``prepare_links_p_nom``
|
||||
===============================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="8,5"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
6 [color="0.17 0.6 0.85",
|
||||
label=base_network];
|
||||
11 [color="0.39 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=prepare_links_p_nom,
|
||||
style=filled];
|
||||
11 -> 6;
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: prepare_links_p_nom
|
||||
261
doc/publications.bib
Normal file
261
doc/publications.bib
Normal file
@ -0,0 +1,261 @@
|
||||
@Comment{
|
||||
SPDX-FileCopyrightText: 2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC0-1.0
|
||||
}
|
||||
|
||||
@article{PyPSAEur,
|
||||
author = "Jonas Hörsch and Fabian Hofmann and David Schlachtberger and Tom Brown",
|
||||
title = "PyPSA-Eur: An open optimisation model of the {European} transmission system",
|
||||
journal = "Energy Strategy Reviews",
|
||||
volume = "22",
|
||||
pages = "207--215",
|
||||
year = "2018",
|
||||
doi = "10.1016/j.esr.2018.08.012",
|
||||
eprint = "1806.01613"
|
||||
}
|
||||
|
||||
@misc{PyPSAEurSec,
|
||||
author = "Fabian Neumann and Elisabeth Zeyen and Marta Victoria and Tom Brown",
|
||||
title = "The Potential Role of a Hydrogen Network in {Europe}",
|
||||
year = "2022",
|
||||
eprint = "2207.05816",
|
||||
}
|
||||
|
||||
@article{brownSynergiesSector2018a,
|
||||
title = {Synergies of sector coupling and transmission reinforcement in a cost-optimised, highly renewable {European} energy system},
|
||||
volume = {160},
|
||||
issn = {03605442},
|
||||
doi = {10.1016/j.energy.2018.06.222},
|
||||
journal = {Energy},
|
||||
author = {Brown, T. and Schlachtberger, D. and Kies, A. and Schramm, S. and Greiner, M.},
|
||||
year = {2018},
|
||||
pages = {720--739},
|
||||
}
|
||||
|
||||
|
||||
@article{SpeedTechnological2022,
|
||||
title = "Speed of technological transformations required in {Europe} to achieve different climate goals",
|
||||
author = "Marta Victoria and Elisabeth Zeyen and Tom Brown",
|
||||
journal = "Joule",
|
||||
volume = "6",
|
||||
number = "5",
|
||||
pages = "1066--1086",
|
||||
year = "2022",
|
||||
doi = "10.1016/j.joule.2022.04.016",
|
||||
eprint = "2109.09563",
|
||||
}
|
||||
|
||||
|
||||
|
||||
@article{victoriaEarlyDecarbonisation2020,
|
||||
title = {Early decarbonisation of the {European} energy system pays off},
|
||||
volume = {11},
|
||||
doi = {10.1038/s41467-020-20015-4},
|
||||
number = {1},
|
||||
journal = {Nature Communications},
|
||||
author = {Victoria, Marta and Zhu, Kun and Brown, Tom and Andresen, Gorm B. and Greiner, Martin},
|
||||
year = {2020},
|
||||
pages = {6223},
|
||||
}
|
||||
|
||||
@article{schlachtbergerCostOptimal2018,
|
||||
title = {Cost optimal scenarios of a future highly renewable {European} electricity system: {Exploring} the influence of weather data, cost parameters and policy constraints},
|
||||
volume = {163},
|
||||
eprint = {http://arxiv.org/abs/1803.09711},
|
||||
doi = {10/gfk5cj},
|
||||
journal = {Energy},
|
||||
author = {Schlachtberger, David P. and Brown, Tom and Schäfer, Mirko and Schramm, Stefan and Greiner, Martin},
|
||||
year = {2018},
|
||||
pages = {100--114},
|
||||
}
|
||||
|
||||
@article{zeyenMitigatingHeat2021,
|
||||
title = {Mitigating heat demand peaks in buildings in a highly renewable {European} energy system},
|
||||
volume = {231},
|
||||
url = {http://arxiv.org/abs/2012.01831},
|
||||
doi = {10.1016/j.energy.2021.120784},
|
||||
journal = {Energy},
|
||||
author = {Zeyen, Elisabeth and Hagenmeyer, Veit and Brown, Tom},
|
||||
year = {2021},
|
||||
pages = {120784},
|
||||
}
|
||||
|
||||
@misc{zeyenEndogenousLearning2022,
|
||||
title = {Endogenous learning for green hydrogen in a sector-coupled energy model for {Europe}},
|
||||
url = {http://arxiv.org/abs/2205.11901},
|
||||
author = {Zeyen, Elisabeth and Victoria, Marta and Brown, Tom},
|
||||
year = {2022},
|
||||
}
|
||||
|
||||
|
||||
|
||||
@article{MILLINGER2022120016,
|
||||
title = {Are biofuel mandates cost-effective? - An analysis of transport fuels and biomass usage to achieve emissions targets in the European energy system},
|
||||
journal = {Applied Energy},
|
||||
volume = {326},
|
||||
pages = {120016},
|
||||
year = {2022},
|
||||
doi = {https://doi.org/10.1016/j.apenergy.2022.120016},
|
||||
author = {M. Millinger and L. Reichenberg and F. Hedenus and G. Berndes and E. Zeyen and T. Brown},
|
||||
}
|
||||
|
||||
@misc{frysztackiInverseMethods2022,
|
||||
title = {Inverse methods: {How} feasible are spatially low-resolved capacity expansion modeling results when dis-aggregated at high resolution?},
|
||||
url = {http://arxiv.org/abs/2209.02364},
|
||||
author = {Frysztacki, Martha Maria and Hagenmeyer, Veit and Brown, Tom},
|
||||
year = {2022},
|
||||
}
|
||||
|
||||
|
||||
|
||||
@article{frysztackiStrongEffect2021a,
|
||||
title = {The strong effect of network resolution on electricity system models with high shares of wind and solar},
|
||||
volume = {291},
|
||||
issn = {03062619},
|
||||
doi = {10.1016/j.apenergy.2021.116726},
|
||||
journal = {Applied Energy},
|
||||
author = {Frysztacki, Martha Maria and Hörsch, Jonas and Hagenmeyer, Veit and Brown, Tom},
|
||||
year = {2021},
|
||||
pages = {116726},
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
@inproceedings{frysztackiModelingCurtailment2020a,
|
||||
title = {Modeling {Curtailment} in {Germany}: {How} {Spatial} {Resolution} {Impacts} {Line} {Congestion}},
|
||||
shorttitle = {Modeling {Curtailment} in {Germany}},
|
||||
doi = {10.1109/EEM49802.2020.9221886},
|
||||
booktitle = {2020 17th {International} {Conference} on the {European} {Energy} {Market} ({EEM})},
|
||||
publisher = {IEEE},
|
||||
author = {Frysztacki, Martha and Brown, Tom},
|
||||
year = {2020},
|
||||
pages = {1--7},
|
||||
}
|
||||
|
||||
|
||||
@article{frysztackiComparisonClustering2022,
|
||||
title = {A comparison of clustering methods for the spatial reduction of renewable electricity optimisation models of {Europe}},
|
||||
volume = {5},
|
||||
url = {https://energyinformatics.springeropen.com/articles/10.1186/s42162-022-00187-7},
|
||||
doi = {10.1186/s42162-022-00187-7},
|
||||
number = {1},
|
||||
journal = {Energy Informatics},
|
||||
author = {Frysztacki, Martha Maria and Recht, Gereon and Brown, Tom},
|
||||
year = {2022},
|
||||
pages = {4},
|
||||
}
|
||||
|
||||
@article{neumannNearoptimalFeasible2021,
|
||||
title = {The near-optimal feasible space of a renewable power system model},
|
||||
volume = {190},
|
||||
doi = {10.1016/j.epsr.2020.106690},
|
||||
journal = {Electric Power Systems Research},
|
||||
author = {Neumann, Fabian and Brown, Tom},
|
||||
year = {2021},
|
||||
pages = {106690},
|
||||
}
|
||||
|
||||
@article{neumannAssessmentsLinear2022,
|
||||
title = {Assessments of linear power flow and transmission loss approximations in coordinated capacity expansion problems},
|
||||
volume = {314},
|
||||
doi = {10.1016/j.apenergy.2022.118859},
|
||||
journal = {Applied Energy},
|
||||
author = {Neumann, Fabian and Hagenmeyer, Veit and Brown, Tom},
|
||||
year = {2022},
|
||||
}
|
||||
|
||||
|
||||
@article{neumannCostsRegional2021,
|
||||
title = {Costs of regional equity and autarky in a renewable {European} power system},
|
||||
volume = {35},
|
||||
doi = {10.1016/j.esr.2021.100652},
|
||||
journal = {Energy Strategy Reviews},
|
||||
author = {Neumann, Fabian},
|
||||
year = {2021},
|
||||
}
|
||||
|
||||
|
||||
@article{roseHydrogenRefueling2020,
|
||||
title = {Hydrogen refueling station networks for heavy-duty vehicles in future power systems},
|
||||
volume = {83},
|
||||
issn = {13619209},
|
||||
doi = {10.1016/j.trd.2020.102358},
|
||||
journal = {Transportation Research Part D: Transport and Environment},
|
||||
author = {Rose, Philipp K. and Neumann, Fabian},
|
||||
year = {2020},
|
||||
pages = {102358},
|
||||
}
|
||||
|
||||
@inproceedings{neumannHeuristicsTransmission2019a,
|
||||
title = {Heuristics for {Transmission} {Expansion} {Planning} in {Low}-{Carbon} {Energy} {System} {Models}},
|
||||
doi = {10.1109/EEM.2019.8916411},
|
||||
booktitle = {2019 16th {International} {Conference} on the {European} {Energy} {Market} ({EEM})},
|
||||
publisher = {IEEE},
|
||||
author = {Neumann, Fabian and Brown, Tom},
|
||||
year = {2019},
|
||||
pages = {1--8},
|
||||
}
|
||||
|
||||
@misc{neumannBroadRanges2021,
|
||||
title = {Broad {Ranges} of {Investment} {Configurations} for {Renewable} {Power} {Systems}, {Robust} to {Cost} {Uncertainty} and {Near}-{Optimality}},
|
||||
url = {http://arxiv.org/abs/2111.14443},
|
||||
author = {Neumann, Fabian and Brown, Tom},
|
||||
year = {2021},
|
||||
}
|
||||
|
||||
@misc{gazafroudiLongTermBenefits2021,
|
||||
title = {Long-{Term} {Benefits} for {Renewables} {Integration} of {Network} {Boosters} for {Corrective} {Grid} {Security}},
|
||||
url = {http://arxiv.org/abs/2112.06667},
|
||||
author = {Gazafroudi, Amin Shokri and Zeyen, Elisabeth and Frysztacki, Martha and Neumann, Fabian and Brown, Tom},
|
||||
year = {2021},
|
||||
}
|
||||
|
||||
|
||||
|
||||
@article{shokrigazafroudiTopologybasedApproximations2022,
|
||||
title = {Topology-based approximations for {N} - 1 contingency constraints in power transmission networks},
|
||||
volume = {137},
|
||||
doi = {10.1016/j.ijepes.2021.107702},
|
||||
journal = {International Journal of Electrical Power \& Energy Systems},
|
||||
author = {Shokri Gazafroudi, Amin and Neumann, Fabian and Brown, Tom},
|
||||
year = {2022},
|
||||
pages = {107702},
|
||||
}
|
||||
|
||||
|
||||
@inproceedings{horschRoleSpatial2017,
|
||||
title = {The role of spatial scale in joint optimisations of generation and transmission for {European} highly renewable scenarios},
|
||||
doi = {10.1109/EEM.2017.7982024},
|
||||
booktitle = {2017 14th {International} {Conference} on the {European} {Energy} {Market} ({EEM})},
|
||||
publisher = {IEEE},
|
||||
author = {Horsch, Jonas and Brown, Tom},
|
||||
year = {2017},
|
||||
pages = {1--7},
|
||||
}
|
||||
|
||||
@article{schlachtbergerBenefitsCooperation2017a,
|
||||
title = {The benefits of cooperation in a highly renewable {European} electricity network},
|
||||
volume = {134},
|
||||
issn = {03605442},
|
||||
doi = {10.1016/j.energy.2017.06.004},
|
||||
journal = {Energy},
|
||||
author = {Schlachtberger, D.P. and Brown, T. and Schramm, S. and Greiner, M.},
|
||||
year = {2017},
|
||||
pages = {469--481},
|
||||
}
|
||||
|
||||
@misc{glaumEnhancingGerman2022,
|
||||
title = {Enhancing the {German} {Transmission} {Grid} {Through} {Dynamic} {Line} {Rating}},
|
||||
url = {http://arxiv.org/abs/2208.04716},
|
||||
author = {Glaum, Philipp and Hofmann, Fabian},
|
||||
year = {2022},
|
||||
}
|
||||
|
||||
@misc{parzenPyPSAEarthNew2022,
|
||||
title = {{PyPSA}-{Earth}. {A} {New} {Global} {Open} {Energy} {System} {Optimization} {Model} {Demonstrated} in {Africa}},
|
||||
url = {http://arxiv.org/abs/2209.04663},
|
||||
author = {Parzen, Maximilian and Abdel-Khalek, Hazem and Fedorova, Ekaterina and Mahmood, Matin and Frysztacki, Martha Maria and Hampp, Johannes and Franken, Lukas and Schumm, Leon and Neumann, Fabian and Poli, Davide and Kiprakis, Aristides and Fioriti, Davide},
|
||||
year = {2022},
|
||||
}
|
||||
11
doc/publications.rst
Normal file
11
doc/publications.rst
Normal file
@ -0,0 +1,11 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
##########################################
|
||||
Publications
|
||||
##########################################
|
||||
|
||||
.. bibliography::
|
||||
:all:
|
||||
@ -10,11 +10,101 @@ Release Notes
|
||||
Upcoming Release
|
||||
================
|
||||
|
||||
* The solver configuration in `config.default.yaml` are now modularized. To change the set of solver options, change to value in `solving`: `solver`: `options` to one of the keys `solving`: `solver_options`.
|
||||
* new feature or bugfix
|
||||
|
||||
|
||||
PyPSA-Eur 0.8.0 (17th March 2023)
|
||||
=================================
|
||||
|
||||
.. note::
|
||||
This is the first release of PyPSA-Eur which incorporates its sector-coupled extension PyPSA-Eur-Sec (v0.7.1).
|
||||
PyPSA-Eur can now directly be used for high-resolution energy system modelling with sector-coupling
|
||||
including industry, transport, buildings, biomass, and detailed carbon management. The PyPSA-Eur-Sec repository is now deprecated.
|
||||
|
||||
* The :mod:`solve_network` script now uses the ``linopy`` backend of PyPSA and is applied for both electricity-only and sector-coupled models. This
|
||||
requires an adjustment of custom ``extra_functionality``.
|
||||
See the `migration guide <https://pypsa.readthedocs.io/en/latest/examples/optimization-with-linopy-migrate-extra-functionalities.html>`_ in the PyPSA documentation.
|
||||
|
||||
* The configuration file ``config.default.yaml`` now also includes settings for
|
||||
sector-coupled models, which will be ignored when the user runs
|
||||
electricity-only studies. Common settings have been aligned.
|
||||
|
||||
* Unified handling of scenario runs. Users can name their scenarios in ``run:
|
||||
name:``, which will encapsulate results in a correspondingly named folder
|
||||
under ``results``. Additionally, users can select to encapsulate the ``resources`` folder
|
||||
in the same way, through the setting ``run: shared_resources:``.
|
||||
|
||||
* The solver configurations in ``config.default.yaml`` are now modularized. To
|
||||
change the set of solver options, change to value in ``solving: solver:
|
||||
options:`` to one of the keys in ``solving: solver_options:``.
|
||||
|
||||
* The ``Snakefile`` has been modularised. Rules are now organised in the
|
||||
``rules`` directory.
|
||||
|
||||
* Unified wildcard for transmission line expansion from ``{lv}`` and ``{ll}`` to
|
||||
``{ll}``.
|
||||
|
||||
* Renamed collection rules to distinguish between sector-coupled and
|
||||
electricity-only runs: ``cluster_networks``, ``extra_components_networks``,
|
||||
``prepare_elec_networks``, ``prepare_sector_networks``,
|
||||
``solve_elec_networks``, ``solve_sector_networks``, ``plot_networks``,
|
||||
``all``.
|
||||
|
||||
* Some rules with a small computational footprint have been declared as ``localrules``.
|
||||
|
||||
* Added new utility rules ``purge`` for clearing workflow outputs from the
|
||||
directory, ``doc`` to build the documentation, and ``dag`` to create a
|
||||
workflow graph.
|
||||
|
||||
* The workflow can now be used with the ``snakemake --use-conda`` directive. In
|
||||
this way, Snakemake can automatically handle the installation of dependencies.
|
||||
|
||||
* Data retrieval rules now retry download twice in case of connection problems.
|
||||
|
||||
* The cutouts are now marked as ``protected()`` in the workflow to avoid
|
||||
accidental recomputation.
|
||||
|
||||
* The files contained in ``data/bundle`` are now marked as ``ancient()`` as they
|
||||
are not expected to be altered by workflow changes.
|
||||
|
||||
* Preparation scripts for sector-coupled models have been improved to only run
|
||||
for the subset of selected countries rather than all European countries.
|
||||
|
||||
* Added largely automated country code conversion using ``country_converter``..
|
||||
|
||||
* Test coverage extended to an electricity-only run and sector-coupled runs for
|
||||
overnight and myopic foresight scenarios for Ubuntu, MacOS and Windows.
|
||||
|
||||
* Apply ``black`` and ``snakefmt`` code formatting.
|
||||
|
||||
* Implemented REUSE compatibility for merged code.
|
||||
|
||||
* Merged documentations of PyPSA-Eur and PyPSA-Eur-Sec.
|
||||
|
||||
* Added a tutorial for running sector-coupled models to the documentation
|
||||
(:ref:`tutorial_sector`).
|
||||
|
||||
* Deleted ``config.tutorial.yaml``, which is superseded by
|
||||
``test/config.electricity.yaml``.
|
||||
|
||||
* The ``mock_snakemake`` function now also takes configuration files as inputs.
|
||||
|
||||
* The helper scripts ``helper.py`` and ``_helpers.py`` have been merged into
|
||||
``_helpers.py``.
|
||||
|
||||
* The unused rule ``plot_p_nom_max`` has been removed.
|
||||
|
||||
* The rule ``solve_network`` from PyPSA-Eur-Sec was renamed to
|
||||
``solve_sector_network``.
|
||||
|
||||
* The plotting scripts from PyPSA-Eur (electricity-only) have been removed and
|
||||
are superseded by those from PyPSA-Eur-Sec (sector-coupled).
|
||||
|
||||
PyPSA-Eur Releases (pre-merge)
|
||||
==============================
|
||||
|
||||
PyPSA-Eur 0.7.0 (16th February 2023)
|
||||
====================================
|
||||
------------------------------------
|
||||
|
||||
|
||||
**New Features**
|
||||
@ -87,7 +177,7 @@ PyPSA-Eur 0.7.0 (16th February 2023)
|
||||
|
||||
|
||||
PyPSA-Eur 0.6.1 (20th September 2022)
|
||||
=====================================
|
||||
-------------------------------------
|
||||
|
||||
* Individual commits are now tested against pre-commit hooks. This includes
|
||||
black style formatting, sorting of package imports, Snakefile formatting and
|
||||
@ -110,7 +200,7 @@ PyPSA-Eur 0.6.1 (20th September 2022)
|
||||
efficiency into account where available.
|
||||
|
||||
PyPSA-Eur 0.6.0 (10th September 2022)
|
||||
=====================================
|
||||
-------------------------------------
|
||||
|
||||
* Functionality to consider shipping routes when calculating the available area
|
||||
for offshore technologies were added. Data for the shipping density comes from
|
||||
@ -131,7 +221,7 @@ PyPSA-Eur 0.6.0 (10th September 2022)
|
||||
|
||||
|
||||
PyPSA-Eur 0.5.0 (27th July 2022)
|
||||
=====================================
|
||||
--------------------------------
|
||||
|
||||
**New Features**
|
||||
|
||||
@ -289,7 +379,7 @@ PyPSA-Eur 0.5.0 (27th July 2022)
|
||||
|
||||
|
||||
Synchronisation Release - Ukraine and Moldova (17th March 2022)
|
||||
===============================================================
|
||||
---------------------------------------------------------------
|
||||
|
||||
On March 16, 2022, the transmission networks of Ukraine and Moldova have
|
||||
successfully been `synchronised with the continental European grid <https://www.entsoe.eu/news/2022/03/16/continental-europe-successful-synchronisation-with-ukraine-and-moldova-power-systems/>`_. We have taken
|
||||
@ -324,7 +414,7 @@ This release is not on the ``master`` branch. It can be used with
|
||||
|
||||
|
||||
PyPSA-Eur 0.4.0 (22th September 2021)
|
||||
=====================================
|
||||
-------------------------------------
|
||||
|
||||
**New Features and Changes**
|
||||
|
||||
@ -439,11 +529,11 @@ PyPSA-Eur 0.4.0 (22th September 2021)
|
||||
in the Snakemake file [`#247 <https://github.com/PyPSA/pypsa-eur/pull/247>`_]
|
||||
|
||||
PyPSA-Eur 0.3.0 (7th December 2020)
|
||||
===================================
|
||||
-----------------------------------
|
||||
|
||||
**New Features**
|
||||
|
||||
Using the ``{opts}`` wildcard for scenarios:
|
||||
Using the ``{opts}`` wildcard for scenario:
|
||||
|
||||
* An option is introduced which adds constraints such that each country or node produces on average a minimal share of its total consumption itself.
|
||||
For example ``EQ0.5c`` set in the ``{opts}`` wildcard requires each country to produce on average at least 50% of its consumption. Additionally,
|
||||
@ -539,7 +629,7 @@ Other:
|
||||
|
||||
|
||||
PyPSA-Eur 0.2.0 (8th June 2020)
|
||||
==================================
|
||||
-------------------------------
|
||||
|
||||
* The optimization is now performed using the ``pyomo=False`` setting in the :func:`pypsa.lopf.network_lopf`. This speeds up the solving process significantly and consumes much less memory. The inclusion of additional constraints were adjusted to the new implementation. They are all passed to the :func:`network_lopf` function via the ``extra_functionality`` argument. The rule ``trace_solve_network`` was integrated into the rule :mod:`solve_network` and can be activated via configuration with ``solving: options: track_iterations: true``. The charging and discharging capacities of batteries modelled as store-link combination are now coupled [`#116 <https://github.com/PyPSA/pypsa-eur/pull/116>`_].
|
||||
|
||||
@ -572,7 +662,7 @@ PyPSA-Eur 0.2.0 (8th June 2020)
|
||||
* Updated ``conda`` environment regarding ``pypsa``, ``pyproj``, ``gurobi``, ``lxml``. This release requires PyPSA v0.17.0.
|
||||
|
||||
PyPSA-Eur 0.1.0 (9th January 2020)
|
||||
==================================
|
||||
----------------------------------
|
||||
|
||||
This is the first release of PyPSA-Eur, a model of the European power system at the transmission network level. Recent changes include:
|
||||
|
||||
@ -588,7 +678,7 @@ This is the first release of PyPSA-Eur, a model of the European power system at
|
||||
|
||||
* Data dependencies are now retrieved directly from within the snakemake workflow [`#86 <https://github.com/PyPSA/pypsa-eur/pull/86>`_].
|
||||
|
||||
* Emission prices can be added to marginal costs of generators through the keyworks ``Ep`` in the ``{opts}`` wildcard [`#100 <https://github.com/PyPSA/pypsa-eur/pull/100>`_].
|
||||
* Emission prices can be added to marginal costs of generators through the keywords ``Ep`` in the ``{opts}`` wildcard [`#100 <https://github.com/PyPSA/pypsa-eur/pull/100>`_].
|
||||
|
||||
* An option is introduced to add extendable nuclear power plants to the network [`#98 <https://github.com/PyPSA/pypsa-eur/pull/98>`_].
|
||||
|
||||
@ -602,6 +692,566 @@ This is the first release of PyPSA-Eur, a model of the European power system at
|
||||
|
||||
* The new function ``_helpers.mock_snakemake`` creates a ``snakemake`` object which mimics the actual ``snakemake`` object produced by workflow by parsing the ``Snakefile`` and setting all paths for inputs, outputs, and logs. This allows running all scripts within a (I)python terminal (or just by calling ``python <script-name>``) and thereby facilitates developing and debugging scripts significantly [`#107 <https://github.com/PyPSA/pypsa-eur/pull/107>`_].
|
||||
|
||||
|
||||
PyPSA-Eur-Sec Releases (pre-merge)
|
||||
==================================
|
||||
|
||||
PyPSA-Eur-Sec 0.7.0 (16th February 2023)
|
||||
----------------------------------------
|
||||
|
||||
This release includes many new features. Highlights include new gas
|
||||
infrastructure data with retrofitting options for hydrogen transport, improved
|
||||
carbon management and infrastructure planning, regionalised potentials for
|
||||
hydrogen underground storage and carbon sequestration, new applications for
|
||||
biomass, and explicit modelling of methanol and ammonia as separate energy
|
||||
carriers.
|
||||
|
||||
This release is known to work with `PyPSA-Eur
|
||||
<https://github.com/PyPSA/pypsa-eur>`_ Version 0.7.0 and `Technology Data
|
||||
<https://github.com/PyPSA/technology-data>`_ Version 0.5.0.
|
||||
|
||||
**Gas Transmission Network**
|
||||
|
||||
* New rule ``retrieve_gas_infrastructure_data`` that downloads and extracts the
|
||||
SciGRID_gas `IGGIELGN <https://zenodo.org/record/4767098>`_ dataset from
|
||||
zenodo. It includes data on the transmission routes, pipe diameters,
|
||||
capacities, pressure, and whether the pipeline is bidirectional and carries
|
||||
H-Gas or L-Gas.
|
||||
|
||||
* New rule ``build_gas_network`` processes and cleans the pipeline data from
|
||||
SciGRID_gas. Missing or uncertain pipeline capacities can be inferred by
|
||||
diameter.
|
||||
|
||||
* New rule ``build_gas_input_locations`` compiles the LNG import capacities
|
||||
(from the Global Energy Monitor's `Europe Gas Tracker
|
||||
<https://globalenergymonitor.org/projects/europe-gas-tracker/>`_, pipeline
|
||||
entry capacities and local production capacities for each region of the model.
|
||||
These are the regions where fossil gas can eventually enter the model.
|
||||
|
||||
* New rule ``cluster_gas_network`` that clusters the gas transmission network
|
||||
data to the model resolution. Cross-regional pipeline capacities are
|
||||
aggregated (while pressure and diameter compatibility is ignored),
|
||||
intra-regional pipelines are dropped. Lengths are recalculated based on the
|
||||
regions' centroids.
|
||||
|
||||
* With the option ``sector: gas_network:``, the existing gas network is added
|
||||
with a lossless transport model. A length-weighted `k-edge augmentation
|
||||
algorithm
|
||||
<https://networkx.org/documentation/stable/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation.html#networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation>`_
|
||||
can be run to add new candidate gas pipelines such that all regions of the
|
||||
model can be connected to the gas network. The number of candidates can be
|
||||
controlled via the setting ``sector: gas_network_connectivity_upgrade:``. When
|
||||
the gas network is activated, all the gas demands are regionally disaggregated
|
||||
as well.
|
||||
|
||||
* New constraint allows endogenous retrofitting of gas pipelines to hydrogen
|
||||
pipelines. This option is activated via the setting ``sector: H2_retrofit:``.
|
||||
For every unit of gas pipeline capacity dismantled, ``sector:
|
||||
H2_retrofit_capacity_per_CH4`` units are made available as hydrogen pipeline
|
||||
capacity in the corresponding corridor. These repurposed hydrogen pipelines
|
||||
have lower costs than new hydrogen pipelines. Both new and repurposed
|
||||
pipelines can be built simultaneously. The retrofitting option ``sector:
|
||||
H2_retrofit:`` also works with a copperplated methane infrastructure, i.e.
|
||||
when ``sector: gas_network: false``.
|
||||
|
||||
* New hydrogen pipelines can now be built where there are already power or gas
|
||||
transmission routes. Previously, only the electricity transmission routes were
|
||||
considered.
|
||||
|
||||
**Carbon Management and Biomass**
|
||||
|
||||
* Add option to spatially resolve carrier representing stored carbon dioxide
|
||||
(``co2_spatial``). This allows for more detailed modelling of CCUTS, e.g.
|
||||
regarding the capturing of industrial process emissions, usage as feedstock
|
||||
for electrofuels, transport of carbon dioxide, and geological sequestration
|
||||
sites.
|
||||
|
||||
* Add option for regionally-resolved geological carbon dioxide sequestration
|
||||
potentials through new rule ``build_sequestration_potentials`` based on
|
||||
`CO2StoP <https://setis.ec.europa.eu/european-co2-storage-database_en>`_. This
|
||||
can be controlled in the section ``regional_co2_sequestration_potential`` of
|
||||
the ``config.yaml``. It includes options to select the level of conservatism,
|
||||
whether onshore potentials should be included, the respective upper and lower
|
||||
limits per region, and an annualisation parameter for the cumulative
|
||||
potential. The defaults are preliminary and will be validated the next
|
||||
release.
|
||||
|
||||
* Add option to sweep the global CO2 sequestration potentials with keyword
|
||||
``seq200`` in the ``{sector_opts}`` wildcard (for limit of 200 Mt CO2).
|
||||
|
||||
* Add option to include `Allam cycle gas power plants
|
||||
<https://en.wikipedia.org/wiki/Allam_power_cycle>`_ (``allam_cycle``).
|
||||
|
||||
* Add option for planning a new carbon dioxide network (``co2network``).
|
||||
|
||||
* Separate option to regionally resolve biomass (``biomass_spatial``) from
|
||||
option to allow biomass transport (``biomass_transport``).
|
||||
|
||||
* Add option for biomass boilers (wood pellets) for decentral heating.
|
||||
|
||||
* Add option for BioSNG (methane from biomass) with and without carbon capture.
|
||||
|
||||
* Add option for BtL (biomass to liquid fuel/oil) with and without carbon
|
||||
capture.
|
||||
|
||||
|
||||
**Other new features**
|
||||
|
||||
* Add regionalised hydrogen salt cavern storage potentials from `Technical
|
||||
Potential of Salt Caverns for Hydrogen Storage in Europe
|
||||
<https://doi.org/10.20944/preprints201910.0187.v1>`_. This data is compiled in
|
||||
a new rule ``build_salt_cavern_potentials``.
|
||||
|
||||
* Add option to resolve ammonia as separate energy carrier with Haber-Bosch
|
||||
synthesis, ammonia cracking, storage and industrial demand. The ammonia
|
||||
carrier can be nodally resolved or copperplated across Europe (see
|
||||
``ammonia``).
|
||||
|
||||
* Add methanol as energy carrier, methanolisation as process, and option for
|
||||
methanol demand in shipping sector.
|
||||
|
||||
* Shipping demand now defaults to methanol rather than liquefied hydrogen
|
||||
until 2050.
|
||||
|
||||
* Demand for liquid hydrogen in international shipping is now geographically
|
||||
distributed by port trade volumes in a new rule ``build_shipping_demand``
|
||||
using data from the `World Bank Data Catalogue
|
||||
<https://datacatalog.worldbank.org/search/dataset/0038118/Global---International-Ports>`_.
|
||||
Domestic shipping remains distributed by population.
|
||||
|
||||
* Add option to aggregate network temporally using representative snapshots or
|
||||
segments (with `tsam <https://github.com/FZJ-IEK3-VSA/tsam>`_).
|
||||
|
||||
* Add option for minimum part load for Fischer-Tropsch plants (default: 90%) and
|
||||
methanolisation plants (default: 50%).
|
||||
|
||||
* Add option to use waste heat of electrolysis in district heating networks
|
||||
(``use_electrolysis_waste_heat``).
|
||||
|
||||
* Add option for coal CHPs with carbon capture (see ``coal_cc``).
|
||||
|
||||
* In overnight optimisation, it is now possible to specify a year for the
|
||||
technology cost projections separate from the planning horizon.
|
||||
|
||||
* New config options for changing energy demands in aviation
|
||||
(``aviation_demand_factor``) and HVC industry (``HVC_demand_factor``), as well
|
||||
as explicit ICE shares for land transport (``land_transport_ice_share``) and
|
||||
agriculture machinery (``agriculture_machinery_oil_share``).
|
||||
|
||||
* It is now possible to merge residential and services heat buses to reduce the
|
||||
problem size (see ``cluster_heat_nodes``).
|
||||
|
||||
* Added option to tweak (almost) any configuration parameter through the
|
||||
``{sector_opts}`` wildcard. The regional_co2_sequestration_potential is
|
||||
triggered by the prefix ``CF+`` after which it is possible to pipe to any
|
||||
setting that does not contain underscores (``_``). Example:
|
||||
``CF+sector+v2g+false`` disables vehicle-to-grid flexibility.
|
||||
|
||||
* Option ``retrieve_sector_databundle`` to automatically retrieve and extract
|
||||
data bundle.
|
||||
|
||||
* Removed the need to clone ``technology-data`` repository in a parallel
|
||||
directory. The new approach automatically retrieves the technology data from
|
||||
remote in the rule ``retrieve_cost_data``.
|
||||
|
||||
* Improved network plots including better legends, hydrogen retrofitting network
|
||||
display, and change to EqualEarth projection. A new color scheme for
|
||||
technologies was also introduced.
|
||||
|
||||
* Add two new rules ``build_transport_demand`` and
|
||||
``build_population_weighted_energy_totals`` using code previously contained in
|
||||
``prepare_sector_network``.
|
||||
|
||||
* Rules that convert weather data with ``atlite`` now largely run separately for
|
||||
categories residential, rural and total.
|
||||
|
||||
* Units are assigned to the buses. These only provide a better understanding.
|
||||
The specifications of the units are not taken into account in the
|
||||
optimisation, which means that no automatic conversion of units takes place.
|
||||
|
||||
* Configuration file and wildcards are now stored under ``n.meta`` in every
|
||||
PyPSA network.
|
||||
|
||||
* Updated `data bundle
|
||||
<https://zenodo.org/record/5824485/files/pypsa-eur-sec-data-bundle.tar.gz>`_
|
||||
that includes the hydrogan salt cavern storage potentials.
|
||||
|
||||
* Updated and extended documentation in
|
||||
<https://pypsa-eur-sec.readthedocs.io/en/latest/>
|
||||
|
||||
* Added new rule ``copy_conda_env`` that exports a list of packages with which
|
||||
the workflow was executed.
|
||||
|
||||
* Add basic continuous integration using Github Actions.
|
||||
|
||||
* Add basic ``rsync`` setup.
|
||||
|
||||
**Bugfixes**
|
||||
|
||||
* The CO2 sequestration limit implemented as GlobalConstraint (introduced in the
|
||||
previous version) caused a failure to read in the shadow prices of other
|
||||
global constraints.
|
||||
|
||||
* Correct capital cost of Fischer-Tropsch according to new units in
|
||||
``technology-data`` repository.
|
||||
|
||||
* Fix unit conversion error for thermal energy storage.
|
||||
|
||||
* For myopic pathway optimisation, set optimised capacities of power grid
|
||||
expansion of previous iteration as minimum capacity for next iteration.
|
||||
|
||||
* Further rather minor bugfixes for myopic optimisation code (see `#256
|
||||
<https://github.com/PyPSA/pypsa-eur-sec/pull/256>`_).
|
||||
|
||||
|
||||
Many thanks to all who contributed to this release!
|
||||
|
||||
|
||||
PyPSA-Eur-Sec 0.6.0 (4 October 2021)
|
||||
------------------------------------
|
||||
|
||||
This release includes
|
||||
improvements regarding the basic chemical production,
|
||||
the addition of plastics recycling,
|
||||
the addition of the agriculture, forestry and fishing sector,
|
||||
more regionally resolved biomass potentials,
|
||||
CO2 pipeline transport and storage, and
|
||||
more options in setting exogenous transition paths,
|
||||
besides many performance improvements.
|
||||
|
||||
This release is known to work with `PyPSA-Eur
|
||||
<https://github.com/PyPSA/pypsa-eur>`_ Version 0.4.0, `Technology Data
|
||||
<https://github.com/PyPSA/technology-data>`_ Version 0.3.0 and
|
||||
`PyPSA <https://github.com/PyPSA/PyPSA>`_ Version 0.18.0.
|
||||
|
||||
Please note that the data bundle has also been updated.
|
||||
|
||||
|
||||
**General**
|
||||
|
||||
* With this release, we change the license from copyleft GPLv3 to the more
|
||||
liberal MIT license with the consent of all contributors.
|
||||
|
||||
|
||||
**New features and functionality**
|
||||
|
||||
* Distinguish costs for home battery storage and inverter from utility-scale
|
||||
battery costs.
|
||||
|
||||
* Separate basic chemicals into HVC (high-value chemicals), chlorine, methanol and ammonia
|
||||
[`#166 <https://github.com/PyPSA/PyPSA-Eur-Sec/pull/166>`_].
|
||||
|
||||
* Add option to specify reuse, primary production, and mechanical and chemical
|
||||
recycling fraction of platics
|
||||
[`#166 <https://github.com/PyPSA/PyPSA-Eur-Sec/pull/166>`_].
|
||||
|
||||
* Include energy demands and CO2 emissions for the agriculture, forestry and fishing sector.
|
||||
It is included by default through the option ``A`` in the ``sector_opts`` wildcard.
|
||||
Part of the emissions (1.A.4.c) was previously assigned to "industry non-elec" in the ``co2_totals.csv``.
|
||||
Hence, excluding the agriculture sector will now lead to a tighter CO2 limit.
|
||||
Energy demands are taken from the JRC IDEES database (missing countries filled with eurostat data)
|
||||
and are split into
|
||||
electricity (lighting, ventilation, specific electricity uses, pumping devices (electric)),
|
||||
heat (specific heat uses, low enthalpy heat)
|
||||
machinery oil (motor drives, farming machine drives, pumping devices (diesel)).
|
||||
Heat demand is assigned at "services rural heat" buses.
|
||||
Electricity demands are added to low-voltage buses.
|
||||
Time series for demands are constant and distributed inside countries by population
|
||||
[`#147 <https://github.com/PyPSA/PyPSA-Eur-Sec/pull/147>`_].
|
||||
|
||||
* Include today's district heating shares in myopic optimisation and add option
|
||||
to specify exogenous path for district heating share increase under ``sector:
|
||||
district_heating:`` [`#149 <https://github.com/PyPSA/PyPSA-Eur-Sec/pull/149>`_].
|
||||
|
||||
* Added option for hydrogen liquefaction costs for hydrogen demand in shipping.
|
||||
This introduces a new ``H2 liquid`` bus at each location. It is activated via
|
||||
``sector: shipping_hydrogen_liquefaction: true``.
|
||||
|
||||
* The share of shipping transformed into hydrogen fuel cell can be now defined
|
||||
for different years in the ``config.yaml`` file. The carbon emission from the
|
||||
remaining share is treated as a negative load on the atmospheric carbon dioxide
|
||||
bus, just like aviation and land transport emissions.
|
||||
|
||||
* The transformation of the Steel and Aluminium production can be now defined
|
||||
for different years in the ``config.yaml`` file.
|
||||
|
||||
* Include the option to alter the maximum energy capacity of a store via the
|
||||
``carrier+factor`` in the ``{sector_opts}`` wildcard. This can be useful for
|
||||
sensitivity analyses. Example: ``co2 stored+e2`` multiplies the ``e_nom_max`` by
|
||||
factor 2. In this example, ``e_nom_max`` represents the CO2 sequestration
|
||||
potential in Europe.
|
||||
|
||||
* Use `JRC ENSPRESO database <https://data.jrc.ec.europa.eu/dataset/74ed5a04-7d74-4807-9eab-b94774309d9f>`_ to
|
||||
spatially disaggregate biomass potentials to PyPSA-Eur regions based on
|
||||
overlaps with NUTS2 regions from ENSPRESO (proportional to area) (`#151
|
||||
<https://github.com/PyPSA/pypsa-eur-sec/pull/151>`_).
|
||||
|
||||
* Add option to regionally disaggregate biomass potential to individual nodes
|
||||
(previously given per country, then distributed by population density within)
|
||||
and allow the transport of solid biomass. The transport costs are determined
|
||||
based on the `JRC-EU-Times Bioenergy report
|
||||
<http://dx.doi.org/10.2790/01017>`_ in the new optional rule
|
||||
``build_biomass_transport_costs``. Biomass transport can be activated with the
|
||||
setting ``sector: biomass_transport: true``.
|
||||
|
||||
* Add option to regionally resolve CO2 storage and add CO2 pipeline transport
|
||||
because geological storage potential,
|
||||
CO2 utilisation sites and CO2 capture sites may be separated. The CO2 network
|
||||
is built from zero based on the topology of the electricity grid (greenfield).
|
||||
Pipelines are assumed to be bidirectional and lossless. Furthermore, neither
|
||||
retrofitting of natural gas pipelines (required pressures are too high, 80-160
|
||||
bar vs <80 bar) nor other modes of CO2 transport (by ship, road or rail) are
|
||||
considered. The regional representation of CO2 is activated with the config
|
||||
setting ``sector: co2_network: true`` but is deactivated by default. The
|
||||
global limit for CO2 sequestration now applies to the sum of all CO2 stores
|
||||
via an ``extra_functionality`` constraint.
|
||||
|
||||
* The myopic option can now be used together with different clustering for the
|
||||
generators and the network. The existing renewable capacities are split evenly
|
||||
among the regions in every country [`#144 <https://github.com/PyPSA/PyPSA-Eur-Sec/pull/144>`_].
|
||||
|
||||
* Add optional function to use ``geopy`` to locate entries of the Hotmaps
|
||||
database of industrial sites with missing location based on city and country,
|
||||
which reduces missing entries by half. It can be activated by setting
|
||||
``industry: hotmaps_locate_missing: true``, takes a few minutes longer, and
|
||||
should only be used if spatial resolution is coarser than city level.
|
||||
|
||||
|
||||
**Performance and Structure**
|
||||
|
||||
* Extended use of ``multiprocessing`` for much better performance
|
||||
(from up to 20 minutes to less than one minute).
|
||||
|
||||
* Handle most input files (or base directories) via ``snakemake.input``.
|
||||
|
||||
* Use of ``mock_snakemake`` from PyPSA-Eur.
|
||||
|
||||
* Update ``solve_network`` rule to match implementation in PyPSA-Eur by using
|
||||
``n.ilopf()`` and remove outdated code using ``pyomo``.
|
||||
Allows the new setting to skip iterated impedance updates with ``solving:
|
||||
options: skip_iterations: true``.
|
||||
|
||||
* The component attributes that are to be overridden are now stored in the folder
|
||||
``data/override_component_attrs`` analogous to ``pypsa/component_attrs``.
|
||||
This reduces verbosity and also allows circumventing the ``n.madd()`` hack
|
||||
for individual components with non-default attributes.
|
||||
This data is also tracked in the Snakefile.
|
||||
A function ``helper.override_component_attrs`` was added that loads this data
|
||||
and can pass the overridden component attributes into ``pypsa.Network()``.
|
||||
|
||||
* Add various parameters to ``config.default.yaml`` which were previously hardcoded inside the scripts
|
||||
(e.g. energy reference years, BEV settings, solar thermal collector models, geomap colours).
|
||||
|
||||
* Removed stale industry demand rules ``build_industrial_energy_demand_per_country``
|
||||
and ``build_industrial_demand``. These are superseded with more regionally resolved rules.
|
||||
|
||||
* Use simpler and shorter ``gdf.sjoin()`` function to allocate industrial sites
|
||||
from the Hotmaps database to onshore regions.
|
||||
This change also fixes a bug:
|
||||
The previous version allocated sites to the closest bus,
|
||||
but at country borders (where Voronoi cells are distorted by the borders),
|
||||
this had resulted in e.g. a Spanish site close to the French border
|
||||
being wrongly allocated to the French bus if the bus center was closer.
|
||||
|
||||
* Retrofitting rule is now only triggered if endogeneously optimised.
|
||||
|
||||
* Show progress in build rules with ``tqdm`` progress bars.
|
||||
|
||||
* Reduced verbosity of ``Snakefile`` through directory prefixes.
|
||||
|
||||
* Improve legibility of ``config.default.yaml`` and remove unused options.
|
||||
|
||||
* Use the country-specific time zone mappings from ``pytz`` rather than a manual mapping.
|
||||
|
||||
* A function ``add_carrier_buses()`` was added to the ``prepare_network`` rule to reduce code duplication.
|
||||
|
||||
* In the ``prepare_network`` rule the cost and potential adjustment was moved into an
|
||||
own function ``maybe_adjust_costs_and_potentials()``.
|
||||
|
||||
* Use ``matplotlibrc`` to set the default plotting style and backend.
|
||||
|
||||
* Added benchmark files for each rule.
|
||||
|
||||
* Consistent use of ``__main__`` block and further unspecific code cleaning.
|
||||
|
||||
* Updated data bundle and moved data bundle to zenodo.org (`10.5281/zenodo.5546517 <https://doi.org/10.5281/zenodo.5546517>`_).
|
||||
|
||||
|
||||
**Bugfixes and Compatibility**
|
||||
|
||||
* Compatibility with ``atlite>=0.2``. Older versions of ``atlite`` will no longer work.
|
||||
|
||||
* Corrected calculation of "gas for industry" carbon capture efficiency.
|
||||
|
||||
* Implemented changes to ``n.snapshot_weightings`` in PyPSA v0.18.0.
|
||||
|
||||
* Compatibility with ``xarray`` version 0.19.
|
||||
|
||||
* New dependencies: ``tqdm``, ``atlite>=0.2.4``, ``pytz`` and ``geopy`` (optional).
|
||||
These are included in the environment specifications of PyPSA-Eur v0.4.0.
|
||||
|
||||
Many thanks to all who contributed to this release!
|
||||
|
||||
|
||||
PyPSA-Eur-Sec 0.5.0 (21st May 2021)
|
||||
-----------------------------------
|
||||
|
||||
This release includes improvements to the cost database for building retrofits, carbon budget management and wildcard settings, as well as an important bugfix for the emissions from land transport.
|
||||
|
||||
This release is known to work with `PyPSA-Eur <https://github.com/PyPSA/pypsa-eur>`_ Version 0.3.0 and `Technology Data <https://github.com/PyPSA/technology-data>`_ Version 0.2.0.
|
||||
|
||||
Please note that the data bundle has also been updated.
|
||||
|
||||
New features and bugfixes:
|
||||
|
||||
* The cost database for retrofitting of the thermal envelope of buildings has been updated. Now, for calculating the space heat savings of a building, losses by thermal bridges and ventilation are included as well as heat gains (internal and by solar radiation). See the section :ref:`retro` for more details on the retrofitting module.
|
||||
* For the myopic investment option, a carbon budget and a type of decay (exponential or beta) can be selected in the ``config.yaml`` file to distribute the budget across the ``planning_horizons``. For example, ``cb40ex0`` in the ``{sector_opts}`` wildcard will distribute a carbon budget of 40 GtCO2 following an exponential decay with initial growth rate 0.
|
||||
* Added an option to alter the capital cost or maximum capacity of carriers by a factor via ``carrier+factor`` in the ``{sector_opts}`` wildcard. This can be useful for exploring uncertain cost parameters. Example: ``solar+c0.5`` reduces the ``capital_cost`` of solar to 50\% of original values. Similarly ``solar+p3`` multiplies the ``p_nom_max`` by 3.
|
||||
* Rename the bus for European liquid hydrocarbons from ``Fischer-Tropsch`` to ``EU oil``, since it can be supplied not just with the Fischer-Tropsch process, but also with fossil oil.
|
||||
* Bugfix: The new separation of land transport by carrier in Version 0.4.0 failed to account for the carbon dioxide emissions from internal combustion engines in land transport. This is now treated as a negative load on the atmospheric carbon dioxide bus, just like aviation emissions.
|
||||
* Bugfix: Fix reading in of ``pypsa-eur/resources/powerplants.csv`` to PyPSA-Eur Version 0.3.0 (use column attribute name ``DateIn`` instead of old ``YearDecommissioned``).
|
||||
* Bugfix: Make sure that ``Store`` components (battery and H2) are also removed from PyPSA-Eur, so they can be added later by PyPSA-Eur-Sec.
|
||||
|
||||
Thanks to Lisa Zeyen (KIT) for the retrofitting improvements and Marta Victoria (Aarhus University) for the carbon budget and wildcard management.
|
||||
|
||||
PyPSA-Eur-Sec 0.4.0 (11th December 2020)
|
||||
----------------------------------------
|
||||
|
||||
This release includes a more accurate nodal disaggregation of industry demand within each country, fixes to CHP and CCS representations, as well as changes to some configuration settings.
|
||||
|
||||
It has been released to coincide with `PyPSA-Eur <https://github.com/PyPSA/pypsa-eur>`_ Version 0.3.0 and `Technology Data <https://github.com/PyPSA/technology-data>`_ Version 0.2.0, and is known to work with these releases.
|
||||
|
||||
New features:
|
||||
|
||||
* The `Hotmaps Industrial Database <https://gitlab.com/hotmaps/industrial_sites/industrial_sites_Industrial_Database>`_ is used to disaggregate the industrial demand spatially to the nodes inside each country (previously it was distributed by population density).
|
||||
* Electricity demand from industry is now separated from the regular electricity demand and distributed according to the industry demand. Only the remaining regular electricity demand for households and services is distributed according to GDP and population.
|
||||
* A cost database for the retrofitting of the thermal envelope of residential and services buildings has been integrated, as well as endogenous optimisation of the level of retrofitting. This is described in the paper `Mitigating heat demand peaks in buildings in a highly renewable European energy system <https://arxiv.org/abs/2012.01831>`_. Retrofitting can be activated both exogenously and endogenously from the ``config.yaml``.
|
||||
* The biomass and gas combined heat and power (CHP) parameters ``c_v`` and ``c_b`` were read in assuming they were extraction plants rather than back pressure plants. The data is now corrected in `Technology Data <https://github.com/PyPSA/technology-data>`_ Version 0.2.0 to the correct DEA back pressure assumptions and they are now implemented as single links with a fixed ratio of electricity to heat output (even as extraction plants, they were always sitting on the backpressure line in simulations, so there was no point in modelling the full heat-electricity feasibility polygon). The old assumptions underestimated the heat output.
|
||||
* The Danish Energy Agency released `new assumptions for carbon capture <https://ens.dk/en/our-services/projections-and-models/technology-data/technology-data-industrial-process-heat-and>`_ in October 2020, which have now been incorporated in PyPSA-Eur-Sec, including direct air capture (DAC) and post-combustion capture on CHPs, cement kilns and other industrial facilities. The electricity and heat demand for DAC is modelled for each node (with heat coming from district heating), but currently the electricity and heat demand for industrial capture is not modelled very cleanly (for process heat, 10% of the energy is assumed to go to carbon capture) - a new issue will be opened on this.
|
||||
* Land transport is separated by energy carrier (fossil, hydrogen fuel cell electric vehicle, and electric vehicle), but still needs to be separated into heavy and light vehicles (the data is there, just not the code yet).
|
||||
* For assumptions that change with the investment year, there is a new time-dependent format in the ``config.yaml`` using a dictionary with keys for each year. Implemented examples include the CO2 budget, exogenous retrofitting share and land transport energy carrier; more parameters will be dynamised like this in future.
|
||||
* Some assumptions have been moved out of the code and into the ``config.yaml``, including the carbon sequestration potential and cost, the heat pump sink temperature, reductions in demand for high value chemicals, and some BEV DSM parameters and transport efficiencies.
|
||||
* Documentation on :doc:`supply_demand` options has been added.
|
||||
|
||||
Many thanks to Fraunhofer ISI for opening the hotmaps database and to Lisa Zeyen (KIT) for implementing the building retrofitting.
|
||||
|
||||
|
||||
PyPSA-Eur-Sec 0.3.0 (27th September 2020)
|
||||
-----------------------------------------
|
||||
|
||||
This releases focuses on improvements to industry demand and the generation of intermediate files for demand for basic materials. There are still inconsistencies with CCS and waste management that need to be improved.
|
||||
|
||||
It is known to work with PyPSA-Eur v0.1.0 (commit bb3477cd69), PyPSA v0.17.1 and technology-data v0.1.0. Please note that the data bundle has also been updated.
|
||||
|
||||
|
||||
New features:
|
||||
|
||||
* In previous version of PyPSA-Eur-Sec the energy demand for industry was calculated directly for each location. Now, instead, the production of each material (steel, cement, aluminium) at each location is calculated as an intermediate data file, before the energy demand is calculated from it. This allows us in future to have competing industrial processes for supplying the same material demand.
|
||||
* The script ``build_industrial_production_per_country_tomorrow.py`` determines the future industrial production of materials based on today's levels as well as assumed recycling and demand change measures.
|
||||
* The energy demand for each industry sector and each location in 2015 is also calculated, so that it can be later incorporated in the pathway optimization.
|
||||
* Ammonia production data is taken from the USGS and deducted from JRC-IDEES's "basic chemicals" so that it ammonia can be handled separately from the others (olefins, aromatics and chlorine).
|
||||
* Solid biomass is no longer allowed to be used for process heat in cement and basic chemicals, since the wastes and residues cannot be guaranteed to reach the high temperatures required. Instead, solid biomass is used in the paper and pulp as well as food, beverages and tobacco industries, where required temperatures are lower (see `DOI:10.1002/er.3436 <https://doi.org/10.1002/er.3436>`_ and `DOI:10.1007/s12053-017-9571-y <https://doi.org/10.1007/s12053-017-9571-y>`_).
|
||||
* National installable potentials for salt caverns are now applied.
|
||||
* When electricity distribution grids are activated, new industry electricity demand, resistive heaters and micro-CHPs are now connected to the lower voltage levels.
|
||||
* Gas distribution grid costs are included for gas boilers and micro-CHPs.
|
||||
* Installable potentials for rooftop PV are included with an assumption of 1 kWp per person.
|
||||
* Some intermediate files produced by scripts have been moved from the folder ``data`` to the folder ``resources``. Now ``data`` only includes input data, while ``resources`` only includes intermediate files necessary for building the network models. Please note that the data bundle has also been updated.
|
||||
* Biomass potentials for different years and scenarios from the JRC are generated in an intermediate file, so that a selection can be made more explicitly by specifying the biomass types from the ``config.yaml``.
|
||||
|
||||
|
||||
PyPSA-Eur-Sec 0.2.0 (21st August 2020)
|
||||
--------------------------------------
|
||||
|
||||
This release introduces pathway optimization over many years (e.g. 2020, 2030, 2040, 2050) with myopic foresight, as well as outsourcing the technology assumptions to the `technology-data <https://github.com/PyPSA/technology-data>`_ repository.
|
||||
|
||||
It is known to work with PyPSA-Eur v0.1.0 (commit bb3477cd69), PyPSA v0.17.1 and technology-data v0.1.0.
|
||||
|
||||
New features:
|
||||
|
||||
* Option for pathway optimization with myopic foresight, based on the paper `Early decarbonisation of the European Energy system pays off (2020) <https://arxiv.org/abs/2004.11009>`_. Investments are optimized sequentially for multiple years (e.g. 2020, 2030, 2040, 2050) taking account of existing assets built in previous years and their lifetimes. The script uses data on the existing assets for electricity and building heating technologies, but there are no assumptions yet for existing transport and industry (if you include these, the model will greenfield them). There are also some `outstanding issues <https://github.com/PyPSA/pypsa-eur-sec/issues/19#issuecomment-678194802>`_ on e.g. the distribution of existing wind, solar and heating technologies within each country. To use myopic foresight, set ``foresight : 'myopic'`` in the ``config.yaml`` instead of the default ``foresight : 'overnight'``. An example configuration can be found in ``config.myopic.yaml``. More details on the implementation can be found in :doc:`myopic`.
|
||||
|
||||
* Technology assumptions (costs, efficiencies, etc.) are no longer stored in the repository. Instead, you have to install the `technology-data <https://github.com/PyPSA/technology-data>`_ database in a parallel directory. These assumptions are largely based on the `Danish Energy Agency Technology Data <https://ens.dk/en/our-services/projections-and-models/technology-data>`_. More details on the installation can be found in :doc:`installation`.
|
||||
|
||||
* Logs and benchmarks are now stored with the other model outputs in ``results/run-name/``.
|
||||
|
||||
* All buses now have a ``location`` attribute, e.g. bus ``DE0 3 urban central heat`` has a ``location`` of ``DE0 3``.
|
||||
|
||||
* All assets have a ``lifetime`` attribute (integer in years). For the myopic foresight, a ``build_year`` attribute is also stored.
|
||||
|
||||
* Costs for solar and onshore and offshore wind are recalculated by PyPSA-Eur-Sec based on the investment year, including the AC or DC connection costs for offshore wind.
|
||||
|
||||
Many thanks to Marta Victoria for implementing the myopic foresight, and Marta Victoria, Kun Zhu and Lisa Zeyen for developing the technology assumptions database.
|
||||
|
||||
|
||||
PyPSA-Eur-Sec 0.1.0 (8th July 2020)
|
||||
-----------------------------------
|
||||
|
||||
This is the first proper release of PyPSA-Eur-Sec, a model of the European energy system at the transmission network level that covers the full ENTSO-E area.
|
||||
|
||||
It is known to work with PyPSA-Eur v0.1.0 (commit bb3477cd69) and PyPSA v0.17.0.
|
||||
|
||||
We are making this release since in version 0.2.0 we will introduce changes to allow myopic investment planning that will require minor changes for users of the overnight investment planning.
|
||||
|
||||
PyPSA-Eur-Sec builds on the electricity generation and transmission
|
||||
model `PyPSA-Eur <https://github.com/PyPSA/pypsa-eur>`_ to add demand
|
||||
and supply for the following sectors: transport, space and water
|
||||
heating, biomass, industry and industrial feedstocks. This completes
|
||||
the energy system and includes all greenhouse gas emitters except
|
||||
waste management, agriculture, forestry and land use.
|
||||
|
||||
PyPSA-Eur-Sec was initially based on the model PyPSA-Eur-Sec-30 (Version 0.0.1 below) described
|
||||
in the paper `Synergies of sector coupling and transmission
|
||||
reinforcement in a cost-optimised, highly renewable European energy
|
||||
system <https://arxiv.org/abs/1801.05290>`_ (2018) but it differs by
|
||||
being based on the higher resolution electricity transmission model
|
||||
`PyPSA-Eur <https://github.com/PyPSA/pypsa-eur>`_ rather than a
|
||||
one-node-per-country model, and by including biomass, industry,
|
||||
industrial feedstocks, aviation, shipping, better carbon management,
|
||||
carbon capture and usage/sequestration, and gas networks.
|
||||
|
||||
|
||||
PyPSA-Eur-Sec includes PyPSA-Eur as a
|
||||
`snakemake <https://snakemake.readthedocs.io/en/stable/index.html>`_
|
||||
`subworkflow <https://snakemake.readthedocs.io/en/stable/snakefiles/modularization.html#snakefiles-sub-workflows>`_. PyPSA-Eur-Sec
|
||||
uses PyPSA-Eur to build the clustered transmission model along with
|
||||
wind, solar PV and hydroelectricity potentials and time series. Then
|
||||
PyPSA-Eur-Sec adds other conventional generators, storage units and
|
||||
the additional sectors.
|
||||
|
||||
|
||||
|
||||
|
||||
PyPSA-Eur-Sec 0.0.2 (4th September 2020)
|
||||
----------------------------------------
|
||||
|
||||
This version, also called PyPSA-Eur-Sec-30-Path, built on
|
||||
PyPSA-Eur-Sec 0.0.1 (also called PyPSA-Eur-Sec-30) to include myopic
|
||||
pathway optimisation for the paper `Early decarbonisation of the
|
||||
European energy system pays off <https://arxiv.org/abs/2004.11009>`_
|
||||
(2020). The myopic pathway optimisation was then merged into the main
|
||||
PyPSA-Eur-Sec codebase in Version 0.2.0 above.
|
||||
|
||||
This model has `its own github repository
|
||||
<https://github.com/martavp/pypsa-eur-sec-30-path>`_ and is `archived
|
||||
on Zenodo <https://zenodo.org/record/4014807>`_.
|
||||
|
||||
|
||||
|
||||
PyPSA-Eur-Sec 0.0.1 (12th January 2018)
|
||||
---------------------------------------
|
||||
|
||||
This is the first published version of PyPSA-Eur-Sec, also called
|
||||
PyPSA-Eur-Sec-30. It was first used in the research paper `Synergies of
|
||||
sector coupling and transmission reinforcement in a cost-optimised,
|
||||
highly renewable European energy system
|
||||
<https://arxiv.org/abs/1801.05290>`_ (2018). The model covers 30
|
||||
European countries with one node per country. It includes demand and
|
||||
supply for electricity, space and water heating in buildings, and land
|
||||
transport.
|
||||
|
||||
It is `archived on Zenodo <https://zenodo.org/record/1146666>`_.
|
||||
|
||||
|
||||
Release Process
|
||||
===============
|
||||
|
||||
@ -615,15 +1265,17 @@ Release Process
|
||||
|
||||
* Update version number in ``doc/conf.py``, ``CITATION.cff`` and ``*config.*.yaml``.
|
||||
|
||||
* Make a ``git commit``.
|
||||
|
||||
* Open, review and merge pull request for branch ``release-v0.x.x``.
|
||||
Make sure to close issues and PRs or the release milestone with it (e.g. closes #X).
|
||||
|
||||
* Tag a release on Github via ``git tag v0.x.x``, ``git push``, ``git push --tags``. Include release notes in the tag message.
|
||||
|
||||
* Upload code to `zenodo code repository <https://doi.org/10.5281/zenodo.3520874>`_ with `MIT license <https://opensource.org/licenses/MIT>`_.
|
||||
* Make a `GitHub release <https://github.com/PyPSA/pypsa-eur-sec/releases>`_, which automatically triggers archiving to the `zenodo code repository <https://doi.org/10.5281/zenodo.3520874>`_ with `MIT license <https://opensource.org/licenses/MIT>`_.
|
||||
|
||||
* Create pre-built networks for ``config.default.yaml`` by running ``snakemake -call extra_components_all_networks``.
|
||||
* Create pre-built networks for ``config.default.yaml`` by running ``snakemake -call prepare_sector_networks``.
|
||||
|
||||
* Upload pre-built networks to `zenodo data repository <https://doi.org/10.5281/zenodo.3601881>`_ with `CC BY 4.0 <https://creativecommons.org/licenses/by/4.0/>`_ license.
|
||||
|
||||
* Send announcement on the `PyPSA and PyPSA-Eur mailing list <https://groups.google.com/forum/#!forum/pypsa>`_.
|
||||
* Send announcement on the `PyPSA mailing list <https://groups.google.com/forum/#!forum/pypsa>`_.
|
||||
|
||||
@ -4,12 +4,15 @@
|
||||
|
||||
sphinx
|
||||
sphinx_book_theme
|
||||
sphinxcontrib-bibtex
|
||||
|
||||
pypsa
|
||||
vresutils>=0.3.1
|
||||
powerplantmatching>=0.5.5
|
||||
atlite>=0.2.9
|
||||
dask
|
||||
dask[distributed]
|
||||
matplotlib>3.5.1,<3.6
|
||||
tabula-py
|
||||
|
||||
# cartopy
|
||||
scikit-learn
|
||||
|
||||
@ -5,8 +5,9 @@
|
||||
|
||||
.. _data:
|
||||
|
||||
Rules ``retrieve*``
|
||||
=============================
|
||||
###############
|
||||
Retrieving Data
|
||||
###############
|
||||
|
||||
Not all data dependencies are shipped with the git repository,
|
||||
since git is not suited for handling large changing files.
|
||||
@ -14,12 +15,12 @@ Instead we provide separate data bundles which can be obtained
|
||||
using the ``retrieve*`` rules.
|
||||
|
||||
Rule ``retrieve_databundle``
|
||||
----------------------------
|
||||
============================
|
||||
|
||||
.. automodule:: retrieve_databundle
|
||||
|
||||
Rule ``retrieve_cutout``
|
||||
------------------------
|
||||
============================
|
||||
|
||||
.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3517949.svg
|
||||
:target: https://doi.org/10.5281/zenodo.3517949
|
||||
@ -53,7 +54,7 @@ The :ref:`tutorial` uses a smaller cutout than required for the full model (30 M
|
||||
|
||||
|
||||
Rule ``retrieve_natura_raster``
|
||||
-------------------------------
|
||||
================================
|
||||
|
||||
.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.4706686.svg
|
||||
:target: https://doi.org/10.5281/zenodo.4706686
|
||||
@ -80,7 +81,7 @@ This rule, as a substitute for :mod:`build_natura_raster`, downloads an already
|
||||
|
||||
|
||||
Rule ``retrieve_load_data``
|
||||
---------------------------
|
||||
================================
|
||||
|
||||
This rule downloads hourly electric load data for each country from the `OPSD platform <data.open-power-system-data.org/time_series/2019-06-05/time_series_60min_singleindex.csv>`_.
|
||||
|
||||
@ -94,7 +95,7 @@ None.
|
||||
|
||||
|
||||
Rule ``retrieve_cost_data``
|
||||
---------------------------
|
||||
================================
|
||||
|
||||
This rule downloads techno-economic assumptions from the `technology-data repository <https://github.com/pypsa/technology-data>`_.
|
||||
|
||||
@ -118,7 +119,7 @@ This rule downloads techno-economic assumptions from the `technology-data reposi
|
||||
- ``resources/costs.csv``
|
||||
|
||||
Rule ``retrieve_ship_raster``
|
||||
-----------------------------
|
||||
================================
|
||||
|
||||
This rule downloads data on global shipping traffic density from the `World Bank Data Catalogue <https://datacatalog.worldbank.org/search/dataset/0037580/Global-Shipping-Traffic-Density>`_.
|
||||
|
||||
@ -129,3 +130,14 @@ None.
|
||||
**Outputs**
|
||||
|
||||
- ``data/shipdensity_global.zip``
|
||||
|
||||
|
||||
Rule ``retrieve_sector_databundle``
|
||||
====================================
|
||||
|
||||
.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.5546516.svg
|
||||
:target: https://doi.org/10.5281/zenodo.5546516
|
||||
|
||||
In addition to the databundle required for electricity-only studies,
|
||||
another databundle is required for modelling sector-coupled systems.
|
||||
The size of this data bundle is around 640 MB.
|
||||
166
doc/sector.rst
Normal file
166
doc/sector.rst
Normal file
@ -0,0 +1,166 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
##########################################
|
||||
Building Sector-Coupled Networks
|
||||
##########################################
|
||||
|
||||
.. warning::
|
||||
This part of the documentation is under development.
|
||||
|
||||
Rule ``add_brownfield``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: add_brownfield
|
||||
|
||||
Rule ``add_existing_baseyear``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: add_existing_baseyear
|
||||
|
||||
Rule ``build_ammonia_production``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_ammonia_production
|
||||
|
||||
Rule ``build_biomass_potentials``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_biomass_potentials
|
||||
|
||||
Rule ``build_biomass_transport_costs``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_biomass_transport_costs
|
||||
|
||||
Rule ``build_clustered_population_layouts``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_clustered_population_layouts
|
||||
|
||||
Rule ``build_cop_profiles``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_cop_profiles
|
||||
|
||||
Rule ``build_energy_totals``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_energy_totals
|
||||
|
||||
Rule ``build_gas_input_locations``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_gas_input_locations
|
||||
|
||||
Rule ``build_gas_network``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_gas_network
|
||||
|
||||
Rule ``build_heat_demand``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_heat_demand
|
||||
|
||||
Rule ``build_industrial_distribution_key``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_industrial_distribution_key
|
||||
|
||||
Rule ``build_industrial_energy_demand_per_country_today``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_industrial_energy_demand_per_country_today
|
||||
|
||||
Rule ``build_industrial_energy_demand_per_node_today``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_industrial_energy_demand_per_node_today
|
||||
|
||||
Rule ``build_industrial_energy_demand_per_node``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_industrial_energy_demand_per_node
|
||||
|
||||
Rule ``build_industrial_production_per_country_tomorrow``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_industrial_production_per_country_tomorrow
|
||||
|
||||
Rule ``build_industrial_production_per_country``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_industrial_production_per_country
|
||||
|
||||
Rule ``build_industrial_production_per_node``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_industrial_production_per_node
|
||||
|
||||
Rule ``build_industry_sector_ratios``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_industry_sector_ratios
|
||||
|
||||
Rule ``build_population_layouts``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_population_layouts
|
||||
|
||||
Rule ``build_population_weighted_energy_totals``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_population_weighted_energy_totals
|
||||
|
||||
Rule ``build_retro_cost``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_retro_cost
|
||||
|
||||
Rule ``build_salt_cavern_potentials``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_salt_cavern_potentials
|
||||
|
||||
Rule ``build_sequestration_potentials``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_sequestration_potentials
|
||||
|
||||
Rule ``build_shipping_demand``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_shipping_demand
|
||||
|
||||
Rule ``build_solar_thermal_profiles``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_solar_thermal_profiles
|
||||
|
||||
Rule ``build_temperature_profiles``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_temperature_profiles
|
||||
|
||||
Rule ``build_transport_demand``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_transport_demand
|
||||
|
||||
Rule ``cluster_gas_network``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: cluster_gas_network
|
||||
|
||||
Rule ``copy_config``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: copy_config
|
||||
|
||||
Rule ``prepare_sector_network``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: prepare_sector_network
|
||||
@ -6,7 +6,7 @@
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
##########################################
|
||||
Simplifying Networks
|
||||
Simplifying Electricity Networks
|
||||
##########################################
|
||||
|
||||
The simplification ``snakemake`` rules prepare **approximations** of the full model, for which it is computationally viable to co-optimize generation, storage and transmission capacities.
|
||||
@ -20,10 +20,31 @@ The simplification and clustering steps are described in detail in the paper
|
||||
|
||||
After simplification and clustering of the network, additional components may be appended in the rule :mod:`add_extra_components` and the network is prepared for solving in :mod:`prepare_network`.
|
||||
|
||||
.. toctree::
|
||||
:caption: Overview
|
||||
.. _simplify:
|
||||
|
||||
simplification/simplify_network
|
||||
simplification/cluster_network
|
||||
simplification/add_extra_components
|
||||
simplification/prepare_network
|
||||
Rule ``simplify_network``
|
||||
============================
|
||||
|
||||
.. automodule:: simplify_network
|
||||
|
||||
.. _cluster:
|
||||
|
||||
Rule ``cluster_network``
|
||||
===========================
|
||||
|
||||
.. automodule:: cluster_network
|
||||
|
||||
.. _extra_components:
|
||||
|
||||
Rule ``add_extra_components``
|
||||
=============================
|
||||
|
||||
.. automodule:: add_extra_components
|
||||
|
||||
|
||||
.. _prepare:
|
||||
|
||||
Rule ``prepare_network``
|
||||
===========================
|
||||
|
||||
.. automodule:: prepare_network
|
||||
|
||||
@ -1,42 +0,0 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _extra_components:
|
||||
|
||||
Rule ``add_extra_components``
|
||||
=============================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="8,5"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
1 [color="0.56 0.6 0.85",
|
||||
label=prepare_network];
|
||||
2 [color="0.47 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=add_extra_components,
|
||||
style=filled];
|
||||
2 -> 1;
|
||||
3 [color="0.03 0.6 0.85",
|
||||
label=cluster_network];
|
||||
3 -> 2;
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: add_extra_components
|
||||
@ -1,43 +0,0 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _cluster:
|
||||
|
||||
Rule ``cluster_network``
|
||||
===========================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="8,5"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
1 [color="0.50 0.6 0.85",
|
||||
label=prepare_network];
|
||||
2 [color="0.36 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=cluster_network,
|
||||
style=filled];
|
||||
2 -> 1;
|
||||
3 [color="0.14 0.6 0.85",
|
||||
label=simplify_network];
|
||||
3 -> 2;
|
||||
}
|
||||
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: cluster_network
|
||||
@ -1,42 +0,0 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _prepare:
|
||||
|
||||
Rule ``prepare_network``
|
||||
===========================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="8,5"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
0 [color="0.53 0.6 0.85",
|
||||
label=solve_network];
|
||||
1 [color="0.50 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=prepare_network,
|
||||
style=filled];
|
||||
1 -> 0;
|
||||
2 [color="0.36 0.6 0.85",
|
||||
label=cluster_network];
|
||||
2 -> 1;
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: prepare_network
|
||||
@ -1,45 +0,0 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _simplify:
|
||||
|
||||
Rule ``simplify_network``
|
||||
============================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="8,5"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
2 [color="0.36 0.6 0.85",
|
||||
label=cluster_network];
|
||||
3 [color="0.14 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=simplify_network,
|
||||
style=filled];
|
||||
3 -> 2;
|
||||
4 [color="0.61 0.6 0.85",
|
||||
label=add_electricity];
|
||||
4 -> 3;
|
||||
5 [color="0.19 0.6 0.85",
|
||||
label=build_bus_regions];
|
||||
5 -> 3;
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: simplify_network
|
||||
@ -7,10 +7,27 @@
|
||||
Solving Networks
|
||||
##########################################
|
||||
|
||||
After generating and simplifying the networks they can be solved through the rule :mod:`solve_network` by using the collection rule :mod:`solve_all_networks`. Moreover, networks can be solved for another focus with the derivative rules :mod:`solve_network` by using the collection rule :mod:`solve_operations_network` for dispatch-only analyses on an already solved network.
|
||||
After generating and simplifying the networks they can be solved through the
|
||||
rule :mod:`solve_network` by using the collection rules ``solve_elec_networks``
|
||||
or ``solve_sector_networks``. Moreover, networks can be solved for dispatch-only
|
||||
analyses on an already solved network with :mod:`solve_operations_network`.
|
||||
|
||||
.. toctree::
|
||||
:caption: Overview
|
||||
.. _solve:
|
||||
|
||||
solving/solve_network
|
||||
solving/solve_operations_network
|
||||
Rule ``solve_network``
|
||||
=========================
|
||||
|
||||
.. automodule:: solve_network
|
||||
|
||||
.. _solve_operations:
|
||||
|
||||
Rule ``solve_operations_network``
|
||||
====================================
|
||||
|
||||
.. automodule:: solve_operations_network
|
||||
|
||||
Rule ``solve_sector_network``
|
||||
=============================
|
||||
|
||||
.. warning::
|
||||
More comprehensive documentation for this rule will be released soon.
|
||||
|
||||
@ -1,39 +0,0 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _solve:
|
||||
|
||||
Rule ``solve_network``
|
||||
=========================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="3,3"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
0 [color="0.64 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=solve_network,
|
||||
style=filled];
|
||||
1 [color="0.33 0.6 0.85",
|
||||
label=prepare_network];
|
||||
1 -> 0;
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: solve_network
|
||||
@ -1,42 +0,0 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _solve_operations:
|
||||
|
||||
Rule ``solve_operations_network``
|
||||
====================================
|
||||
|
||||
.. graphviz::
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph [bgcolor=white,
|
||||
margin=0,
|
||||
size="8,5"
|
||||
];
|
||||
node [fontname=sans,
|
||||
fontsize=10,
|
||||
penwidth=2,
|
||||
shape=box,
|
||||
style=rounded
|
||||
];
|
||||
edge [color=grey,
|
||||
penwidth=2
|
||||
];
|
||||
0 [color="0.06 0.6 0.85",
|
||||
fillcolor=gray,
|
||||
label=solve_operations_network,
|
||||
style=filled];
|
||||
1 [color="0.00 0.6 0.85",
|
||||
label=cluster_network];
|
||||
1 -> 0;
|
||||
2 [color="0.19 0.6 0.85",
|
||||
label=solve_network];
|
||||
2 -> 0;
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
.. automodule:: solve_operations_network
|
||||
54
doc/spatial_resolution.rst
Normal file
54
doc/spatial_resolution.rst
Normal file
@ -0,0 +1,54 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2021-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _spatial_resolution:
|
||||
|
||||
##########################################
|
||||
Spatial resolution
|
||||
##########################################
|
||||
|
||||
The default nodal resolution of the model follows the electricity generation and transmission model `PyPSA-Eur <https://github.com/PyPSA/pypsa-eur>`_, which clusters down the electricity transmission substations in each European country based on the k-means algorithm (See `cluster_network <https://pypsa-eur.readthedocs.io/en/latest/simplification/cluster_network.html#rule-cluster-network>`_ for a complete explanation). This gives nodes which correspond to major load and generation centres (typically cities).
|
||||
|
||||
The total number of nodes for Europe is set in the ``config.yaml`` file under ``clusters``. The number of nodes can vary between 37, the number of independent countries / synchronous areas, and several hundred. With 200-300 nodes the model needs 100-150 GB RAM to solve with a commercial solver like Gurobi.
|
||||
|
||||
Exemplary unsolved network clustered to 512 nodes:
|
||||
|
||||
.. image:: ../graphics/elec_s_512.png
|
||||
|
||||
Exemplary unsolved network clustered to 37 nodes:
|
||||
|
||||
.. image:: ../graphics/elec_s_37.png
|
||||
|
||||
The total number of nodes for Europe is set in the config.yaml file under `clusters <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L20>`_. The number of nodes can vary between 37, the number of independent countries/synchronous areas, and several hundred. With 200-300 nodes, the model needs 100-150 GB RAM to solve with a commercial solver like Gurobi.
|
||||
Not all of the sectors are at the full nodal resolution, and some demand for some sectors is distributed to nodes using heuristics that need to be corrected. Some networks are copper-plated to reduce computational times.
|
||||
|
||||
Here are some examples of how spatial resolution is set for different sectors in PyPSA-Eur-Sec:
|
||||
|
||||
• Electricity network: Modeled as nodal.
|
||||
|
||||
• Electricity residential and commercial demand: Modeled as nodal, distributed in each country based on population and GDP.
|
||||
|
||||
• Electricity distribution network: Not included in the model, but a link per node can be used to represent energy transferred between distribution and transmission levels (explained more in detail below).
|
||||
|
||||
• Residential and commercial building heating demand: Modeled as nodal, distributed in each country based on population.
|
||||
|
||||
• Electricity demand in industry: Modeled as nodal, based on the location of industrial facilities from HotMaps database.
|
||||
|
||||
• Industry demand (heat, chemicals, etc.) : Modeled as nodal, distributed in each country based on locations of industry from HotMaps database.
|
||||
• Hydrogen network: Modeled as nodal (if activated in the `config <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L260>`_ file).
|
||||
|
||||
• Methane network: It can be modeled as a single node for Europe or it can be nodally resolved if activated in the `config <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L266>`_. One node can be considered reasonable since future demand is expected to be low and no bottlenecks are expected. Also, the nodally resolved methane grid is based on SciGRID_gas data.
|
||||
|
||||
• Solid biomass: It can be modeled as a single node for Europe or it can be nodally resolved if activated in the `config <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L270>`_. Nodal modeling includes modeling biomass potential per country (given per country, then distributed by population density within) and the transport of solid biomass between countries.
|
||||
|
||||
• CO2: It can be modeled as a single node for Europe or it can be nodally resolved with CO2 transport pipelines if activated in the `config <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L248>`_. It should mentioned that in single node mode a transport and storage cost is added for sequestered CO2, the cost of which can be adjusted in the `config <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L247>`_.
|
||||
|
||||
• Liquid hydrocarbons: Modeled as a single node for Europe, since transport costs for liquids are low and no bottlenecks are expected.
|
||||
|
||||
**Electricity distribution network**
|
||||
|
||||
Contrary to the transmission grid, the grid topology at the distribution level (at and below 110 kV) is not included due to the very high computational burden. However, a link per node can be used (if activated in the `Config <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L257>`_ file) to represent energy transferred between distribution and transmission levels at every node. In essence, the total energy capacity connecting the transmission grid and the low-voltage level is optimized. The cost assumptions for this link can be adjusted in Config file `options <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L258>`_ , and is currently assumed to be 500 Eur/kW.
|
||||
|
||||
Rooftop PV, heat pumps, resistive heater, home batteries chargers for passenger EVs, as well as individual heating technologies (heat pumps and resistive heaters) are connected to low-voltage level. All the remaining generation and storage technologies are connected to the transmission grid. In practice, this means that the distribution grid capacity is only extended if it is necessary to balance the mismatch between local generation and demand.
|
||||
621
doc/supply_demand.rst
Normal file
621
doc/supply_demand.rst
Normal file
@ -0,0 +1,621 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2021-2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
##########################################
|
||||
Supply and demand
|
||||
##########################################
|
||||
|
||||
An initial orientation to the supply and demand options in the model
|
||||
PyPSA-Eur-Sec can be found in the description of the model
|
||||
PyPSA-Eur-Sec-30 in the paper `Synergies of sector coupling and
|
||||
transmission reinforcement in a cost-optimised, highly renewable
|
||||
European energy system <https://arxiv.org/abs/1801.05290>`_ (2018).
|
||||
The latest version of PyPSA-Eur-Sec differs by including biomass,
|
||||
industry, industrial feedstocks, aviation, shipping, better carbon
|
||||
management, carbon capture and usage/sequestration, and gas networks.
|
||||
|
||||
The basic supply (left column) and demand (right column) options in the model are described in this figure:
|
||||
|
||||
.. image:: ../graphics/multisector_figure.png
|
||||
|
||||
.. _Electricity supply and demand:
|
||||
|
||||
Electricity supply and demand
|
||||
=============================
|
||||
|
||||
Electricity supply and demand follows the electricity generation and
|
||||
transmission model `PyPSA-Eur <https://github.com/PyPSA/pypsa-eur>`_,
|
||||
except that hydrogen storage is integrated into the hydrogen supply,
|
||||
demand and network, and PyPSA-Eur-Sec includes CHPs.
|
||||
|
||||
Unlike PyPSA-Eur, PyPSA-Eur-Sec does not distribution electricity demand for industry according to population and GDP, but uses the
|
||||
geographical data from the `Hotmaps Industrial Database
|
||||
<https://gitlab.com/hotmaps/industrial_sites/industrial_sites_Industrial_Database>`_.
|
||||
|
||||
Also unlike PyPSA-Eur, PyPSA-Eur-Sec subtracts existing electrified heating from the existing electricity demand, so that power-to-heat can be optimised separately.
|
||||
|
||||
The remaining electricity demand for households and services is distributed inside each country proportional to GDP and population.
|
||||
|
||||
.. _Heat demand:
|
||||
|
||||
Heat demand
|
||||
===========
|
||||
|
||||
Building heating in residential and services sectors is resolved regionally, both for individual buildings and district heating systems, which include different supply options (see :ref:`heat-supply`.)
|
||||
Annual heat demands per country are retrieved from `JRC-IDEES <https://op.europa.eu/en/publication-detail/-/publication/989282db-ad65-11e7-837e-01aa75ed71a1/language-en>`_ and split into space and water heating. For space heating, the annual demands are converted to daily values based on the population-weighted Heating Degree Day (HDD) using the `atlite tool <https://github.com/PyPSA/atlite>`_, where space heat demand is proportional to the difference between the daily average ambient temperature (read from `ERA5 <https://doi.org/10.1002/qj.3803>`_) and a threshold temperature above which space heat demand is zero. A threshold temperature of 15 °C is assumed by default. The daily space heat demand is distributed to the hours of the day following heat demand profiles from `BDEW <https://github.com/oemof/demandlib>`_. These differ for weekdays and weekends/holidays and between residential and services demand.
|
||||
|
||||
*Space heating*
|
||||
|
||||
The space heating demand can be exogenously reduced by retrofitting measures that improve the buildings’ thermal envelopes.
|
||||
|
||||
.. literalinclude:: ../config.default.yaml
|
||||
:language: yaml
|
||||
:lines: 205
|
||||
|
||||
Co-optimsing of building renovation is also possible, if it is activated in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L222>`_.
|
||||
Renovation of the thermal envelope reduces the space heating demand and is optimised at each node for every heat bus. Renovation measures through additional insulation material and replacement of energy inefficient windows are considered.
|
||||
In a first step, costs per energy savings are estimated in `build_retro_cost.py <https://github.com/PyPSA/pypsa-eur-sec/blob/master/scripts/build_retro_cost.py>`_. They depend on the insulation condition of the building stock and costs for renovation of the building elements. In a second step, for those cost per energy savings two possible renovation strengths are determined: a moderate renovation with lower costs, a lower maximum possible space heat savings, and an ambitious renovation with associated higher costs and higher efficiency gains. They are added by step-wise linearisation in form of two additional generations in `prepare_sector_network.py <https://github.com/PyPSA/pypsa-eur-sec/blob/master/scripts/prepare_sector_network.py>`_.
|
||||
Further information are given in the publication :
|
||||
`Mitigating heat demand peaks in buildings in a highly renewable European energy system, (2021) <https://arxiv.org/abs/2012.01831>`_.
|
||||
|
||||
*Water heating*
|
||||
|
||||
Hot water demand is assumed to be constant throughout the year.
|
||||
|
||||
*Urban and rural heating*
|
||||
|
||||
For every country, heat demand is split between low and high population density areas. These country-level totals are then distributed to each region in proportion to their rural and urban populations respectively. Urban areas with dense heat demand can be supplied with large-scale district heating systems. The percentage of urban heat demand that can be supplied by district heating networks as well as lump-sum losses in district heating systems is exogenously determined in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L153>`_.
|
||||
|
||||
*Cooling demand*
|
||||
|
||||
Cooling is electrified and is included in the electricity demand. Cooling demand is assumed to remain at current levels. An example of regional distribution of the total heat demand for network 181 regions is depicted below.
|
||||
|
||||
.. image:: ../graphics/demand-map-heat.png
|
||||
|
||||
As below figure shows, the current total heat demand in Europe is similar to the total electricity demand but features much more pronounced seasonal variations. The current total building heating demand in Europe adds up to 3084 TWh/a of which 78% occurs in urban areas.
|
||||
|
||||
.. image:: ../graphics/Heat_and_el_demand_timeseries.png
|
||||
|
||||
In practice, in PyPSA-Eur-Sec, there are heat demand buses to which the corresponding heat demands are added.
|
||||
|
||||
|
||||
1) Urban central heat: large-scale district heating networks in urban areas with dense heat population. Residential and services demand in these areas are added as demands to this bus
|
||||
2) Residential urban decentral heat: heating for residential buildings in urban areas not using district heating
|
||||
3) Services urban decentral heat: heating for services buildings in urban areas not using district heating
|
||||
4) Residential rural heat: heating for residential buildings in rural areas with low population density.
|
||||
5) Services rural heat: heating for residential services buildings in rural areas with low population density. Heat demand from agriculture sector is also included here.
|
||||
|
||||
.. _heat-supply:
|
||||
|
||||
Heat supply
|
||||
=======================
|
||||
|
||||
Different supply options are available depending on whether demand is met centrally through district heating systems, or decentrally through appliances in individual buildings.
|
||||
|
||||
**Urban central heat**
|
||||
|
||||
For large-scale district heating systems the following options are available: combined heat and power (CHP) plants consuming gas or biomass from waste and residues with and without carbon capture (CC), large-scale air-sourced heat pumps, gas and oil boilers, resistive heaters, and fuel cell CHPs. Additionally, waste heat from the `Fischer-Tropsch <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L255>`_ and `Sabatier <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L240>`_ processes for the production of synthetic hydrocarbons can supply district heating systems. For more detailed explanation of these processes, see :ref:`Oil-based products supply` and :ref:`Methane supply`.
|
||||
|
||||
**Residential and Urban decentral heat**
|
||||
|
||||
Supply options in individual buildings include gas and oil boilers, air- and ground-sourced heat pumps, resistive heaters, and solar thermal collectors.
|
||||
Ground-source heat pumps are only allowed in rural areas because of space constraints. Thus, only air- source heat pumps are allowed in urban areas. This is a conservative assumption, since there are many possible sources of low-temperature heat that could be tapped in cities (e.g. waste water, ground water, or natural bodies of water). Costs, lifetimes and efficiencies for these technologies are retrieved from the `technology-data repository <https://github.com/PyPSA/technology-data>`_.
|
||||
|
||||
Below are more detailed explanations for each heating supply component, all of which are modelled as `links <https://pypsa.readthedocs.io/en/latest/components.html?highlight=distribution#link>`_ in PyPSA-Eur-Sec.
|
||||
|
||||
.. _Large-scale CHP:
|
||||
|
||||
**Large-scale CHP**
|
||||
|
||||
Large Combined Heat and Power plants are included in the model if it is specified in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L235>`_.
|
||||
|
||||
CHPs are based on back pressure plants operating with a fixed ratio of electricity to heat output. The efficiencies of each are given on the back pressure line, where the back pressure coefficient cb is the electricity output divided by the heat output. (For a more complete explanation of the operation of CHPs refer to the study by Dahl et al. : `Cost sensitivity of optimal sector-coupled district heating production systems <https://arxiv.org/pdf/1804.07557.pdf>`_.
|
||||
|
||||
PyPSA-Eur-Sec includes CHP plants fueled by methane and solid biomass from waste and residues. Hydrogen fuel cells also produce both electricity and heat.
|
||||
|
||||
The methane CHP is modeled on the Danish Energy Agency (DEA) “Gas turbine simple cycle (large)” while the solid biomass CHP is based on the DEA’s “09b Wood Pellets Medium”. For biomass CHP, cb = `0.46 <https://ens.dk/sites/ens.dk/files/Statistik/technology_data_catalogue_for_el_and_dh_-_0009.pdf#page=156>`_ , whereas for gas CHP, cb = `1 <https://ens.dk/sites/ens.dk/files/Statistik/technology_data_catalogue_for_el_and_dh_-_0009.pdf#page=64>`_.
|
||||
|
||||
NB: The old PyPSA-Eur-Sec-30 model assumed an extraction plant (like the DEA coal CHP) for gas which has flexible production of heat and electricity within the feasibility diagram of Figure 4 in the study by `Brown et al. <https://arxiv.org/abs/1801.05290>`_ We have switched to the DEA back pressure plants since these are more common for smaller plants for biomass, and because the extraction plants were on the back pressure line for 99.5% of the time anyway. The plants were all changed to back pressure in PyPSA-Eur-Sec v0.4.0.
|
||||
|
||||
**Micro-CHP**
|
||||
|
||||
PyPSA-Eur-Sec allows individual buildings to make use of `micro gas CHPs <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L236>`_ that are assumed to be installed at the distribution grid level.
|
||||
|
||||
**Heat pumps**
|
||||
|
||||
The coefficient of performance (COP) of air- and ground-sourced heat pumps depends on the ambient or soil temperature respectively. Hence, the COP is a time-varying parameter (refer to `Config <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L206>`_ file). Generally, the COP will be lower during winter when temperatures are low. Because the ambient temperature is more volatile than the soil temperature, the COP of ground-sourced heat pumps is less variable. Moreover, the COP depends on the difference between the source and sink temperatures:
|
||||
|
||||
.. math::
|
||||
\Delta T = T_{sink} − T_{source}
|
||||
|
||||
For the sink water temperature Tsink we assume 55 °C [`Config <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L207>`_ file]. For the time- and location-dependent source temperatures Tsource, we rely on the `ERA5 <https://doi.org/10.1002/qj.3803>`_ reanalysis weather data. The temperature differences are converted into COP time series using results from a regression analysis performed in the study by `Stafell et al. <https://pubs.rsc.org/en/content/articlelanding/2012/EE/c2ee22653g>`_. For air-sourced heat pumps (ASHP), we use the function:
|
||||
|
||||
.. math::
|
||||
COP (\Delta T) = 6.81 + 0.121\Delta T + 0.000630\Delta T^2
|
||||
|
||||
for ground-sourced heat pumps (GSHP), we use the function:
|
||||
|
||||
.. math::
|
||||
COP(\Delta T) = 8.77 + 0.150\Delta T + 0.000734\Delta T^2
|
||||
|
||||
**Resistive heaters**
|
||||
|
||||
Can be activated in Config from the `boilers <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L232>`_ option.
|
||||
Resistive heaters produce heat with a fixed conversion efficiency (refer to `Technology-data repository <https://github.com/PyPSA/technology-data>`_ ).
|
||||
|
||||
**Gas, oil, and biomass boilers**
|
||||
|
||||
Can be activated in Config from the `boilers <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L232>`_ , `oil boilers <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L233>`_ , and `biomass boiler <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L234>`_ option.
|
||||
Similar to resistive heaters, boilers have a fixed efficiency and produce heat using gas, oil or biomass.
|
||||
|
||||
**Solar thermal collectors**
|
||||
|
||||
Can be activated in the config file from the `solar_thermal <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L237>`_ option.
|
||||
Solar thermal profiles are built based on weather data and also have the `options <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L134>`_ for setting the sky model and the orientation of the panel in the config file, which are then used by the atlite tool to calculate the solar resource time series.
|
||||
|
||||
**Waste heat from Fuel Cells, Methanation and Fischer-Tropsch plants**
|
||||
|
||||
Waste heat from `fuel cells <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L256>`_ in addition to processes like `Fischer-Tropsch <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L255>`_, methanation, and Direct Air Capture (DAC) is dumped into district heating networks.
|
||||
|
||||
**Existing heating capacities and decommissioning**
|
||||
|
||||
For the myopic transition paths, capacities already existing for technologies supplying heat are retrieved from `“Mapping and analyses of the current and future (2020 - 2030)” <https://ec.europa.eu/energy/en/studies/mapping-and-analyses-current-and-future-2020-2030-heatingcooling-fuel-deployment>`_ . For the sake of simplicity, coal, oil and gas boiler capacities are assimilated to gas boilers. Besides that, existing capacities for heat resistors, air-sourced and ground-sourced heat pumps are included in the model. For heating capacities, 25% of existing capacities in 2015 are assumed to be decommissioned in every 5-year time step after 2020.
|
||||
|
||||
**Thermal Energy Storage**
|
||||
|
||||
Activated in Config from the `tes <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L228>`_ option.
|
||||
|
||||
Thermal energy can be stored in large water pits associated with district heating systems and individual thermal energy storage (TES), i.e., small water tanks. Water tanks are modelled as `stores <https://pypsa.readthedocs.io/en/latest/components.html?highlight=distribution#store, which are connected to heat demand buses through water charger/discharger links>`_.
|
||||
A thermal energy density of 46.8 kWh :math:`_{th}`/m3 is assumed, corresponding to a temperature difference of 40 K. The decay of thermal energy in the stores: 1- :math:`e^{-1/24τ}` is assumed to have a time constant of τ=180 days for central TES and τ=3 days for individual TES, both modifiable through `tes_tau <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L229>`_ in config file. Charging and discharging efficiencies are 90% due to pipe losses.
|
||||
|
||||
**Retrofitting of the thermal envelope of buildings**
|
||||
|
||||
Co-optimising building renovation is only enabled if in the `config <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L222>`_ file. To reduce the computational burden,
|
||||
default setting is set as false.
|
||||
|
||||
Renovation of the thermal envelope reduces the space heating demand and is
|
||||
optimised at each node for every heat bus. Renovation measures through additional
|
||||
insulation material and replacement of energy inefficient windows are considered.
|
||||
|
||||
In a first step, costs per energy savings are estimated in the `build_retro_cost.py <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/scripts/build_retro_cost.py>`_ script.
|
||||
They depend on the insulation condition of the building stock and costs for
|
||||
renovation of the building elements.
|
||||
In a second step, for those cost per energy savings two possible renovation
|
||||
strengths are determined: a moderate renovation with lower costs and lower
|
||||
maximum possible space heat savings, and an ambitious renovation with associated
|
||||
higher costs and higher efficiency gains. They are added by step-wise
|
||||
linearisation in form of two additional generations in
|
||||
the `prepare_sector_network.py <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/scripts/prepare_sector_network.py#L1600>`_ script.
|
||||
|
||||
Settings in the config.yaml concerning the endogenously optimisation of building
|
||||
renovation include `cost factor <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L223>`_, `interest rate <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L224>`_, `annualised cost <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L225>`_, `tax weighting <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L226>`_, and `construction index <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L227>`_.
|
||||
|
||||
Further information are given in the study by Zeyen et al. : `Mitigating heat demand peaks in buildings in a highly renewable European energy system, (2021) <https://arxiv.org/abs/2012.01831>`_.
|
||||
|
||||
.. _Hydrogen demand:
|
||||
|
||||
Hydrogen demand
|
||||
=============================
|
||||
|
||||
Hydrogen is consumed in the industry sector (see :ref:`Industry demand`) to produce ammonia (see :ref:`Chemicals Industry`) and direct reduced iron (DRI) (see :ref:`Iron and Steel`). Hydrogen is also consumed to produce synthetic methane (see :ref:`Methane supply`) and liquid hydrocarbons (see :ref:`Oil-based products supply`) which have multiple uses in industry and other sectors.
|
||||
Hydrogen is also used for transport applications (see :ref:`Transportation`), where it is exogenously fixed. It is used in `heavy-duty land transport <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L181>`_ and as liquified hydrogen in the shipping sector (see :ref:`Shipping`). Furthermore, stationary fuel cells may re-electrify hydrogen (with waste heat as a byproduct) to balance renewable fluctuations (see :ref:`Electricity supply and demand`). The waste heat from the stationary fuel cells can be used in `district-heating systems <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L256>`_.
|
||||
|
||||
.. _Hydrogen supply:
|
||||
|
||||
Hydrogen supply
|
||||
=============================
|
||||
|
||||
Today, most of the :math:`H_2` consumed globally is produced from natural gas by steam methane reforming (SMR)
|
||||
|
||||
.. math::
|
||||
|
||||
CH_4 + H_2O \xrightarrow{} CO + 3H_2
|
||||
|
||||
combined with a water-gas shift reaction
|
||||
|
||||
.. math::
|
||||
|
||||
CO + H_2O \xrightarrow{} CO_2 + H_2
|
||||
|
||||
|
||||
SMR is included `here <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L245>`_.
|
||||
PyPSA-Eur-Sec allows this route of :math:`H_2` production with and without [carbon capture (CC)] (see :ref:`Carbon dioxide capture, usage and sequestration (CCU/S)`). These routes are often referred to as blue and grey hydrogen. Here, methane input can be both of fossil or synthetic origin.
|
||||
|
||||
Green hydrogen can be produced by electrolysis to split water into hydrogen and oxygen
|
||||
|
||||
.. math::
|
||||
|
||||
2H_2O \xrightarrow{} 2H_2 + O_2
|
||||
|
||||
|
||||
For the electrolysis, alkaline electrolysers are chosen since they have lower cost and higher cumulative installed capacity than polymer electrolyte membrane (PEM) electrolysers. The techno-economic assumptions are taken from the technology-data repository. Waste heat from electrolysis is not leveraged in the model.
|
||||
|
||||
**Transport**
|
||||
|
||||
Hydrogen is transported by pipelines. :math:`H_2` pipelines are endogenously generated, either via a greenfield :math:`H_2` network, or by `retrofitting natural gas pipelines <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L262>`_). Retrofitting is implemented in such a way that for every unit of decommissioned gas pipeline, a share (60% is used in the study by `Neumann et al. <https://arxiv.org/abs/2207.05816>`_) of its nominal capacity (exogenously determined in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L266>`_.) is available for hydrogen transport. When the gas network is not resolved, this input denotes the potential for gas pipelines repurposed into hydrogen pipelines.
|
||||
New pipelines can be built additionally on all routes where there currently is a gas or electricity network connection. These new pipelines will be built where no sufficient retrofitting options are available. The capacities of new and repurposed pipelines are a result of the optimisation.
|
||||
|
||||
**Storage**
|
||||
|
||||
Hydrogen can be stored in overground steel tanks or `underground salt caverns <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L250>`_. For the latter, energy storage capacities in every country are limited to the potential estimation for onshore salt caverns within `50 km <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L251>`_ of shore to avoid environmental issues associated with brine solution disposal. Underground storage potentials for hydrogen in European salt caverns is acquired from `Caglayan et al. <https://doi.org/10.1016/j.ijhydene.2019.12.161>`_
|
||||
|
||||
.. _Methane demand:
|
||||
|
||||
Methane demand
|
||||
====================================
|
||||
|
||||
Methane is used in individual and large-scale gas boilers, in CHP plants with and without carbon capture, in OCGT and CCGT power plants, and in some industry subsectors for the provision of high temperature heat (see :ref:`Industry demand`). Methane is not used in the transport sector because of engine slippage.
|
||||
|
||||
.. _Methane supply:
|
||||
|
||||
Methane supply
|
||||
===================================
|
||||
|
||||
In addition to methane from fossil origins, the model also considers biogenic and synthetic sources. `The gas network can either be modelled, or it can be assumed that gas transport is not limited <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L261>`_. If gas infrastructure is regionally resolved, fossil gas can enter the system only at existing and planned LNG terminals, pipeline entry-points, and intra- European gas extraction sites, which are retrieved from the SciGRID Gas IGGIELGN dataset and the GEM Wiki.
|
||||
Biogas can be upgraded to methane.
|
||||
Synthetic methane can be produced by processing hydrogen and captures :math:`CO_2` in the Sabatier reaction
|
||||
|
||||
.. math::
|
||||
CO_2 + 4H_2 \xrightarrow{} CH_4 + 2H_2O
|
||||
|
||||
|
||||
Direct power-to-methane conversion with efficient heat integration developed in the HELMETH project is also an option. The share of synthetic, biogenic and fossil methane is an optimisation result depending on the techno-economic assumptions.
|
||||
|
||||
*Methane transport*
|
||||
|
||||
The existing European gas transmission network is represented based on the SciGRID Gas IGGIELGN dataset. This dataset is based on compiled and merged data from the ENTSOG maps and other publicly available data sources. It includes data on the capacity, diameter, pressure, length, and directionality of pipelines. Missing capacity data is conservatively inferred from the pipe diameter following conversion factors derived from an EHB report. The gas network is clustered to the selected number of model regions. Gas pipelines can be endogenously expanded or repurposed for hydrogen transport. Gas flows are represented by a lossless transport model. Methane is assumed to be transmitted without cost or capacity constraints because future demand is predicted to be low compared to available transport capacities.
|
||||
|
||||
The following figure shows the unclustered European gas transmission network based on the SciGRID Gas IGGIELGN dataset. Pipelines are color-coded by estimated capacities. Markers indicate entry-points, sites of fossil resource extraction, and LNG terminals.
|
||||
|
||||
.. image:: ../graphics/gas_pipeline_figure.png
|
||||
|
||||
.. _Biomass supply:
|
||||
|
||||
Biomass Supply
|
||||
=====================
|
||||
Biomass supply potentials for each European country are taken from the `JRC ENSPRESO database <http://data.europa.eu/89h/74ed5a04-7d74-4807-9eab-b94774309d9f>`_ where data is available for various years (2010, 2020, 2030, 2040 and 2050) and scenarios (low, medium, high). No biomass import from outside Europe is assumed. More information on the data set can be found `here <https://publications.jrc.ec.europa.eu/repository/handle/JRC98626>`_.
|
||||
|
||||
.. _Biomass demand:
|
||||
|
||||
Biomass demand
|
||||
=====================
|
||||
|
||||
|
||||
Biomass supply potentials for every NUTS2 region are taken from the `JRC ENSPRESO database <http://data.europa.eu/89h/74ed5a04-7d74-4807-9eab-b94774309d9f>`_ where data is available for various years (2010, 2020, 2030, 2040 and 2050) and different availability scenarios (low, medium, high). No biomass import from outside Europe is assumed. More information on the data set can be found `here <https://publications.jrc.ec.europa.eu/repository/handle/JRC98626>`_. The data for NUTS2 regions is mapped to PyPSA-Eur-Sec model regions in proportion to the area overlap.
|
||||
|
||||
|
||||
The desired scenario can be selected in the PyPSA-Eur-Sec `configuration <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L108>`_. The script for building the biomass potentials from the JRC ENSPRESO data base is located `here <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/scripts/build_biomass_potentials.py#L43>`_. Consult the script to see the keywords that specify the scenario options.
|
||||
|
||||
|
||||
The `configuration <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L108>`_ also allows the user to define how the various types of biomass are used in the model by using the following categories: biogas, solid biomass, and not included. Feedstocks categorized as biogas, typically manure and sludge waste, are available to the model as biogas, which can be upgraded to biomethane. Feedstocks categorized as solid biomass, e.g. secondary forest residues or municipal waste, are available for combustion in combined-heat-and power (CHP) plants and for medium temperature heat (below 500 °C) applications in industry. It can also converted to gas or liquid fuels.
|
||||
|
||||
|
||||
Feedstocks labeled as not included are ignored by the model.
|
||||
|
||||
|
||||
A `typical use case for biomass <https://arxiv.org/abs/2109.09563>`_ would be the medium availability scenario for 2030 where only residues from agriculture and forestry as well as biodegradable municipal waste are considered as energy feedstocks. Fuel crops are avoided because they compete with scarce land for food production, while primary wood, as well as wood chips and pellets, are avoided because of concerns about sustainability. See the supporting materials of the `paper <https://www.sciencedirect.com/science/article/pii/S1364032117302034>`_ for more details.
|
||||
|
||||
|
||||
*Solid biomass conversion and use*
|
||||
|
||||
Solid biomass can be used directly to provide process heat up to 500˚C in the industry. It can also be burned in CHP plants and boilers associated with heating systems. These technologies are described elsewhere (see :ref:`Large-scale CHP` and :ref:`Industry demand`).
|
||||
|
||||
|
||||
Solid biomass can be converted to syngas if the option is enabled in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L274>`_. In this case the model will enable the technology BioSNG both with and without the option for carbon capture (see `Technology-data repository <https://github.com/PyPSA/technology-data>`_).
|
||||
|
||||
|
||||
Liquefaction of solid biomass `can be enabled <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L273>`_ allowing the model to convert it into liquid hydrocarbons that can replace conventional oil products. This technology also comes with and without carbon capture (see `Technology-data repository <https://github.com/PyPSA/technology-data>`_).
|
||||
|
||||
|
||||
*Transport of solid biomass*
|
||||
|
||||
The transport of solid biomass can either be assumed unlimited between countries or it can be associated with a country specific cost per MWh/km. In the config file these options are toggled `here <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L270>`_. If the option is off, use of solid biomass is transport. If it is turned on, a biomass transport network will be `created <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/scripts/prepare_sector_network.py#L1803>`_ between all nodes. This network resembles road transport of biomass and the cost of transportation is a variable cost which is proportional to distance and a country specific cost per MWh/km. The latter is `estimated <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/scripts/build_biomass_transport_costs.py>`_ from the country specific costs per ton/km used in the publication `“The JRC-EU-TIMES model. Bioenergy potentials for EU and neighbouring countries” <https://publications.jrc.ec.europa.eu/repository/handle/JRC98626>`_.
|
||||
|
||||
*Biogas transport and use*
|
||||
|
||||
Biogas will be aggregated into a common European resources if a gas network is not modelled explicitly, i.e., the `gas_network <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L261>`_ option is set to false. If, on the other hand, a gas network is included, the biogas potential will be associated with each node of origin.
|
||||
The model can only use biogas by first upgrading it to natural gas quality [see :ref:`Methane supply`] (bio methane) which is fed into the general gas network.
|
||||
|
||||
.. _Oil-based products demand:
|
||||
|
||||
|
||||
Oil-based products demand
|
||||
=========================
|
||||
|
||||
Naphtha is used as a feedstock in the chemicals industry (see :ref:`Chemicals Industry`). Furthermore, kerosene is used as transport fuel in the aviation sector (see :ref:`Aviation`). Non-electrified agriculture machinery also consumes gasoline.
|
||||
Land transport [(see :ref:`Land transport`) that is not electrified or converted into using :math:`H_2`-fuel cells also consumes oil-based products. While there is regional distribution of demand, the carrier is copperplated in the model, which means that transport costs and constraints are neglected.
|
||||
|
||||
.. _Oil-based products supply:
|
||||
|
||||
Oil-based products supply
|
||||
=========================
|
||||
|
||||
Oil-based products can be either of fossil origin or synthetically produced by combining :math:`H_2` (see :ref:`Hydrogen supply`) and captured :math:`CO_2` (see :ref:`Carbon dioxide capture, usage and sequestration (CCU/S)`) in Fischer-Tropsch plants
|
||||
|
||||
.. math::
|
||||
𝑛CO+(2𝑛+1)H_2 → C_{n}H_{2n + 2} +𝑛H_2O
|
||||
|
||||
|
||||
with costs as included from the `technology-data repository <https://github.com/PyPSA/technology-data/blob/master/latex_tables/tables_in_latex.pdf>`_. The waste heat from the Fischer-Tropsch process is supplied to `district heating networks <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L255>`_. The share of fossil and synthetic oil is an optimisation result depending on the techno-economic assumptions.
|
||||
|
||||
|
||||
*Oil-based transport*
|
||||
|
||||
Liquid hydrocarbons are assumed to be transported freely among the model region since future demand is predicted to be low, transport costs for liquids are low and no bottlenecks are expected.
|
||||
|
||||
.. _Industry demand:
|
||||
|
||||
Industry demand
|
||||
================
|
||||
|
||||
Industry demand is split into a dozen different sectors with specific energy demands, process
|
||||
emissions of carbon dioxide, as well as existing and prospective mitigation strategies.
|
||||
|
||||
The Subsection overview below provides a general description of the modelling approach for the industry sector. The following subsections describe the current energy demands, available mitigation strategies, and whether mitigation is exogenously fixed or co-optimised with the other components of the model for each industry subsector in more detail. See details for Iron and Steel (see :ref:`Iron and Steel`), Chemicals Industry and Ammonia (see :ref:`Chemicals Industry`), Non-metallic Mineral products , Non-ferrous Metals , and other Industry Subsectors.
|
||||
|
||||
.. _Overview:
|
||||
|
||||
**Overview**
|
||||
|
||||
Greenhouse gas emissions associated with industry can be classified into energy-related and process-related emissions. Today, fossil fuels are used for process heat energy in the chemicals industry, but also as a non-energy feedstock for chemicals like ammonia ( :math:`NH_3`), ethylene ( :math:`C_2H_4`) and methanol ( :math:`CH_3OH`). Energy-related emissions can be curbed by using low-emission energy sources. The only option to reduce process-related emissions is by using an alternative manufacturing process or by assuming a certain rate of recycling so that a lower amount of virgin material is needed.
|
||||
|
||||
The overarching modelling procedure can be described as follows. First, the energy demands and process emissions for every unit of material output are estimated based on data from the `JRC-IDEES database <https://data.europa.eu/doi/10.2760/182725>`_ and the fuel and process switching described in the subsequent sections. Second, the 2050 energy demands and process emissions are calculated using the per-unit-of-material ratios based on the industry transformations and the `country-level material production in 2015 <https://data.europa.eu/doi/10.2760/182725>`_, assuming constant material demand.
|
||||
|
||||
Missing or too coarsely aggregated data in the JRC-IDEES database is supplemented with additional datasets: `Eurostat energy balances <https://ec.europa.eu/eurostat/web/energy/data/energy-balances>`_, `United States <https://www.usgs.gov/media/files/%20nitrogen-2017-xlsx>`_, `Geological Survey <https://www.usgs.gov/media/files/%20nitrogen-2017-xlsx>`_ for ammonia production, `DECHEMA <https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry.pdf>`_ for methanol and chlorine, and `national statistics from Switzerland <https://www.bfe.admin.ch/bfe/de/home/versorgung/statistik-und-geodaten/energiestatistiken.html>`_.
|
||||
|
||||
|
||||
Where there are fossil and electrified alternatives for the same process (e.g. in glass manufacture or drying), we assume that the process is completely electrified. Current electricity demands (lighting, air compressors, motor drives, fans, pumps) will remain electric. Processes that require temperatures below 500 °C are supplied with solid biomass, since we assume that residues and wastes are not suitable for high-temperature applications. We see solid biomass use primarily in the pulp and paper industry, where it is already widespread, and in food, beverages and tobacco, where it replaces natural gas. Industries which require high temperatures (above 500 °C), such as metals, chemicals and non-metallic minerals are either electrified where suitable processes already exist, or the heat is provided with synthetic methane.
|
||||
|
||||
Hydrogen for high-temperature process heat is not part of the model currently.
|
||||
|
||||
Where process heat is required, our approach depends on the necessary temperature. For example, due to the high share of high-temperature process heat demand (see `Naegler et al. <https://doi.org/10.1002/er.3436>`_ and `Rehfeldt el al. <https://link.springer.com/article/10.1007/s12053-017-9571-y>`_), we disregard geothermal and solar thermal energy as sources for process heat since they cannot attain high-temperature heat.
|
||||
|
||||
The following figure shows the final consumption of energy and non-energy feedstocks in industry today in comparison to the scenario in 2050 assumed in `Neumann et al <https://arxiv.org/abs/2207.05816>`_.
|
||||
|
||||
.. image:: ../graphics/fec_industry_today_tomorrow.png
|
||||
|
||||
|
||||
The following figure shows the process emissions in industry today (top bar) and in 2050 without
|
||||
carbon capture (bottom bar) assumed in `Neumann et al <https://arxiv.org/abs/2207.05816>`_.
|
||||
|
||||
|
||||
|
||||
|
||||
.. image:: ../graphics/process-emissions.png
|
||||
|
||||
|
||||
Inside each country the industrial demand is then distributed using the `Hotmaps Industrial Database <https://zenodo.org/record/4687147#.YvOaxhxBy5c>`_, which is illustrated in the figure below. This open database includes georeferenced industrial sites of energy-intensive industry sectors in EU28, including cement, basic chemicals, glass, iron and steel, non-ferrous metals, non-metallic minerals, paper, and refineries subsectors. The use of this spatial dataset enables the calculation of regional and process-specific energy demands. This approach assumes that there will be no significant migration of energy-intensive industries.
|
||||
|
||||
.. image:: ../graphics/hotmaps.png
|
||||
|
||||
|
||||
.. _Iron and Steel:
|
||||
|
||||
**Iron and Steel**
|
||||
|
||||
Two alternative routes are used today to manufacture steel in Europe. The primary route (integrated steelworks) represents 60% of steel production, while the secondary route (electric arc furnaces, EAF), represents the other 40% `(Lechtenböhmer et. al) <https://doi.org/10.1016/j.energy.2016.07.110>`_.
|
||||
|
||||
The primary route uses blast furnaces in which coke is used to reduce iron ore into molten iron, which is then converted into steel:
|
||||
|
||||
.. math::
|
||||
CO_2 + C \xrightarrow{} 2 CO
|
||||
|
||||
|
||||
.. math::
|
||||
3 Fe_2O_3 + CO \xrightarrow{} 2 Fe_3O_4 + CO
|
||||
|
||||
|
||||
.. math::
|
||||
Fe_3O_4 + CO \xrightarrow{} 3 FeO + CO_2
|
||||
|
||||
|
||||
.. math::
|
||||
FeO + CO \xrightarrow{} Fe + CO_2
|
||||
|
||||
|
||||
The primary route of steelmaking implies large process emissions of 0.22 t :math:`_{CO_2}` /t of steel, amounting to 7% of global greenhouse gas emissions `(Vogl et. al) <https://doi.org/10.1016/j.joule.2021.09.007>`_.
|
||||
|
||||
In the secondary route, electric arc furnaces are used to melt scrap metal. This limits the :math:`CO_2` emissions to the burning of graphite electrodes `(Friedrichsen et. al) <https://www.umweltbundesamt.de/en/publikationen/comparative-analysis-of-options-potential-for>`_, and reduces process emissions to 0.03 t :math:`_{CO_2}` /t of steel.
|
||||
|
||||
We assume that the primary route can be replaced by a third route in 2050, using direct reduced iron (DRI) and subsequent processing in an EAF.
|
||||
|
||||
.. math::
|
||||
3 Fe_2O_3 + H_2 \xrightarrow{} 2 Fe_3O_4 + H_2O
|
||||
|
||||
|
||||
.. math::
|
||||
Fe_3O_4 +H_2 \xrightarrow{} 3FeO+H_2O
|
||||
|
||||
|
||||
.. math::
|
||||
FeO + H_2 \xrightarrow{} Fe + H_2O
|
||||
|
||||
|
||||
This circumvents the process emissions associated with the use of coke. For hydrogen- based DRI, we assume energy requirements of 1.7 MWh :math:`_{H_2}` /t steel `(Vogl et. al) <https://doi.org/10.1016/j.jclepro.2018.08.279>`_ and 0.322 MWh :math:`_{el}`/t steel `(HYBRIT 2016) <https://dh5k8ug1gwbyz.cloudfront.net/uploads/2021/02/Hybrit-broschure-engelska.pdf>`_.
|
||||
|
||||
|
||||
The share of steel produced via the primary route is exogenously set in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L279>`_. The share of steel obtained via hydrogen-based DRI plus EAF is also set exogenously in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L287>`_. The remaining share is manufactured through the secondary route using scrap metal in EAF. Bioenergy as alternative to coke in blast furnaces is not considered in the model (`Mandova et.al <https://doi.org/10.1016/j.biombioe.2018.04.021>`_, `Suopajärvi et.al <https://doi.org/10.1016/j.apenergy.2018.01.060>`_).
|
||||
|
||||
For the remaining subprocesses in this sector, the following transformations are assumed. Methane is used as energy source for the smelting process. Activities associated with furnaces, refining and rolling, and product finishing are electrified assuming the current efficiency values for these cases. These transformations result in changes in process emissions as outlined in the process emissions figure presented in the industry overview section (see :ref:`Overview`).
|
||||
|
||||
.. _Chemicals Industry:
|
||||
|
||||
**Chemicals Industry**
|
||||
|
||||
The chemicals industry includes a wide range of diverse industries, including the production of basic organic compounds (olefins, alcohols, aromatics), basic inorganic compounds (ammonia, chlorine), polymers (plastics), and end-user products (cosmetics, pharmaceutics).
|
||||
|
||||
The chemicals industry consumes large amounts of fossil-fuel based feedstocks (see `Levi et. al <https://pubs.acs.org/doi/10.1021/acs.est.7b04573>`_), which can also be produced from renewables as outlined for hydrogen (see :ref:`Hydrogen supply`), for methane (see :ref:`Methane supply`), and for oil-based products (see :ref:`Oil-based products supply`). The ratio between synthetic and fossil-based fuels used in the industry is an endogenous result of the optimisation.
|
||||
|
||||
The basic chemicals consumption data from the `JRC IDEES <https://op.europa.eu/en/publication-detail/-/publication/989282db-ad65-11e7-837e-01aa75ed71a1/language-en>`_ database comprises high- value chemicals (ethylene, propylene and BTX), chlorine, methanol and ammonia. However, it is necessary to separate out these chemicals because their current and future production routes are different.
|
||||
|
||||
Statistics for the production of ammonia, which is commonly used as a fertilizer, are taken from the `USGS <https://www.usgs.gov/media/files/nitrogen-2017-xlsx>`_ for every country. Ammonia can be made from hydrogen and nitrogen using the Haber-Bosch process.
|
||||
|
||||
.. math::
|
||||
N_2 + 3H_2 \xrightarrow{} 2NH_3
|
||||
|
||||
|
||||
|
||||
The Haber-Bosch process is not explicitly represented in the model, such that demand for ammonia enters the model as a demand for hydrogen ( 6.5 MWh :math:`_{H_2}` / t :math:`_{NH_3}` ) and electricity ( 1.17 MWh :math:`_{el}` /t :math:`_{NH_3}` ) (see `Wang et. al <https://doi.org/10.1016/j.joule.2018.04.017>`_). Today, natural gas dominates in Europe as the source for the hydrogen used in the Haber-Bosch process, but the model can choose among the various hydrogen supply options described in the hydrogen section (see :ref:`Hydrogen supply`)
|
||||
|
||||
The total production and specific energy consumption of chlorine and methanol is taken from a `DECHEMA report <https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry.pdf>`_. According to this source, the production of chlorine amounts to 9.58 MtCl/a, which is assumed to require electricity at 3.6 MWh :math:`_{el}`/t of chlorine and yield hydrogen at 0.937 MWh :math:`_{H_2}`/t of chlorine in the chloralkali process. The production of methanol adds up to 1.5 MtMeOH/a, requiring electricity at 0.167 MWh :math:`_{el}`/t of methanol and methane at 10.25 MWh :math:`_{CH_4}`/t of methanol.
|
||||
|
||||
|
||||
The production of ammonia, methanol, and chlorine production is deducted from the JRC IDEES basic chemicals, leaving the production totals of high-value chemicals. For this, we assume that the liquid hydrocarbon feedstock comes from synthetic or fossil- origin naphtha (14 MWh :math:`_{naphtha}`/t of HVC, similar to `Lechtenböhmer et al <https://doi.org/10.1016/j.energy.2016.07.110>`_), ignoring the methanol-to-olefin route. Furthermore, we assume the following transformations of the energy-consuming processes in the production of plastics: the final energy consumption in steam processing is converted to methane since requires temperature above 500 °C (4.1 MWh :math:`_{CH_4}` /t of HVC, see `Rehfeldt et al. <https://doi.org/10.1007/s12053-017-9571-y>`_); and the remaining processes are electrified using the current efficiency of microwave for high-enthalpy heat processing, electric furnaces, electric process cooling and electric generic processes (2.85 MWh :math:`_{el}`/t of HVC).
|
||||
|
||||
The process emissions from feedstock in the chemical industry are as high as 0.369 t :math:`_{CO_2}`/t of ethylene equivalent. We consider process emissions for all the material output, which is a conservative approach since it assumes that all plastic-embedded :math:`CO_2` will eventually be released into the atmosphere. However, plastic disposal in landfilling will avoid, or at least delay, associated :math:`CO_2` emissions.
|
||||
|
||||
Circular economy practices drastically reduce the amount of primary feedstock needed for the production of plastics in the model (see `Kullmann et al. <https://doi.org/10.1016/j.energy.2022.124660>`_, `Meys et al. (2021) <https://doi.org/10.1126/science.abg9853>`_, `Meys et al. (2020) <https://doi.org/10/gmxv6z>`_, `Gu et al. <https://doi.org/10/gf8n9w>`_) and consequently, also the energy demands and level of process emission. The percentage of plastics that are assumed to be mechanically recycled can be selected in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/776596ab9ac6a6cc93422ccfd0383abeffb0baa9/config.default.yaml#L315>`_, as well as
|
||||
the percentage that is chemically recycled, see `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/776596ab9ac6a6cc93422ccfd0383abeffb0baa9/config.default.yaml#L316>`_ The energy consumption for those recycling processes are respectively 0.547 MWh :math:`_{el}`/t of HVC (as indicated in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/776596ab9ac6a6cc93422ccfd0383abeffb0baa9/config.default.yaml#L318>`_) (`Meys et al. (2020) <https://doi.org/10/gmxv6z>`_), and 6.9 MWh :math:`_{el}`/t of HVC (as indicated in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/776596ab9ac6a6cc93422ccfd0383abeffb0baa9/config.default.yaml#L319>`_) based on pyrolysis and electric steam cracking (see `Materials Economics <https://materialeconomics.com/publications/industrial-transformation-2050>`_ report).
|
||||
|
||||
|
||||
**Non-metallic Mineral Products**
|
||||
|
||||
This subsector includes the manufacturing of cement, ceramics, and glass.
|
||||
|
||||
*Cement*
|
||||
|
||||
Cement is used in construction to make concrete. The production of cement involves high energy consumption and large process emissions. The calcination of limestone to chemically reactive calcium oxide, also known as lime, involves process emissions of 0.54 t :math:`_{CO_2}` /t cement (see `Akhtar et al. <https://doi.org/10.1109/CITCON.2013.6525276>`_.
|
||||
|
||||
|
||||
.. math::
|
||||
CaCO_3 \xrightarrow{} CaO + CO_2
|
||||
|
||||
|
||||
Additionally, :math:`CO_2` is emitted from the combustion of fossil fuels to provide process heat. Thereby, cement constitutes the biggest source of industry process emissions in Europe.
|
||||
|
||||
Cement process emissions can be captured assuming a capture rate of 90%. Whether emissions are captured is decided by the model taking into account the capital costs of carbon capture modules. The electricity and heat demand of process emission carbon capture is currently ignored. For net-zero emission scenarios, the remaining process emissions need to be compensated by negative emissions.
|
||||
|
||||
With the exception of electricity demand and biomass demand for low-temperature heat (0.06 MWh/t and 0.2 MWh/t), the final energy consumption of this subsector is assumed to be supplied by methane (0.52 MWh/t), which is capable of delivering the required high-temperature heat. This implies a switch from burning solid fuels to burning gas which will require adjustments of the `kilns <10.1109/CITCON.2013.6525276>`_. The share of fossil vs. synthetic methane consumed is a result of the optimisation
|
||||
|
||||
|
||||
*Ceramics*
|
||||
|
||||
The ceramics sector is assumed to be fully electrified based on the current efficiency of already electrified processes which include microwave drying and sintering of raw materials, electric kilns for primary production processes, electric furnaces for the `product finishing <https://data.europa.eu/doi/10.2760/182725>`_. In total, the final electricity consumption is 0.44 MWh/t of ceramic. The manufacturing of ceramics includes process emissions of 0.03 t :math:`_{CO_2}`/t of ceramic. For a detailed overview of the ceramics industry sector see `Furszyfer Del Rio et al <https://doi.org/10.1016/j.rser.2021.111885>`_.
|
||||
|
||||
*Glass*
|
||||
|
||||
The production of glass is assumed to be fully electrified based on the current efficiency of electric melting tanks and electric annealing which adds up to an electricity demand of 2.07 MWh :math:`_{el}`/t of `glass <https://doi.org/10/f9df2m>`_. The manufacturing of glass incurs process emissions of 0.1 t :math:`_{CO_2}`/t of glass. Potential efficiency improvements, which according to `Lechtenböhmer et al <https://doi.org/10/f9df2m>`_ could reduce energy demands to 0.85 MW :math:`_{el}`/t of glass, have not been considered. For a detailed overview of the glass industry sector see `Furszyfer Del Rio et al <https://doi.org/10.1016/j.rser.2021.111885>`_.
|
||||
|
||||
|
||||
**Non-ferrous Metals**
|
||||
|
||||
The non-ferrous metal subsector includes the manufacturing of base metals (aluminium, copper, lead, zinc), precious metals (gold, silver), and technology metals (molybdenum, cobalt, silicon).
|
||||
|
||||
The manufacturing of aluminium accounts for more than half of the final energy consumption of this subsector. Two alternative processing routes are used today to manufacture aluminium in Europe. The primary route represents 40% of the aluminium pro- duction, while the secondary route represents the remaining 60%.
|
||||
|
||||
The primary route involves two energy-intensive processes: the production of alumina from bauxite (aluminium ore) and the electrolysis to transform alumina into aluminium via the Hall-Héroult process
|
||||
|
||||
.. math::
|
||||
2Al_2O_3 +3C \xrightarrow{} 4Al+3CO_2
|
||||
|
||||
|
||||
The primary route requires high-enthalpy heat (2.3 MWh/t) to produce alumina which is supplied by methane and causes process emissions of 1.5 t :math:`_{CO_2}`/t aluminium. According to `Friedrichsen et al. <http://www.umweltbundesamt.de/en/publikationen/comparative-analysis-of-options-potential-for>`_, inert anodes might become commercially available by 2030 that would eliminate the process emissions, but they are not included in the model. Assuming all subprocesses are electrified, the primary route requires 15.4 MWh :math:`_{el}`/t of aluminium.
|
||||
|
||||
In the secondary route, scrap aluminium is remelted. The energy demand for this process is only 10% of the primary route and there are no associated process emissions. Assuming all subprocesses are electrified, the secondary route requires 1.7 MWh/t of aluminium. The share of aliminum manufactured by the primary and secondary route can be selected in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L297>`_]
|
||||
|
||||
For the other non-ferrous metals, we assume the electrification of the entire manufacturing process with an average electricity demand of 3.2 MWh :math:`_{el}`/t lead equivalent.
|
||||
|
||||
**Other Industry Subsectors**
|
||||
|
||||
The remaining industry subsectors include (a) pulp, paper, printing, (b) food, beverages, tobacco, (c) textiles and leather, (d) machinery equipment, (e) transport equipment, (f) wood and wood products, (g) others. Low- and mid-temperature process heat in these industries is assumed to be `supplied by biomass <https://doi.org/10.1016/j.rser.2021.110856>`_ while the remaining processes are electrified. None of the subsectors involve process emissions.
|
||||
|
||||
|
||||
Agriculture demand
|
||||
=========================
|
||||
|
||||
Energy demands for the agriculture, forestry and fishing sector per country are taken from the `JRC-IDEES database <http://data.europa.eu/89h/jrc-10110-10001>`_. Missing countries are filled with `Eurostat data <https://ec.europa.eu/eurostat/web/energy/data/energy-balances>`_. Agricultural energy demands are split into electricity (lighting, ventilation, specific electricity uses, electric pumping devices), heat (specific heat uses, low enthalpy heat), and machinery oil (motor drives, farming machine drives, diesel-fueled pumping devices). Heat demand is assigned at “services rural heat” buses. Time series for demands are assumed to be constant and distributed inside countries by population.
|
||||
|
||||
.. _Transportation:
|
||||
|
||||
Transportation
|
||||
=========================
|
||||
Annual energy demands for land transport, aviation and shipping for every country are retrieved from `JRC-IDEES data set <http://data.europa.eu/89h/jrc-10110-10001>`_. Below, the details of how each of these categories are treated is explained.
|
||||
|
||||
.. _Land transport:
|
||||
|
||||
**Land transport**
|
||||
|
||||
Both road and rail transport is combined as `land transport demand <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/scripts/build_transport_demand.py#L74>`_ although electrified rail transport is excluded because that demand is included in the current electricity demand.
|
||||
|
||||
The most important settings for land transport are the exogenously fixed fuel mix (an option enabling the endogeous optimization of transport electrification is planned but not yet implemented). In the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L181>`_, the share of battery electric vehicles (BEV) and hydrogen fuel cell vehicles (FCEV) can be set. The remaining percentage will be treated as internal combustion engines (ICE) that consume oil products.
|
||||
|
||||
*Battery Electric vehicles (BEV)*
|
||||
|
||||
For the electrified land transport, country-specific factors are computed by comparing the `current car final energy consumption per km in <https://www.sciencedirect.com/science/article/pii/S0360544216310295>`_ (average for Europe 0.7 kWh/km) to the 0.18 kWh/km value assumed for battery-to-wheels efficiency in EVs. The characteristic `weekly profile <https://www.bast.de/DE/Verkehrstechnik/Fachthemen/v2-verkehrszaehlung/zaehl_node.html>`_ provided by the German Federal Highway Research Institute (BASt) is used to obtain hourly time series for European countries taking into account the corresponding local times. Furthermore, a temperature dependence is included in the time series to account for heating/cooling demand in transport. For temperatures `below <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L166>`_/`above <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L165>`_ certain threshold values, e.g. 15 °C/20 °C, `temperature coefficients <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L169>`_ of typically 0.98%/°C and 0.63%/°C are assumed, based on the `paper <https://www.sciencedirect.com/science/article/pii/S036054421831288X>`_.
|
||||
|
||||
For BEVs the user can define the `storage energy capacity <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L173>`_, `charging power capacity <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L176>`_, and `charging efficiency <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L174>`_.
|
||||
|
||||
For BEV, smart charging is an option. A `certain share <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L172>`_ of the BEV fleet can shift their charging time. The BEV state of charge is forced to be higher than a `set percentage <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L163>`_, e.g. 75%, every day at a `specified hour <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L164>`_, e.g., 7 am, to ensure that the batteries are sufficiently charged for peak usage in the morning and they not behave as seasonal storage. They also have the option to participate in vehicle-to-grid (V2G) services to facilitate system operation if that `is enabled <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L179>`_.
|
||||
|
||||
The battery cost of BEV is not included in the model since it is assumed that BEV owners buy them to primarily satisfy their mobility needs.
|
||||
|
||||
*Hydrogen fuel cell vehicles (FCEV)*
|
||||
|
||||
The share of all land transport that is specified to be be FCEV will be converted to a demand for hydrogen (see :ref:`Hydrogen supply`) using the `FCEV efficiency
|
||||
<https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L191>`_.
|
||||
|
||||
FCEVs are typically used to simulate demand for transport that is hard to electrify directly, e.g. heavy construction machinery. But it may also be used to investigate a more widespread adoption of the technology.
|
||||
|
||||
*Internal combustion engine vehicles (ICE)*
|
||||
|
||||
All land transport that is not specified to be either BEV or FCEV will be treated as conventional ICEs. The transport demand is converted to a demand for oil products (see :ref:`Oil-based products supply`) using the `ICE efficiency
|
||||
<https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L192>`_.
|
||||
|
||||
.. _Aviation:
|
||||
|
||||
**Aviation**
|
||||
|
||||
The `demand for aviation <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/scripts/prepare_sector_network.py#L2193>`_ includes international and domestic use. It is modelled as an oil demand since aviation consumes kerosene. This can be produced synthetically or have fossil-origin (see :ref:`Oil-based products supply`).
|
||||
|
||||
.. _Shipping:
|
||||
|
||||
**Shipping**
|
||||
|
||||
Shipping energy demand is covered by a combination of oil and hydrogen. Other fuel options, like methanol or ammonia, are currently not included in PyPSA-Eur-Sec. The share of shipping that is assumed to be supplied by hydrogen can be selected in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L198>`_.
|
||||
|
||||
To estimate the `hydrogen demand <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/scripts/prepare_sector_network.py#L2090>`_, the average fuel efficiency of the fleet is used in combination with the efficiency of the fuel cell defined in the technology-data repository. The average fuel efficiency is set in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L196>`_.
|
||||
|
||||
The consumed hydrogen comes from the general hydrogen bus where it can be produced by SMR, SMR+CC or electrolysers (see :ref:`Hydrogen supply`). The fraction that is not converted into hydrogen use oil products, i.e. is connected to the general oil bus.
|
||||
|
||||
The energy demand for liquefaction of the hydrogen used for shipping can be `included <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L197>`_. If this option is selected, liquifaction will happen at the `node where the shipping demand occurs <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/scripts/prepare_sector_network.py#L2064>`_.
|
||||
|
||||
.. _Carbon dioxide capture, usage and sequestration (CCU/S):
|
||||
|
||||
Carbon dioxide capture, usage and sequestration (CCU/S)
|
||||
=========================================================
|
||||
|
||||
PyPSA-Eur-Sec includes carbon capture from air (i.e., direct air capture (DAC)), electricity generators, and industrial facilities. It furthermore includes carbon dioxide storage and transport, the usage of carbon dioxide in synthetic methane and oil products, as well as the sequestration of carbon dioxide underground.
|
||||
|
||||
**Carbon dioxide capture**
|
||||
|
||||
For the following point source emissions, carbon capture is applicable:
|
||||
|
||||
• Industry process emissions, e.g., from limestone in cement production
|
||||
|
||||
• Methane or biomass used for process heat in the industry
|
||||
|
||||
• Hydrogen production by SMR
|
||||
|
||||
• CHP plants using biomass or methane
|
||||
|
||||
• `Coal power plants <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L242>`_.
|
||||
|
||||
Point source emissions are captured assuming a capture rate, e.g. 90%, which can be specified in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L249>`_. The electricity and heat demand of process emission carbon capture
|
||||
is currently ignored.
|
||||
|
||||
DAC (if `included <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L243>`_) includes the adsorption phase where electricity and heat consumptionsare required to assist the adsorption process and regenerate the adsorbent. It also includes the drying and compression of :math:`CO_2` prior to storage which consumes electricity and rejects heat.
|
||||
|
||||
*Carbon dioxide usage*
|
||||
|
||||
Captured :math:`CO_2` can be used to produce synthetic methane and synthetic oil products (e.g.
|
||||
naphtha). If captured carbon is used, the :math:`CO_2` emissions of the synthetic fuels are net-neutral.
|
||||
|
||||
*Carbon dioxide sequestration*
|
||||
|
||||
Captured :math:`CO_2` can also be sequestered underground up to an annual sequestration limit of 200 Mt :math:`_{CO_2}`/a. This limit can be chosen in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L246>`_. As stored carbon dioxide is modelled as a single node for Europe, :math:`CO_2` transport constraints are neglected. Since :math:`CO_2` sequestration is an immature technology, the cost assumption is defined in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L247>`_.
|
||||
|
||||
*Carbon dioxide transport*
|
||||
|
||||
Carbon dioxide can be modelled as a single node for Europe (in this case, :math:`CO_2` transport constraints are neglected). A network for modelling the transport of :math:`CO_2` among the different nodes can also be created if selected in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L248>`_.
|
||||
152
doc/tutorial.rst
152
doc/tutorial.rst
@ -5,130 +5,121 @@
|
||||
|
||||
.. _tutorial:
|
||||
|
||||
#####################
|
||||
Tutorial
|
||||
#####################
|
||||
###############################
|
||||
Tutorial: Electricity-Only
|
||||
###############################
|
||||
|
||||
.. raw:: html
|
||||
|
||||
<iframe width="832" height="468" src="https://www.youtube.com/embed/mAwhQnNRIvs" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
|
||||
|
||||
Before getting started with **PyPSA-Eur** it makes sense to be familiar
|
||||
.. note::
|
||||
If you have not done it yet, follow the :ref:`installation` steps first.
|
||||
|
||||
In this tutorial, we will build a heavily simplified power system model for
|
||||
Belgium. But before getting started with **PyPSA-Eur** it makes sense to be familiar
|
||||
with its general modelling framework `PyPSA <https://pypsa.readthedocs.io>`__.
|
||||
|
||||
Running the tutorial requires limited computational resources compared to the full model,
|
||||
which allows the user to explore most of its functionalities on a local machine.
|
||||
It takes approximately five minutes to complete and
|
||||
requires 3 GB of memory along with 1 GB free disk space.
|
||||
|
||||
If not yet completed, follow the :ref:`installation` steps first.
|
||||
|
||||
The tutorial will cover examples on how to
|
||||
|
||||
- configure and customise the PyPSA-Eur model and
|
||||
- run the ``snakemake`` workflow step by step from network creation to the solved network.
|
||||
|
||||
The configuration of the tutorial is included in the ``config.tutorial.yaml``.
|
||||
To run the tutorial, use this as your configuration file ``config.yaml``.
|
||||
Running the tutorial requires limited computational resources compared to the
|
||||
full model, which allows the user to explore most of its functionalities on a
|
||||
local machine. The tutorial will cover examples on how to configure and
|
||||
customise the PyPSA-Eur model and run the ``snakemake`` workflow step by step
|
||||
from network creation to the solved network. The configuration for the tutorial
|
||||
is located at ``test/config.electricity.yaml``. It includes parts deviating from
|
||||
the default config file ``config.default.yaml``. To run the tutorial with this
|
||||
configuration, execute
|
||||
|
||||
.. code:: bash
|
||||
:class: full-width
|
||||
|
||||
.../pypsa-eur % cp config.tutorial.yaml config.yaml
|
||||
snakemake -call --configfile test/config.electricity.yaml results/networks/elec_s_6_ec_lcopt_Co2L-24H.nc
|
||||
|
||||
This configuration is set to download a reduced data set via the rules :mod:`retrieve_databundle`,
|
||||
:mod:`retrieve_natura_raster`, :mod:`retrieve_cutout` totalling at less than 250 MB.
|
||||
The full set of data dependencies would take 5.3 GB.
|
||||
:mod:`retrieve_natura_raster`, :mod:`retrieve_cutout`.
|
||||
For more information on the data dependencies of PyPSA-Eur, continue reading :ref:`data`.
|
||||
|
||||
How to customise PyPSA-Eur?
|
||||
How to configure runs?
|
||||
===========================
|
||||
|
||||
The model can be adapted to only include selected countries (e.g. Belgium) instead of all European countries to limit the spatial scope.
|
||||
|
||||
.. literalinclude:: ../config.tutorial.yaml
|
||||
.. literalinclude:: ../test/config.electricity.yaml
|
||||
:language: yaml
|
||||
:start-at: countries:
|
||||
:end-before: snapshots:
|
||||
|
||||
Likewise, the example's temporal scope can be restricted (e.g. to a single month).
|
||||
Likewise, the example's temporal scope can be restricted (e.g. to a single week).
|
||||
|
||||
.. literalinclude:: ../config.tutorial.yaml
|
||||
.. literalinclude:: ../test/config.electricity.yaml
|
||||
:language: yaml
|
||||
:start-at: snapshots:
|
||||
:end-before: enable:
|
||||
:end-before: electricity:
|
||||
|
||||
It is also possible to allow less or more carbon-dioxide emissions. Here, we limit the emissions of Germany 100 Megatonnes per year.
|
||||
It is also possible to allow less or more carbon-dioxide emissions. Here, we limit the emissions of Belgium to 100 Mt per year.
|
||||
|
||||
.. literalinclude:: ../config.tutorial.yaml
|
||||
.. literalinclude:: ../test/config.electricity.yaml
|
||||
:language: yaml
|
||||
:start-at: electricity:
|
||||
:end-before: extendable_carriers:
|
||||
|
||||
PyPSA-Eur also includes a database of existing conventional powerplants.
|
||||
We can select which types of powerplants we like to be included:
|
||||
We can select which types of existing powerplants we like to be extendable:
|
||||
|
||||
.. literalinclude:: ../config.tutorial.yaml
|
||||
.. literalinclude:: ../test/config.electricity.yaml
|
||||
:language: yaml
|
||||
:start-at: extendable_carriers:
|
||||
:end-before: max_hours:
|
||||
:end-before: renewable_carriers:
|
||||
|
||||
To accurately model the temporal and spatial availability of renewables such as wind and solar energy, we rely on historical weather data.
|
||||
It is advisable to adapt the required range of coordinates to the selection of countries.
|
||||
To accurately model the temporal and spatial availability of renewables such as
|
||||
wind and solar energy, we rely on historical weather data. It is advisable to
|
||||
adapt the required range of coordinates to the selection of countries.
|
||||
|
||||
.. literalinclude:: ../config.tutorial.yaml
|
||||
.. literalinclude:: ../test/config.electricity.yaml
|
||||
:language: yaml
|
||||
:start-at: atlite:
|
||||
:end-before: renewable:
|
||||
|
||||
We can also decide which weather data source should be used to calculate potentials and capacity factor time-series for each carrier.
|
||||
For example, we may want to use the ERA-5 dataset for solar and not the default SARAH-2 dataset.
|
||||
We can also decide which weather data source should be used to calculate
|
||||
potentials and capacity factor time-series for each carrier. For example, we may
|
||||
want to use the ERA-5 dataset for solar and not the default SARAH-2 dataset.
|
||||
|
||||
.. literalinclude:: ../config.tutorial.yaml
|
||||
:language: yaml
|
||||
:start-at: be-03-2013-era5:
|
||||
:end-at: module:
|
||||
|
||||
.. literalinclude:: ../config.tutorial.yaml
|
||||
.. literalinclude:: ../test/config.electricity.yaml
|
||||
:language: yaml
|
||||
:start-at: solar:
|
||||
:end-at: cutout:
|
||||
|
||||
Finally, it is possible to pick a solver. For instance, this tutorial uses the open-source solvers CBC and Ipopt and does not rely
|
||||
on the commercial solvers Gurobi or CPLEX (for which free academic licenses are available).
|
||||
Finally, it is possible to pick a solver. For instance, this tutorial uses the
|
||||
open-source solver GLPK.
|
||||
|
||||
.. literalinclude:: ../config.tutorial.yaml
|
||||
.. literalinclude:: ../test/config.electricity.yaml
|
||||
:language: yaml
|
||||
:start-at: solver:
|
||||
:end-before: plotting:
|
||||
|
||||
.. note::
|
||||
Note, that ``test/config.electricity.yaml`` only includes changes relative to
|
||||
the default configuration. There are many more configuration options, which are
|
||||
documented at :ref:`config`.
|
||||
|
||||
To run the tutorial, either install CBC and Ipopt (see instructions for :ref:`installation`).
|
||||
|
||||
Alternatively, choose another installed solver in the ``config.yaml`` at ``solving: solver:``.
|
||||
|
||||
Note, that we only focus on changes relative to the default configuration.
|
||||
There are many more configuration options, which are documented at :ref:`config`.
|
||||
|
||||
How to use the ``snakemake`` rules?
|
||||
How to use ``snakemake`` rules?
|
||||
===================================
|
||||
|
||||
Open a terminal, go into the PyPSA-Eur directory, and activate the ``pypsa-eur`` environment with
|
||||
|
||||
.. code:: bash
|
||||
|
||||
.../pypsa-eur % conda activate pypsa-eur
|
||||
mamba activate pypsa-eur
|
||||
|
||||
Let's say based on the modifications above we would like to solve a very simplified model
|
||||
clustered down to 6 buses and every 24 hours aggregated to one snapshot. The command
|
||||
|
||||
.. code:: bash
|
||||
|
||||
.../pypsa-eur % snakemake -call results/networks/elec_s_6_ec_lcopt_Co2L-24H.nc
|
||||
snakemake -call --configfile test/config.electricity.yaml results/networks/elec_s_6_ec_lcopt_Co2L-24H.nc
|
||||
|
||||
orders ``snakemake`` to run the script ``solve_network`` that produces the solved network and stores it in ``.../pypsa-eur/results/networks`` with the name ``elec_s_6_ec_lcopt_Co2L-24H.nc``:
|
||||
orders ``snakemake`` to run the rule :mod:`solve_network` that produces the solved network and stores it in ``results/networks`` with the name ``elec_s_6_ec_lcopt_Co2L-24H.nc``:
|
||||
|
||||
.. literalinclude:: ../Snakefile
|
||||
.. literalinclude:: ../rules/solve_electricity.smk
|
||||
:start-at: rule solve_network:
|
||||
:end-before: rule solve_operations_network:
|
||||
|
||||
@ -234,7 +225,6 @@ In the terminal, this will show up as a list of jobs to be run:
|
||||
.. code:: bash
|
||||
|
||||
Building DAG of jobs...
|
||||
Job stats:
|
||||
job count min threads max threads
|
||||
------------------------ ------- ------------- -------------
|
||||
add_electricity 1 1 1
|
||||
@ -282,38 +272,52 @@ You can produce any output file occurring in the ``Snakefile`` by running
|
||||
|
||||
.. code:: bash
|
||||
|
||||
.../pypsa-eur % snakemake -call <output file>
|
||||
snakemake -call <output file>
|
||||
|
||||
For example, you can explore the evolution of the PyPSA networks by running
|
||||
|
||||
#. ``.../pypsa-eur % snakemake -call networks/base.nc``
|
||||
#. ``.../pypsa-eur % snakemake -call networks/elec.nc``
|
||||
#. ``.../pypsa-eur % snakemake -call networks/elec_s.nc``
|
||||
#. ``.../pypsa-eur % snakemake -call networks/elec_s_6.nc``
|
||||
#. ``.../pypsa-eur % snakemake -call networks/elec_s_6_ec_lcopt_Co2L-24H.nc``
|
||||
#. ``snakemake -call --configfile test/config.electricity.yaml resources/networks/base.nc``
|
||||
#. ``snakemake -call --configfile test/config.electricity.yaml resources/networks/elec.nc``
|
||||
#. ``snakemake -call --configfile test/config.electricity.yaml resources/networks/elec_s.nc``
|
||||
#. ``snakemake -call --configfile test/config.electricity.yaml resources/networks/elec_s_6.nc``
|
||||
#. ``snakemake -call --configfile test/config.electricity.yaml resources/networks/elec_s_6_ec_lcopt_Co2L-24H.nc``
|
||||
|
||||
There's a special rule: If you simply run
|
||||
To run all combinations of wildcard values provided in the ``config.yaml`` under ``scenario:``,
|
||||
you can use the collection rule ``solve_elec_networks``.
|
||||
|
||||
.. code:: bash
|
||||
|
||||
.../pypsa-eur % snakemake
|
||||
snakemake -call --configfile test/config.electricity.yaml solve_elec_networks
|
||||
|
||||
the wildcards given in ``scenario`` in the configuration file ``config.yaml`` are used:
|
||||
If you now feel confident and want to tackle runs with larger temporal and
|
||||
spatial scope, clean-up the repository and after modifying the ``config.yaml`` file
|
||||
target the collection rule ``solve_elec_networks`` again without providing the test
|
||||
configuration file.
|
||||
|
||||
.. literalinclude:: ../config.tutorial.yaml
|
||||
:language: yaml
|
||||
:start-at: scenario:
|
||||
:end-before: countries:
|
||||
.. code:: bash
|
||||
|
||||
How to analyse solved networks?
|
||||
snakemake -call purge
|
||||
snakemake -call solve_elec_networks
|
||||
|
||||
.. note::
|
||||
|
||||
It is good practice to perform a dry-run using the option `-n`, before you
|
||||
commit to a run:
|
||||
|
||||
.. code:: bash
|
||||
|
||||
snakemake -call solve_elec_networks -n
|
||||
|
||||
How to analyse results?
|
||||
===============================
|
||||
|
||||
The solved networks can be analysed just like any other PyPSA network (e.g. in Jupyter Notebooks).
|
||||
The solved networks can be analysed just like any other PyPSA network (e.g. in
|
||||
Jupyter Notebooks).
|
||||
|
||||
.. code:: python
|
||||
|
||||
import pypsa
|
||||
|
||||
network = pypsa.Network("results/networks/elec_s_6_ec_lcopt_Co2L-24H.nc")
|
||||
n = pypsa.Network("results/networks/elec_s_6_ec_lcopt_Co2L-24H.nc")
|
||||
|
||||
For inspiration, read the `examples section in the PyPSA documentation <https://pypsa.readthedocs.io/en/latest/examples-basic.html>`_.
|
||||
|
||||
532
doc/tutorial_sector.rst
Normal file
532
doc/tutorial_sector.rst
Normal file
@ -0,0 +1,532 @@
|
||||
..
|
||||
SPDX-FileCopyrightText: 2023 The PyPSA-Eur Authors
|
||||
|
||||
SPDX-License-Identifier: CC-BY-4.0
|
||||
|
||||
.. _tutorial_sector:
|
||||
|
||||
###############################
|
||||
Tutorial: Sector-Coupled
|
||||
###############################
|
||||
|
||||
.. note::
|
||||
If you have not done it yet, follow the :ref:`installation` steps first.
|
||||
|
||||
Also, checkout the tutorial for electricity-only systems first at :ref:`tutorial`.
|
||||
|
||||
In this tutorial, we will add further sectors to the electricity-only model from
|
||||
:ref:`tutorial`, namely industry, transport, and buildings. This
|
||||
requires processing of a few more raw data sources.
|
||||
|
||||
The sector-coupling code can be run as an overnight / greenfield scenario or
|
||||
with multi-horizon investment with myopic foresight. Pathway analysis with
|
||||
perfect foresight is under development. See also the documentation on
|
||||
:ref:`foresight`.
|
||||
|
||||
Overnight Scenarios
|
||||
===========================
|
||||
|
||||
Configuration
|
||||
-------------
|
||||
|
||||
The default configuration file (``config.default.yaml``) is set up for running
|
||||
overnight scenarios. Running a sector-coupled model unlocks many further
|
||||
configuration options. In the example below, we say that the gas network should
|
||||
be added and spatially resolved. We also say that the existing gas network may
|
||||
be retrofitted to transport hydrogen instead.
|
||||
|
||||
.. literalinclude:: ../test/config.overnight.yaml
|
||||
:language: yaml
|
||||
:start-at: sector:
|
||||
:end-before: solving:
|
||||
|
||||
Documentation for all options will be added successively to :ref:`config`.
|
||||
|
||||
Scenarios can be defined like for electricity-only studies, but with additional
|
||||
wildcard options.
|
||||
|
||||
.. literalinclude:: ../test/config.overnight.yaml
|
||||
:language: yaml
|
||||
:start-at: scenario:
|
||||
:end-before: countries:
|
||||
|
||||
For allowed wildcard values, refer to :ref:`wildcards`.
|
||||
|
||||
Execution
|
||||
---------
|
||||
|
||||
To run an overnight / greenfiled scenario with the specifications above, run
|
||||
|
||||
.. code:: bash
|
||||
|
||||
snakemake -call --configfile test/config.overnight.yaml all
|
||||
|
||||
which will result in the following *additional* jobs ``snakemake`` wants to run
|
||||
on top of those already included in the electricity-only tutorial:
|
||||
|
||||
.. code:: bash
|
||||
|
||||
job count min threads max threads
|
||||
------------------------------------------------ ------- ------------- -------------
|
||||
all 1 1 1
|
||||
build_ammonia_production 1 1 1
|
||||
build_biomass_potentials 1 1 1
|
||||
build_clustered_population_layouts 1 1 1
|
||||
build_cop_profiles 1 1 1
|
||||
build_gas_input_locations 1 1 1
|
||||
build_gas_network 1 1 1
|
||||
build_heat_demands 3 1 1
|
||||
build_industrial_distribution_key 1 1 1
|
||||
build_industrial_energy_demand_per_country_today 1 1 1
|
||||
build_industrial_energy_demand_per_node 1 1 1
|
||||
build_industrial_energy_demand_per_node_today 1 1 1
|
||||
build_industrial_production_per_country 1 1 1
|
||||
build_industrial_production_per_country_tomorrow 1 1 1
|
||||
build_industrial_production_per_node 1 1 1
|
||||
build_industry_sector_ratios 1 1 1
|
||||
build_population_weighted_energy_totals 1 1 1
|
||||
build_salt_cavern_potentials 1 1 1
|
||||
build_shipping_demand 1 1 1
|
||||
build_simplified_population_layouts 1 1 1
|
||||
build_solar_thermal_profiles 3 1 1
|
||||
build_temperature_profiles 3 1 1
|
||||
build_transport_demand 1 1 1
|
||||
cluster_gas_network 1 1 1
|
||||
cluster_network 1 1 1
|
||||
copy_config 1 1 1
|
||||
make_summary 1 1 1
|
||||
plot_network 1 1 1
|
||||
plot_summary 1 1 1
|
||||
prepare_sector_network 1 1 1
|
||||
retrieve_gas_infrastructure_data 1 1 1
|
||||
retrieve_sector_databundle 1 1 1
|
||||
solve_sector_network 1 1 1
|
||||
|
||||
This covers the retrieval of additional raw data from online resources and
|
||||
preprocessing data about the transport, industry, and heating sectors as well as
|
||||
additional rules about geological storage and sequestration potentials, gas
|
||||
infrastructure, and biomass potentials. The collection rule ``all`` will also
|
||||
generate summary CSV files and plots after the network has been solved
|
||||
successfully.
|
||||
|
||||
|
||||
|
||||
.. graphviz::
|
||||
:class: full-width
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph[bgcolor=white, margin=0];
|
||||
node[shape=box, style=rounded, fontname=sans, fontsize=10, penwidth=2];
|
||||
edge[penwidth=2, color=grey];
|
||||
0[label = "all", color = "0.51 0.6 0.85", style="rounded"];
|
||||
1[label = "plot_summary", color = "0.54 0.6 0.85", style="rounded"];
|
||||
2[label = "make_summary", color = "0.44 0.6 0.85", style="rounded"];
|
||||
3[label = "solve_sector_network", color = "0.46 0.6 0.85", style="rounded"];
|
||||
4[label = "prepare_sector_network", color = "0.09 0.6 0.85", style="rounded"];
|
||||
5[label = "cluster_gas_network", color = "0.38 0.6 0.85", style="rounded"];
|
||||
6[label = "build_gas_network", color = "0.00 0.6 0.85", style="rounded"];
|
||||
7[label = "retrieve_gas_infrastructure_data", color = "0.33 0.6 0.85", style="rounded"];
|
||||
8[label = "cluster_network", color = "0.26 0.6 0.85", style="rounded"];
|
||||
9[label = "simplify_network", color = "0.03 0.6 0.85", style="rounded"];
|
||||
10[label = "add_electricity", color = "0.25 0.6 0.85", style="rounded"];
|
||||
11[label = "build_renewable_profiles", color = "0.07 0.6 0.85", style="rounded"];
|
||||
12[label = "base_network", color = "0.16 0.6 0.85", style="rounded"];
|
||||
13[label = "build_shapes", color = "0.65 0.6 0.85", style="rounded"];
|
||||
14[label = "retrieve_databundle", color = "0.20 0.6 0.85", style="rounded"];
|
||||
15[label = "retrieve_natura_raster", color = "0.10 0.6 0.85", style="rounded"];
|
||||
16[label = "build_bus_regions", color = "0.11 0.6 0.85", style="rounded"];
|
||||
17[label = "build_ship_raster", color = "0.56 0.6 0.85", style="rounded"];
|
||||
18[label = "retrieve_ship_raster", color = "0.15 0.6 0.85", style="rounded"];
|
||||
19[label = "retrieve_cost_data", color = "0.50 0.6 0.85", style="rounded"];
|
||||
20[label = "build_powerplants", color = "0.49 0.6 0.85", style="rounded"];
|
||||
21[label = "build_load_data", color = "0.39 0.6 0.85", style="rounded"];
|
||||
22[label = "retrieve_load_data", color = "0.05 0.6 0.85", style="rounded"];
|
||||
23[label = "build_gas_input_locations", color = "0.45 0.6 0.85", style="rounded"];
|
||||
24[label = "prepare_network", color = "0.31 0.6 0.85", style="rounded"];
|
||||
25[label = "add_extra_components", color = "0.23 0.6 0.85", style="rounded"];
|
||||
26[label = "build_energy_totals", color = "0.19 0.6 0.85", style="rounded"];
|
||||
27[label = "build_population_weighted_energy_totals", color = "0.27 0.6 0.85", style="rounded"];
|
||||
28[label = "build_clustered_population_layouts", color = "0.64 0.6 0.85", style="rounded"];
|
||||
29[label = "build_population_layouts", color = "0.43 0.6 0.85", style="rounded"];
|
||||
30[label = "build_shipping_demand", color = "0.57 0.6 0.85", style="rounded"];
|
||||
31[label = "build_transport_demand", color = "0.53 0.6 0.85", style="rounded"];
|
||||
32[label = "build_temperature_profiles", color = "0.58 0.6 0.85", style="rounded"];
|
||||
33[label = "build_biomass_potentials", color = "0.30 0.6 0.85", style="rounded"];
|
||||
34[label = "build_salt_cavern_potentials", color = "0.47 0.6 0.85", style="rounded"];
|
||||
35[label = "build_simplified_population_layouts", color = "0.32 0.6 0.85", style="rounded"];
|
||||
36[label = "build_industrial_energy_demand_per_node", color = "0.14 0.6 0.85", style="rounded"];
|
||||
37[label = "build_industry_sector_ratios", color = "0.18 0.6 0.85", style="rounded"];
|
||||
38[label = "build_ammonia_production", color = "0.48 0.6 0.85", style="rounded"];
|
||||
39[label = "build_industrial_production_per_node", color = "0.12 0.6 0.85", style="rounded"];
|
||||
40[label = "build_industrial_distribution_key", color = "0.61 0.6 0.85", style="rounded"];
|
||||
41[label = "build_industrial_production_per_country_tomorrow", color = "0.22 0.6 0.85", style="rounded"];
|
||||
42[label = "build_industrial_production_per_country", color = "0.59 0.6 0.85", style="rounded"];
|
||||
43[label = "build_industrial_energy_demand_per_node_today", color = "0.62 0.6 0.85", style="rounded"];
|
||||
44[label = "build_industrial_energy_demand_per_country_today", color = "0.41 0.6 0.85", style="rounded"];
|
||||
45[label = "build_heat_demands", color = "0.08 0.6 0.85", style="rounded"];
|
||||
46[label = "build_cop_profiles", color = "0.52 0.6 0.85", style="rounded"];
|
||||
47[label = "build_solar_thermal_profiles", color = "0.17 0.6 0.85", style="rounded"];
|
||||
48[label = "copy_config", color = "0.40 0.6 0.85", style="rounded"];
|
||||
49[label = "plot_network", color = "0.60 0.6 0.85", style="rounded"];
|
||||
1 -> 0
|
||||
2 -> 1
|
||||
49 -> 2
|
||||
19 -> 2
|
||||
3 -> 2
|
||||
48 -> 3
|
||||
4 -> 3
|
||||
19 -> 3
|
||||
9 -> 4
|
||||
11 -> 4
|
||||
45 -> 4
|
||||
36 -> 4
|
||||
47 -> 4
|
||||
26 -> 4
|
||||
27 -> 4
|
||||
8 -> 4
|
||||
33 -> 4
|
||||
24 -> 4
|
||||
35 -> 4
|
||||
5 -> 4
|
||||
23 -> 4
|
||||
34 -> 4
|
||||
19 -> 4
|
||||
31 -> 4
|
||||
46 -> 4
|
||||
30 -> 4
|
||||
32 -> 4
|
||||
28 -> 4
|
||||
6 -> 5
|
||||
8 -> 5
|
||||
7 -> 6
|
||||
19 -> 8
|
||||
9 -> 8
|
||||
19 -> 9
|
||||
10 -> 9
|
||||
16 -> 9
|
||||
14 -> 10
|
||||
21 -> 10
|
||||
20 -> 10
|
||||
19 -> 10
|
||||
11 -> 10
|
||||
16 -> 10
|
||||
13 -> 10
|
||||
12 -> 10
|
||||
14 -> 11
|
||||
17 -> 11
|
||||
15 -> 11
|
||||
16 -> 11
|
||||
12 -> 11
|
||||
13 -> 11
|
||||
13 -> 12
|
||||
14 -> 13
|
||||
12 -> 16
|
||||
13 -> 16
|
||||
18 -> 17
|
||||
12 -> 20
|
||||
22 -> 21
|
||||
8 -> 23
|
||||
7 -> 23
|
||||
25 -> 24
|
||||
19 -> 24
|
||||
19 -> 25
|
||||
8 -> 25
|
||||
13 -> 26
|
||||
28 -> 27
|
||||
26 -> 27
|
||||
8 -> 28
|
||||
29 -> 28
|
||||
13 -> 29
|
||||
13 -> 30
|
||||
8 -> 30
|
||||
26 -> 30
|
||||
32 -> 31
|
||||
28 -> 31
|
||||
27 -> 31
|
||||
26 -> 31
|
||||
8 -> 32
|
||||
29 -> 32
|
||||
13 -> 33
|
||||
14 -> 33
|
||||
8 -> 33
|
||||
8 -> 34
|
||||
9 -> 35
|
||||
29 -> 35
|
||||
37 -> 36
|
||||
39 -> 36
|
||||
43 -> 36
|
||||
38 -> 37
|
||||
41 -> 39
|
||||
40 -> 39
|
||||
28 -> 40
|
||||
8 -> 40
|
||||
42 -> 41
|
||||
38 -> 42
|
||||
44 -> 43
|
||||
40 -> 43
|
||||
38 -> 44
|
||||
42 -> 44
|
||||
8 -> 45
|
||||
29 -> 45
|
||||
32 -> 46
|
||||
8 -> 47
|
||||
29 -> 47
|
||||
8 -> 49
|
||||
3 -> 49
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
Myopic Foresight Scenarios
|
||||
===================================
|
||||
|
||||
Configuration
|
||||
-------------
|
||||
|
||||
To activate the myopic foresight mode, set
|
||||
|
||||
.. code:: yaml
|
||||
|
||||
foresight: myopic
|
||||
|
||||
Scenarios can be defined like for electricity-only studies, but with additional
|
||||
wildcard options. For the myopic foresight mode, the ``{planning_horizons}`` wildcard
|
||||
defines the sequence of investment horizons.
|
||||
|
||||
.. literalinclude:: ../test/config.myopic.yaml
|
||||
:language: yaml
|
||||
:start-at: scenario:
|
||||
:end-before: countries:
|
||||
|
||||
For allowed wildcard values, refer to :ref:`wildcards`.
|
||||
|
||||
In the myopic foresight mode, you can tweak for instance exogenously given transition paths, like the one for
|
||||
the share of primary steel production we change below:
|
||||
|
||||
.. literalinclude:: ../test/config.myopic.yaml
|
||||
:language: yaml
|
||||
:start-at: industry:
|
||||
:end-before: solving:
|
||||
|
||||
Documentation for all options will be added successively to :ref:`config`.
|
||||
|
||||
Execution
|
||||
---------
|
||||
|
||||
To run a myopic foresight scenario with the specifications above, run
|
||||
|
||||
.. code:: bash
|
||||
|
||||
snakemake -call --configfile test/config.myopic.yaml all
|
||||
|
||||
which will result in the following *additional* jobs ``snakemake`` wants to run:
|
||||
|
||||
.. code:: bash
|
||||
|
||||
job count min threads max threads
|
||||
------------------------------------------------ ------- ------------- -------------
|
||||
all 1 1 1
|
||||
add_brownfield 2 1 1
|
||||
add_existing_baseyear 1 1 1
|
||||
plot_network 3 1 1
|
||||
plot_summary 1 1 1
|
||||
prepare_sector_network 3 1 1
|
||||
solve_sector_network_myopic 3 1 1
|
||||
|
||||
which translates to the following workflow diagram which nicely outlines
|
||||
how the sequential pathway optimisation with myopic foresight is
|
||||
implemented in the workflow:
|
||||
|
||||
.. graphviz::
|
||||
:class: full-width
|
||||
:align: center
|
||||
|
||||
digraph snakemake_dag {
|
||||
graph[bgcolor=white, margin=0];
|
||||
node[shape=box, style=rounded, fontname=sans, fontsize=10, penwidth=2];
|
||||
edge[penwidth=2, color=grey];
|
||||
0[label = "all", color = "0.38 0.6 0.85", style="rounded"];
|
||||
1[label = "plot_summary", color = "0.61 0.6 0.85", style="rounded"];
|
||||
2[label = "make_summary", color = "0.51 0.6 0.85", style="rounded"];
|
||||
3[label = "solve_sector_network_myopic", color = "0.32 0.6 0.85", style="rounded"];
|
||||
4[label = "add_existing_baseyear", color = "0.20 0.6 0.85", style="rounded"];
|
||||
5[label = "prepare_sector_network", color = "0.14 0.6 0.85", style="rounded"];
|
||||
6[label = "prepare_network", color = "0.06 0.6 0.85", style="rounded"];
|
||||
7[label = "add_extra_components", color = "0.00 0.6 0.85", style="rounded"];
|
||||
8[label = "cluster_network", color = "0.18 0.6 0.85", style="rounded"];
|
||||
9[label = "simplify_network", color = "0.30 0.6 0.85", style="rounded"];
|
||||
10[label = "add_electricity", color = "0.24 0.6 0.85", style="rounded"];
|
||||
11[label = "build_renewable_profiles", color = "0.40 0.6 0.85", style="rounded"];
|
||||
12[label = "base_network", color = "0.11 0.6 0.85", style="rounded"];
|
||||
13[label = "build_shapes", color = "0.29 0.6 0.85", style="rounded"];
|
||||
14[label = "retrieve_databundle", color = "0.58 0.6 0.85", style="rounded"];
|
||||
15[label = "retrieve_natura_raster", color = "0.39 0.6 0.85", style="rounded"];
|
||||
16[label = "build_bus_regions", color = "0.60 0.6 0.85", style="rounded"];
|
||||
17[label = "build_ship_raster", color = "0.65 0.6 0.85", style="rounded"];
|
||||
18[label = "retrieve_ship_raster", color = "0.09 0.6 0.85", style="rounded"];
|
||||
19[label = "retrieve_cost_data", color = "0.04 0.6 0.85", style="rounded"];
|
||||
20[label = "build_powerplants", color = "0.28 0.6 0.85", style="rounded"];
|
||||
21[label = "build_load_data", color = "0.46 0.6 0.85", style="rounded"];
|
||||
22[label = "retrieve_load_data", color = "0.44 0.6 0.85", style="rounded"];
|
||||
23[label = "build_energy_totals", color = "0.53 0.6 0.85", style="rounded"];
|
||||
24[label = "build_population_weighted_energy_totals", color = "0.03 0.6 0.85", style="rounded"];
|
||||
25[label = "build_clustered_population_layouts", color = "0.34 0.6 0.85", style="rounded"];
|
||||
26[label = "build_population_layouts", color = "0.63 0.6 0.85", style="rounded"];
|
||||
27[label = "build_shipping_demand", color = "0.05 0.6 0.85", style="rounded"];
|
||||
28[label = "build_transport_demand", color = "0.52 0.6 0.85", style="rounded"];
|
||||
29[label = "build_temperature_profiles", color = "0.16 0.6 0.85", style="rounded"];
|
||||
30[label = "build_biomass_potentials", color = "0.47 0.6 0.85", style="rounded"];
|
||||
31[label = "build_salt_cavern_potentials", color = "0.48 0.6 0.85", style="rounded"];
|
||||
32[label = "build_simplified_population_layouts", color = "0.08 0.6 0.85", style="rounded"];
|
||||
33[label = "build_industrial_energy_demand_per_node", color = "0.22 0.6 0.85", style="rounded"];
|
||||
34[label = "build_industry_sector_ratios", color = "0.56 0.6 0.85", style="rounded"];
|
||||
35[label = "build_ammonia_production", color = "0.57 0.6 0.85", style="rounded"];
|
||||
36[label = "build_industrial_production_per_node", color = "0.66 0.6 0.85", style="rounded"];
|
||||
37[label = "build_industrial_distribution_key", color = "0.41 0.6 0.85", style="rounded"];
|
||||
38[label = "build_industrial_production_per_country_tomorrow", color = "0.54 0.6 0.85", style="rounded"];
|
||||
39[label = "build_industrial_production_per_country", color = "0.10 0.6 0.85", style="rounded"];
|
||||
40[label = "build_industrial_energy_demand_per_node_today", color = "0.55 0.6 0.85", style="rounded"];
|
||||
41[label = "build_industrial_energy_demand_per_country_today", color = "0.35 0.6 0.85", style="rounded"];
|
||||
42[label = "build_heat_demands", color = "0.49 0.6 0.85", style="rounded"];
|
||||
43[label = "build_cop_profiles", color = "0.01 0.6 0.85", style="rounded"];
|
||||
44[label = "build_solar_thermal_profiles", color = "0.45 0.6 0.85", style="rounded"];
|
||||
45[label = "copy_config", color = "0.33 0.6 0.85", style="rounded"];
|
||||
46[label = "add_brownfield", color = "0.59 0.6 0.85", style="rounded"];
|
||||
47[label = "plot_network", color = "0.15 0.6 0.85", style="rounded"];
|
||||
1 -> 0
|
||||
2 -> 1
|
||||
3 -> 2
|
||||
19 -> 2
|
||||
47 -> 2
|
||||
46 -> 3
|
||||
19 -> 3
|
||||
4 -> 3
|
||||
45 -> 3
|
||||
43 -> 4
|
||||
19 -> 4
|
||||
20 -> 4
|
||||
9 -> 4
|
||||
5 -> 4
|
||||
25 -> 4
|
||||
8 -> 4
|
||||
28 -> 5
|
||||
23 -> 5
|
||||
11 -> 5
|
||||
33 -> 5
|
||||
24 -> 5
|
||||
43 -> 5
|
||||
19 -> 5
|
||||
27 -> 5
|
||||
6 -> 5
|
||||
31 -> 5
|
||||
32 -> 5
|
||||
44 -> 5
|
||||
9 -> 5
|
||||
30 -> 5
|
||||
25 -> 5
|
||||
29 -> 5
|
||||
42 -> 5
|
||||
8 -> 5
|
||||
7 -> 6
|
||||
19 -> 6
|
||||
19 -> 7
|
||||
8 -> 7
|
||||
9 -> 8
|
||||
19 -> 8
|
||||
10 -> 9
|
||||
19 -> 9
|
||||
16 -> 9
|
||||
11 -> 10
|
||||
19 -> 10
|
||||
14 -> 10
|
||||
20 -> 10
|
||||
12 -> 10
|
||||
21 -> 10
|
||||
16 -> 10
|
||||
13 -> 10
|
||||
15 -> 11
|
||||
14 -> 11
|
||||
13 -> 11
|
||||
12 -> 11
|
||||
16 -> 11
|
||||
17 -> 11
|
||||
13 -> 12
|
||||
14 -> 13
|
||||
13 -> 16
|
||||
12 -> 16
|
||||
18 -> 17
|
||||
12 -> 20
|
||||
22 -> 21
|
||||
13 -> 23
|
||||
25 -> 24
|
||||
23 -> 24
|
||||
8 -> 25
|
||||
26 -> 25
|
||||
13 -> 26
|
||||
13 -> 27
|
||||
23 -> 27
|
||||
8 -> 27
|
||||
24 -> 28
|
||||
25 -> 28
|
||||
29 -> 28
|
||||
23 -> 28
|
||||
8 -> 29
|
||||
26 -> 29
|
||||
13 -> 30
|
||||
14 -> 30
|
||||
8 -> 30
|
||||
8 -> 31
|
||||
9 -> 32
|
||||
26 -> 32
|
||||
34 -> 33
|
||||
36 -> 33
|
||||
40 -> 33
|
||||
35 -> 34
|
||||
37 -> 36
|
||||
38 -> 36
|
||||
25 -> 37
|
||||
8 -> 37
|
||||
39 -> 38
|
||||
35 -> 39
|
||||
41 -> 40
|
||||
37 -> 40
|
||||
39 -> 41
|
||||
35 -> 41
|
||||
8 -> 42
|
||||
26 -> 42
|
||||
29 -> 43
|
||||
8 -> 44
|
||||
26 -> 44
|
||||
3 -> 46
|
||||
19 -> 46
|
||||
5 -> 46
|
||||
43 -> 46
|
||||
3 -> 47
|
||||
8 -> 47
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
|
||||
Scaling-Up
|
||||
==========
|
||||
|
||||
If you now feel confident and want to tackle runs with larger temporal, technological and
|
||||
spatial scope, clean-up the repository and after modifying the ``config.yaml`` file
|
||||
target the collection rule ``all`` again without providing the test
|
||||
configuration file.
|
||||
|
||||
.. code:: bash
|
||||
|
||||
snakemake -call purge
|
||||
snakemake -call all
|
||||
|
||||
.. note::
|
||||
|
||||
It is good practice to perform a dry-run using the option `-n`, before you
|
||||
commit to a run:
|
||||
|
||||
.. code:: bash
|
||||
|
||||
snakemake -call all -n
|
||||
@ -15,8 +15,28 @@ which e.g. defines one particular scenario. One can think of a wildcard as a par
|
||||
up in the input/output file names of the ``Snakefile`` and thereby determines which rules to run,
|
||||
what data to retrieve and what files to produce.
|
||||
|
||||
Detailed explanations of how wildcards work in ``snakemake`` can be found in the
|
||||
`relevant section of the documentation <https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#wildcards>`_.
|
||||
.. note::
|
||||
Detailed explanations of how wildcards work in ``snakemake`` can be found in the
|
||||
`relevant section of the documentation <https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#wildcards>`_.
|
||||
|
||||
.. _cutout_wc:
|
||||
|
||||
The ``{cutout}`` wildcard
|
||||
=========================
|
||||
|
||||
The ``{cutout}`` wildcard facilitates running the rule :mod:`build_cutout`
|
||||
for all cutout configurations specified under ``atlite: cutouts:``.
|
||||
These cutouts will be stored in a folder specified by ``{cutout}``.
|
||||
|
||||
.. _technology:
|
||||
|
||||
The ``{technology}`` wildcard
|
||||
=============================
|
||||
|
||||
The ``{technology}`` wildcard specifies for which renewable energy technology to produce availability time
|
||||
series and potentials using the rule :mod:`build_renewable_profiles`.
|
||||
It can take the values ``onwind``, ``offwind-ac``, ``offwind-dc``, and ``solar`` but **not** ``hydro``
|
||||
(since hydroelectric plant profiles are created by a different rule).
|
||||
|
||||
.. _simpl:
|
||||
|
||||
@ -78,10 +98,11 @@ The wildcard, in general, consists of two parts:
|
||||
The ``{opts}`` wildcard
|
||||
=======================
|
||||
|
||||
The ``{opts}`` wildcard triggers optional constraints, which are activated in either
|
||||
:mod:`prepare_network` or the :mod:`solve_network` step.
|
||||
It may hold multiple triggers separated by ``-``, i.e. ``Co2L-3H`` contains the
|
||||
``Co2L`` trigger and the ``3H`` switch. There are currently:
|
||||
The ``{opts}`` wildcard is used for electricity-only studies. It triggers
|
||||
optional constraints, which are activated in either :mod:`prepare_network` or
|
||||
the :mod:`solve_network` step. It may hold multiple triggers separated by ``-``,
|
||||
i.e. ``Co2L-3H`` contains the ``Co2L`` trigger and the ``3H`` switch. There are
|
||||
currently:
|
||||
|
||||
|
||||
.. csv-table::
|
||||
@ -89,71 +110,35 @@ It may hold multiple triggers separated by ``-``, i.e. ``Co2L-3H`` contains the
|
||||
:widths: 10,20,10,10
|
||||
:file: configtables/opts.csv
|
||||
|
||||
.. _country:
|
||||
.. _sector_opts:
|
||||
|
||||
The ``{country}`` wildcard
|
||||
==========================
|
||||
The ``{sector_opts}`` wildcard
|
||||
==============================
|
||||
|
||||
The rules :mod:`make_summary` and :mod:`plot_summary` (generating summaries of all or a subselection
|
||||
of the solved networks) as well as :mod:`plot_p_nom_map` (for plotting the cumulative
|
||||
generation potentials for renewable technologies) can be narrowed to
|
||||
individual countries using the ``{country}`` wildcard.
|
||||
.. warning::
|
||||
More comprehensive documentation for this wildcard will be added soon.
|
||||
|
||||
If ``country=all``, then the rule acts on the network for all countries
|
||||
defined in ``config.yaml``. If otherwise ``country=DE`` or another 2-letter
|
||||
country code, then the network is narrowed to buses of this country
|
||||
for the rule. For example to get a summary of the energy generated
|
||||
in Germany (in the solution for Europe) use:
|
||||
The ``{sector_opts}`` wildcard is only used for sector-coupling studies.
|
||||
|
||||
.. code:: bash
|
||||
.. csv-table::
|
||||
:header-rows: 1
|
||||
:widths: 10,20,10,10
|
||||
:file: configtables/sector-opts.csv
|
||||
|
||||
snakemake -call results/summaries/elec_s_all_lall_Co2L-3H_DE
|
||||
.. _scope:
|
||||
|
||||
.. _cutout_wc:
|
||||
The ``{scope}`` wildcard
|
||||
========================
|
||||
|
||||
The ``{cutout}`` wildcard
|
||||
=========================
|
||||
Takes values ``residential``, ``urban``, ``total``.
|
||||
|
||||
The ``{cutout}`` wildcard facilitates running the rule :mod:`build_cutout`
|
||||
for all cutout configurations specified under ``atlite: cutouts:``.
|
||||
These cutouts will be stored in a folder specified by ``{cutout}``.
|
||||
.. _planning_horizons:
|
||||
|
||||
.. _technology:
|
||||
The ``{planning_horizons}`` wildcard
|
||||
====================================
|
||||
|
||||
The ``{technology}`` wildcard
|
||||
=============================
|
||||
.. warning::
|
||||
More comprehensive documentation for this wildcard will be added soon.
|
||||
|
||||
The ``{technology}`` wildcard specifies for which renewable energy technology to produce availability time
|
||||
series and potentials using the rule :mod:`build_renewable_profiles`.
|
||||
It can take the values ``onwind``, ``offwind-ac``, ``offwind-dc``, and ``solar`` but **not** ``hydro``
|
||||
(since hydroelectric plant profiles are created by a different rule).
|
||||
|
||||
The wildcard can moreover be used to create technology specific figures and summaries.
|
||||
For instance ``{technology}`` can be used to plot regionally disaggregated potentials
|
||||
with the rule :mod:`plot_p_nom_max`.
|
||||
|
||||
.. _attr:
|
||||
|
||||
The ``{attr}`` wildcard
|
||||
=======================
|
||||
|
||||
The ``{attr}`` wildcard specifies which attribute is used for size
|
||||
representations of network components on a map plot produced by the rule
|
||||
:mod:`plot_network`. While it might be extended in the future, ``{attr}``
|
||||
currently only supports plotting of ``p_nom``.
|
||||
|
||||
.. _ext:
|
||||
|
||||
The ``{ext}`` wildcard
|
||||
======================
|
||||
|
||||
The ``{ext}`` wildcard specifies the file type of the figures the
|
||||
rule :mod:`plot_network`, :mod:`plot_summary`, and :mod:`plot_p_nom_max` produce.
|
||||
Typical examples are ``pdf`` and ``png``. The list of supported file
|
||||
formats depends on the used backend. To query the supported file types on your system, issue:
|
||||
|
||||
.. code:: python
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
plt.gcf().canvas.get_supported_filetypes()
|
||||
The ``{planning_horizons}`` wildcard is only used for sector-coupling studies.
|
||||
It takes years as values, e.g. 2020, 2030, 2040, 2050.
|
||||
|
||||
@ -19,7 +19,7 @@ dependencies:
|
||||
- openpyxl!=3.1.1
|
||||
- pycountry
|
||||
- seaborn
|
||||
- snakemake-minimal
|
||||
- snakemake-minimal>=7.7.0
|
||||
- memory_profiler
|
||||
- yaml
|
||||
- pytables
|
||||
@ -38,6 +38,12 @@ dependencies:
|
||||
- proj
|
||||
- fiona
|
||||
- country_converter
|
||||
- geopy
|
||||
- tqdm
|
||||
- pytz
|
||||
- tabula-py
|
||||
- pyxlsb
|
||||
- graphviz
|
||||
|
||||
# Keep in conda environment when calling ipython
|
||||
- ipython
|
||||
@ -47,13 +53,6 @@ dependencies:
|
||||
- descartes
|
||||
- rasterio!=1.2.10
|
||||
|
||||
# PyPSA-Eur-Sec Dependencies
|
||||
- geopy
|
||||
- tqdm
|
||||
- pytz
|
||||
- tabula-py
|
||||
- pyxlsb
|
||||
|
||||
- pip:
|
||||
- vresutils>=0.3.1
|
||||
- tsam>=1.1.0
|
||||
|
||||
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graphics/hotmaps.png
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Reference in New Issue
Block a user