Merge remote-tracking branch 'upstream/master' into add_methanol_techs
This commit is contained in:
Philipp Glaum
commit
3f4a7a1e1e
92
.github/workflows/codeql.yml
vendored
Normal file
92
.github/workflows/codeql.yml
vendored
Normal file
@ -0,0 +1,92 @@
|
||||
# For most projects, this workflow file will not need changing; you simply need
|
||||
# to commit it to your repository.
|
||||
#
|
||||
# You may wish to alter this file to override the set of languages analyzed,
|
||||
# or to provide custom queries or build logic.
|
||||
#
|
||||
# ******** NOTE ********
|
||||
# We have attempted to detect the languages in your repository. Please check
|
||||
# the `language` matrix defined below to confirm you have the correct set of
|
||||
# supported CodeQL languages.
|
||||
#
|
||||
name: "CodeQL"
|
||||
|
||||
on:
|
||||
push:
|
||||
branches: ["master"]
|
||||
pull_request:
|
||||
branches: ["master"]
|
||||
schedule:
|
||||
- cron: '23 18 * * 5'
|
||||
|
||||
jobs:
|
||||
analyze:
|
||||
name: Analyze (${{ matrix.language }})
|
||||
# Runner size impacts CodeQL analysis time. To learn more, please see:
|
||||
# - https://gh.io/recommended-hardware-resources-for-running-codeql
|
||||
# - https://gh.io/supported-runners-and-hardware-resources
|
||||
# - https://gh.io/using-larger-runners (GitHub.com only)
|
||||
# Consider using larger runners or machines with greater resources for possible analysis time improvements.
|
||||
runs-on: ${{ (matrix.language == 'swift' && 'macos-latest') || 'ubuntu-latest' }}
|
||||
permissions:
|
||||
# required for all workflows
|
||||
security-events: write
|
||||
|
||||
# required to fetch internal or private CodeQL packs
|
||||
packages: read
|
||||
|
||||
# only required for workflows in private repositories
|
||||
actions: read
|
||||
contents: read
|
||||
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
include:
|
||||
- language: python
|
||||
build-mode: none
|
||||
# CodeQL supports the following values keywords for 'language': 'c-cpp', 'csharp', 'go', 'java-kotlin', 'javascript-typescript', 'python', 'ruby', 'swift'
|
||||
# Use `c-cpp` to analyze code written in C, C++ or both
|
||||
# Use 'java-kotlin' to analyze code written in Java, Kotlin or both
|
||||
# Use 'javascript-typescript' to analyze code written in JavaScript, TypeScript or both
|
||||
# To learn more about changing the languages that are analyzed or customizing the build mode for your analysis,
|
||||
# see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/customizing-your-advanced-setup-for-code-scanning.
|
||||
# If you are analyzing a compiled language, you can modify the 'build-mode' for that language to customize how
|
||||
# your codebase is analyzed, see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/codeql-code-scanning-for-compiled-languages
|
||||
steps:
|
||||
- name: Checkout repository
|
||||
uses: actions/checkout@v4
|
||||
|
||||
# Initializes the CodeQL tools for scanning.
|
||||
- name: Initialize CodeQL
|
||||
uses: github/codeql-action/init@v3
|
||||
with:
|
||||
languages: ${{ matrix.language }}
|
||||
build-mode: ${{ matrix.build-mode }}
|
||||
# If you wish to specify custom queries, you can do so here or in a config file.
|
||||
# By default, queries listed here will override any specified in a config file.
|
||||
# Prefix the list here with "+" to use these queries and those in the config file.
|
||||
|
||||
# For more details on CodeQL's query packs, refer to: https://docs.github.com/en/code-security/code-scanning/automatically-scanning-your-code-for-vulnerabilities-and-errors/configuring-code-scanning#using-queries-in-ql-packs
|
||||
# queries: security-extended,security-and-quality
|
||||
|
||||
# If the analyze step fails for one of the languages you are analyzing with
|
||||
# "We were unable to automatically build your code", modify the matrix above
|
||||
# to set the build mode to "manual" for that language. Then modify this step
|
||||
# to build your code.
|
||||
# ℹ️ Command-line programs to run using the OS shell.
|
||||
# 📚 See https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepsrun
|
||||
- if: matrix.build-mode == 'manual'
|
||||
shell: bash
|
||||
run: |
|
||||
echo 'If you are using a "manual" build mode for one or more of the' \
|
||||
'languages you are analyzing, replace this with the commands to build' \
|
||||
'your code, for example:'
|
||||
echo ' make bootstrap'
|
||||
echo ' make release'
|
||||
exit 1
|
||||
|
||||
- name: Perform CodeQL Analysis
|
||||
uses: github/codeql-action/analyze@v3
|
||||
with:
|
||||
category: "/language:${{matrix.language}}"
|
||||
16
CITATION.cff
16
CITATION.cff
@ -6,7 +6,7 @@ cff-version: 1.1.0
|
||||
message: "If you use this package, please cite it in the following way."
|
||||
title: "PyPSA-Eur: An open sector-coupled optimisation model of the European energy system"
|
||||
repository: https://github.com/pypsa/pypsa-eur
|
||||
version: 0.11.0
|
||||
version: 0.12.0
|
||||
license: MIT
|
||||
authors:
|
||||
- family-names: Brown
|
||||
@ -36,3 +36,17 @@ authors:
|
||||
- family-names: Hörsch
|
||||
given-names: Jonas
|
||||
orcid: https://orcid.org/0000-0001-9438-767X
|
||||
- family-names: Schledorn
|
||||
given-names: Amos
|
||||
- family-names: Schauß
|
||||
given-names: Caspar
|
||||
- family-names: van Greevenbroek
|
||||
given-names: Koen
|
||||
- family-names: Millinger
|
||||
given-names: Markus
|
||||
- family-names: Glaum
|
||||
given-names: Philipp
|
||||
- family-names: Xiong
|
||||
given-names: Bobby
|
||||
- family-names: Seibold
|
||||
given-names: Toni
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
# SPDX-License-Identifier: CC0-1.0
|
||||
|
||||
# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#top-level-configuration
|
||||
version: 0.11.0
|
||||
version: 0.12.0
|
||||
tutorial: false
|
||||
|
||||
logging:
|
||||
@ -155,7 +155,7 @@ renewable:
|
||||
resource:
|
||||
method: wind
|
||||
turbine: Vestas_V112_3MW
|
||||
smooth: true
|
||||
smooth: false
|
||||
add_cutout_windspeed: true
|
||||
capacity_per_sqkm: 3
|
||||
# correction_factor: 0.93
|
||||
@ -175,7 +175,7 @@ renewable:
|
||||
resource:
|
||||
method: wind
|
||||
turbine: NREL_ReferenceTurbine_2020ATB_5.5MW
|
||||
smooth: true
|
||||
smooth: false
|
||||
add_cutout_windspeed: true
|
||||
capacity_per_sqkm: 2
|
||||
correction_factor: 0.8855
|
||||
@ -192,7 +192,7 @@ renewable:
|
||||
resource:
|
||||
method: wind
|
||||
turbine: NREL_ReferenceTurbine_2020ATB_5.5MW
|
||||
smooth: true
|
||||
smooth: false
|
||||
add_cutout_windspeed: true
|
||||
capacity_per_sqkm: 2
|
||||
correction_factor: 0.8855
|
||||
@ -209,7 +209,7 @@ renewable:
|
||||
resource:
|
||||
method: wind
|
||||
turbine: NREL_ReferenceTurbine_5MW_offshore
|
||||
smooth: true
|
||||
smooth: false
|
||||
add_cutout_windspeed: true
|
||||
# ScholzPhd Tab 4.3.1: 10MW/km^2
|
||||
capacity_per_sqkm: 2
|
||||
@ -451,21 +451,18 @@ sector:
|
||||
district_heating_loss: 0.15
|
||||
supply_temperature_approximation:
|
||||
max_forward_temperature:
|
||||
default: 90
|
||||
DK: 70
|
||||
SE: 70
|
||||
NO: 70
|
||||
FR: 110
|
||||
DK: 75
|
||||
DE: 109
|
||||
CZ: 130
|
||||
FI: 115
|
||||
PL: 130
|
||||
SE: 102
|
||||
IT: 90
|
||||
min_forward_temperature:
|
||||
default: 68
|
||||
DK: 54
|
||||
SE: 54
|
||||
NO: 54
|
||||
DE: 82
|
||||
return_temperature:
|
||||
default: 50
|
||||
DK: 40
|
||||
SE: 40
|
||||
NO: 40
|
||||
FI: 40
|
||||
DE: 58
|
||||
lower_threshold_ambient_temperature: 0
|
||||
upper_threshold_ambient_temperature: 10
|
||||
rolling_window_ambient_temperature: 72
|
||||
@ -590,7 +587,9 @@ sector:
|
||||
resistive_heaters: true
|
||||
oil_boilers: false
|
||||
biomass_boiler: true
|
||||
overdimension_individual_heating: 1.1 #to cover demand peaks bigger than data
|
||||
overdimension_heat_generators:
|
||||
decentral: 1.1 #to cover demand peaks bigger than data
|
||||
central: 1.0
|
||||
chp: true
|
||||
micro_chp: false
|
||||
solar_thermal: true
|
||||
@ -810,6 +809,7 @@ industry:
|
||||
MWh_MeOH_per_tMeOH: 5.528
|
||||
hotmaps_locate_missing: false
|
||||
reference_year: 2019
|
||||
oil_refining_emissions: 0.013
|
||||
|
||||
|
||||
# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#costs
|
||||
@ -1090,6 +1090,8 @@ plotting:
|
||||
gas pipeline new: '#a87c62'
|
||||
# oil
|
||||
oil: '#c9c9c9'
|
||||
oil primary: '#d2d2d2'
|
||||
oil refining: '#e6e6e6'
|
||||
imported oil: '#a3a3a3'
|
||||
oil boiler: '#adadad'
|
||||
residential rural oil boiler: '#a9a9a9'
|
||||
@ -1133,6 +1135,7 @@ plotting:
|
||||
services rural biomass boiler: '#c6cf98'
|
||||
services urban decentral biomass boiler: '#dde5b5'
|
||||
biomass to liquid: '#32CD32'
|
||||
unsustainable solid biomass: '#998622'
|
||||
unsustainable bioliquids: '#32CD32'
|
||||
electrobiofuels: 'red'
|
||||
BioSNG: '#123456'
|
||||
|
||||
@ -10,3 +10,9 @@ DC40plus,Dörpen/West,Klostermansfeld/Sachsen-Anhalt,2000.0,426,confirmed,2037,T
|
||||
DC41,Alfstedt/Niedersachsen,Hüffenhardt/Baden-Württemberg,2000.0,607,confirmed,2037,True,"{""url"":""https://data.netzausbau.de/2037-2023/NEP/NEP_2037_2045_Bestaetigung.pdf"", ""status"":""confirmed"", ""origin"":""NEP"",""version"":2024,""location0"":""Alfstedt/Niedersachsen"",""location1"":""Hüffenhardt/Baden-Württemberg""",9.0666915,53.5499782,9.0827453,49.2908862
|
||||
DC42,Sahms/Schleswig-Holstein,Böblingen/Baden-Württemberg,2000.0,737,confirmed,2037,True,"{""url"":""https://data.netzausbau.de/2037-2023/NEP/NEP_2037_2045_Bestaetigung.pdf"", ""status"":""confirmed"", ""origin"":""NEP"",""version"":2024,""location0"":""Sahms/Schleswig-Holstein"",""location1"":""Böblingen/Baden-Württemberg""",10.5331297,53.5252973,9.0113444,48.684969
|
||||
DC42plus,Sahms/Schleswig-Holstein,Trennfeld/Bayern,2000.0,546,confirmed,2037,True,"{""url"":""https://data.netzausbau.de/2037-2023/NEP/NEP_2037_2045_Bestaetigung.pdf"", ""status"":""confirmed"", ""origin"":""NEP"",""version"":2024,""location0"":""Sahms/Schleswig-Holstein"",""location1"":""Trennfeld/Bayern""",10.5331297,53.5252973,9.6151453,49.7950676
|
||||
DC1,Emden Ost,Osterath,2000,297,in_permitting,2027,True,"{url:https://www.netzentwicklungsplan.de/sites/default/files/2024-04/NEP_2037_2045_V2023_Anhang_2E_Aktualisierung_April_2024_%28komprimiert%29.pdf,TYNDP 2022:132,""location0"":""Emden Ost"",""location1"":""Osterath""",7.2492328,53.3655941,6.6207151,51.2690922
|
||||
DC2,Osterath,Philippsburg,2000,299,in_permitting,2026,False,"{url:https://www.netzentwicklungsplan.de/sites/default/files/2024-04/NEP_2037_2045_V2023_Anhang_2E_Aktualisierung_April_2024_%28komprimiert%29.pdf,TYNDP 2022: 254,""location0"":""Osterath"",""location1"":""Philippsburg""",6.6207151,51.2690922,7.5514555,48.9953996
|
||||
DC3,Brunsbüttel,Großgartach,2000,694,in_permitting,2028,True,"{url:https://www.netzentwicklungsplan.de/sites/default/files/2024-04/NEP_2037_2045_V2023_Anhang_2E_Aktualisierung_April_2024_%28komprimiert%29.pdf,TYNDP 2022: 235,""location0"":""Brunsbüttel"",""location1"":""Großgartach""",9.1395423,53.8972549,9.1258701,49.1425406
|
||||
DC4,Wilster ,Bergrheinfeld,2000,540,in_permitting,2028,True,"{url:https://www.netzentwicklungsplan.de/sites/default/files/2024-04/NEP_2037_2045_V2023_Anhang_2E_Aktualisierung_April_2024_%28komprimiert%29.pdf,TYNDP 2022: 235,""location0"":""Wilster "",""location1"":""Bergrheinfeld""",9.3741366,53.9233519,10.1810033,50.0082136
|
||||
DC5,Wolmirstedt,Isar/Bayern,2000,539,in_permitting,2027,True,"{url:https://www.netzentwicklungsplan.de/sites/default/files/2024-04/NEP_2037_2045_V2023_Anhang_2E_Aktualisierung_April_2024_%28komprimiert%29.pdf,TYNDP 2022: 130, name:SuedOstLink,""location0"":""Wolmirstedt"",""location1"":""Isar/Bayern""",11.6267388,52.2484924,11.5745421,47.6691308
|
||||
DC20,Klein Rogahn,Isar/Bayern,2000,759,in_permitting,2030,False,"{url:https://www.netzentwicklungsplan.de/sites/default/files/2024-04/NEP_2037_2045_V2023_Anhang_2E_Aktualisierung_April_2024_%28komprimiert%29.pdf, name:SuedOstLink+,""location0"":""Klein Rogahn"",""location1"":""Isar/Bayern""",11.3482229,53.6044461,11.5745421,47.6691308
|
||||
|
||||
|
@ -92,9 +92,9 @@ author = "Tom Brown (KIT, TUB, FIAS), Jonas Hoersch (KIT, FIAS), Fabian Hofmann
|
||||
# built documents.
|
||||
#
|
||||
# The short X.Y version.
|
||||
version = "0.11"
|
||||
version = "0.12"
|
||||
# The full version, including alpha/beta/rc tags.
|
||||
release = "0.11.0"
|
||||
release = "0.12.0"
|
||||
|
||||
# The language for content autogenerated by Sphinx. Refer to documentation
|
||||
# for a list of supported languages.
|
||||
|
||||
@ -4,7 +4,7 @@ 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,,,
|
||||
-- {name},--,"Convention is to name cutouts like ``<region>-<year>-<source>`` (e.g. ``europe-2013-sarah3-era5``).","Name of the cutout netcdf file. The user may specify multiple cutouts under configuration ``atlite: cutouts:``. Reference is used in configuration ``renewable: {technology}: cutout:``. The cutout ``base`` may be used to automatically calculate temporal and spatial bounds of the network."
|
||||
-- -- module,--,"Subset of {'era5','sarah'}","Source of the reanalysis weather dataset (e.g. `ERA5 <https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5>`_ or `SARAH-2 <https://wui.cmsaf.eu/safira/action/viewDoiDetails?acronym=SARAH_V002>`_)"
|
||||
-- -- module,--,"Subset of {'era5','sarah'}","Source of the reanalysis weather dataset (e.g. `ERA5 <https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5>`_ or `SARAH-3 <https://wui.cmsaf.eu/safira/action/viewDoiDetails?acronym=SARAH_V002>`_)"
|
||||
-- -- x,°,"Float interval within [-180, 180]","Range of longitudes to download weather data for. If not defined, it defaults to the spatial bounds of all bus shapes."
|
||||
-- -- y,°,"Float interval within [-90, 90]","Range of latitudes to download weather data for. If not defined, it defaults to the spatial bounds of all bus shapes."
|
||||
-- -- dx,°,"Larger than 0.25","Grid resolution for longitude"
|
||||
|
||||
|
@ -35,3 +35,4 @@ MWh_CH4_per_tMeOH,MWhCH4/tMeOH,float,"The energy amount of methane needed to pro
|
||||
MWh_MeOH_per_tMeOH,LHV,float,"The energy amount per ton of methanol. From `DECHEMA (2017) <https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf>`_, page 74."
|
||||
hotmaps_locate_missing,--,"{true,false}",Locate industrial sites without valid locations based on city and countries.
|
||||
reference_year,year,YYYY,The year used as the baseline for industrial energy demand and production. Data extracted from `JRC-IDEES 2015 <https://data.jrc.ec.europa.eu/dataset/jrc-10110-10001>`_
|
||||
oil_refining_emissions,tCO2/MWh,float,"The emissions from oil fuel processing (e.g. oil in petrochemical refinieries). The default value of 0.013 tCO2/MWh is based on DE statistics for 2019; the EU value is very similar."
|
||||
|
||||
|
@ -89,7 +89,9 @@ boilers,--,"{true, false}",Add option for transforming gas into heat using gas b
|
||||
resistive_heaters,--,"{true, false}",Add option for transforming electricity into heat using resistive heaters (independently from gas boilers)
|
||||
oil_boilers,--,"{true, false}",Add option for transforming oil into heat using boilers
|
||||
biomass_boiler,--,"{true, false}",Add option for transforming biomass into heat using boilers
|
||||
overdimension_individual_heating,--,float,Add option for overdimensioning individual heating systems by a certain factor. This allows them to cover heat demand peaks e.g. 10% higher than those in the data with a setting of 1.1.
|
||||
overdimension_heat_generators,,,Add option for overdimensioning heating systems by a certain factor. This allows them to cover heat demand peaks e.g. 10% higher than those in the data with a setting of 1.1.
|
||||
-- decentral,--,float,The factor for overdimensioning (increasing CAPEX) decentral heating systems
|
||||
-- central,--,float,The factor for overdimensioning (increasing CAPEX) central heating systems
|
||||
chp,--,"{true, false}",Add option for using Combined Heat and Power (CHP)
|
||||
micro_chp,--,"{true, false}",Add option for using Combined Heat and Power (CHP) for decentral areas.
|
||||
solar_thermal,--,"{true, false}",Add option for using solar thermal to generate heat.
|
||||
|
||||
|
@ -1,5 +1,5 @@
|
||||
,Unit,Values,Description
|
||||
cutout,--,"Should be a folder listed in the configuration ``atlite: cutouts:`` (e.g. 'europe-2013-sarah3-era5') or reference an existing folder in the directory ``cutouts``. Source module can be ERA5 or SARAH-2.","Specifies the directory where the relevant weather data ist stored that is specified at ``atlite/cutouts`` configuration. Both ``sarah`` and ``era5`` work."
|
||||
cutout,--,"Should be a folder listed in the configuration ``atlite: cutouts:`` (e.g. 'europe-2013-sarah3-era5') or reference an existing folder in the directory ``cutouts``. Source module can be ERA5 and/or SARAH-3.","Specifies the directory where the relevant weather data ist stored that is specified at ``atlite/cutouts`` configuration. Both ``sarah`` and ``era5`` work."
|
||||
resource,,,
|
||||
-- method,--,"Must be 'pv'","A superordinate technology type."
|
||||
-- panel,--,"One of {'Csi', 'CdTe', 'KANENA'} as defined in `atlite <https://github.com/PyPSA/atlite/tree/master/atlite/resources/solarpanel>`_ . Can be a string or a dictionary with years as keys which denote the year another turbine model becomes available.","Specifies the solar panel technology and its characteristic attributes."
|
||||
|
||||
|
Binary file not shown.
|
Before Width: | Height: | Size: 224 KiB After Width: | Height: | Size: 122 KiB |
@ -41,6 +41,17 @@ Rule ``build_cutout``
|
||||
.. automodule:: build_cutout
|
||||
|
||||
|
||||
Rule ``clean_osm_data``
|
||||
=============================
|
||||
|
||||
.. automodule:: clean_osm_data
|
||||
|
||||
|
||||
Rule ``build_osm_network``
|
||||
=============================
|
||||
|
||||
.. automodule:: build_osm_network
|
||||
|
||||
.. _base:
|
||||
|
||||
Rule ``base_network``
|
||||
@ -48,6 +59,12 @@ Rule ``base_network``
|
||||
|
||||
.. automodule:: base_network
|
||||
|
||||
|
||||
Rule ``build_transmission_projects``
|
||||
====================================
|
||||
|
||||
.. automodule:: build_transmission_projects
|
||||
|
||||
.. _shapes:
|
||||
|
||||
Rule ``build_shapes``
|
||||
@ -55,6 +72,10 @@ Rule ``build_shapes``
|
||||
|
||||
.. automodule:: build_shapes
|
||||
|
||||
Rule ``build_gdp_pop_non_nuts3``
|
||||
=============================
|
||||
|
||||
.. automodule:: build_gdp_pop_non_nuts3
|
||||
|
||||
.. _powerplants:
|
||||
|
||||
|
||||
@ -8,30 +8,41 @@
|
||||
Release Notes
|
||||
##########################################
|
||||
|
||||
Upcoming Release
|
||||
================
|
||||
.. Upcoming Release
|
||||
|
||||
* Add technology options for methanol, like electricity production from methanol, biomass to methanol, methanol to kerosene, ...
|
||||
|
||||
* Bugfix for passing function arguments in rule :mod:`solve_operations_network`.
|
||||
* Updated district heating supply temperatures based on `Euroheat's DHC Market Outlook 2024<https://api.euroheat.org/uploads/Market_Outlook_2024_beeecd62d4.pdf>`__ and `AGFW-Hauptbericht 2022 <https://www.agfw.de/securedl/sdl-eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpYXQiOjE3MjU2MjI2MTUsImV4cCI6MTcyNTcxMjYxNSwidXNlciI6MCwiZ3JvdXBzIjpbMCwtMV0sImZpbGUiOiJmaWxlYWRtaW4vdXNlcl91cGxvYWQvWmFobGVuX3VuZF9TdGF0aXN0aWtlbi9IYXVwdGJlcmljaHRfMjAyMi9BR0ZXX0hhdXB0YmVyaWNodF8yMDIyLnBkZiIsInBhZ2UiOjQzNn0.Bhma3PKg9uJnC57Ixi2p9STW5-II9VXPTDXS544M208/AGFW_Hauptbericht_2022.pdf>`__. `min_forward_temperature` and `return_temperature` (not given by Euroheat) are extrapolated based on German values.
|
||||
* Made the overdimensioning factor for heating systems specific for central/decentral heating, defaults to no overdimensionining for central heating and no changes to decentral heating compared to previous version.
|
||||
|
||||
* Represent Kosovo (XK) as separate country.
|
||||
* bugfix: The carrier of stores was silently overwritten by their bus_carrier as a side effect when building the co2 constraints
|
||||
|
||||
* Added data on the locations and capacities of ammonia plants in Europe.
|
||||
This data is used as a spatial distribution key for the ammonia demand.
|
||||
The data manually collected with sources noted in ``data/ammonia_plants.csv``.
|
||||
* bugfix: The oil generator was incorrectly dropped when the config `oil_refining_emissions` was greater than zero. This was the default behaviour in 0.12.0.
|
||||
|
||||
* Added data on the locations and capacities of cement plants in Europe that are
|
||||
not included in the Hotmaps industrial database. The data sourced from the
|
||||
`USGS 2019 Minerals Yearbooks
|
||||
<https://www.usgs.gov/centers/national-minerals-information-center/international-minerals-statistics-and-information>`__
|
||||
of specific countries is used as a spatial distribution key for the cement
|
||||
demand. The data is stored in ``data/cement-plants-noneu.csv``.
|
||||
PyPSA-Eur 0.12.0 (30th August 2024)
|
||||
===================================
|
||||
|
||||
* Added data on the locations and capacities of refineries in Europe that are
|
||||
not included in the Hotmaps industrial database. The data is mostly sourced
|
||||
from the `Wikipedia list of oil refineries
|
||||
<https://en.wikipedia.org/wiki/List_of_oil_refineries>`__. The data is stored
|
||||
in ``data/refineries-noneu.csv``.
|
||||
**Data Updates and Extensions**
|
||||
|
||||
* Switch to OpenStreetMap (OSM) data for modelling the high-voltage transmission
|
||||
grid. The new OSM-based grid is is now the default. The previous ENTSO-E grid
|
||||
data is now deprecated. It can still be used by setting ``electricity:
|
||||
base_network: entsoegridkit``. The new default setting "osm-prebuilt"
|
||||
downloads the latest prebuilt snapshots from Zenodo. The setting "osm-raw"
|
||||
retrieves and cleans the raw OSM data and subsequently builds the network.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1079)
|
||||
|
||||
* Update energy balances from JRC-IDEES-2015 to `JRC-IDEES-2021
|
||||
<https://publications.jrc.ec.europa.eu/repository/handle/JRC137809>`__. The
|
||||
reference year was changed from 2015 to 2019.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1167)
|
||||
|
||||
* Updated pre-built `weather data cutouts
|
||||
<https://zenodo.org/records/12791128>`__. These are now merged cutouts with
|
||||
solar irradiation from the new SARAH-3 dataset while taking all other
|
||||
variables from ERA5. Cutouts are now available for multiple years (2010, 2013,
|
||||
2019, and 2023). The overall download size was cut in half.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1176)
|
||||
|
||||
* Included data from the `Global Steel Plant Tracker
|
||||
<https://globalenergymonitor.org/projects/global-steel-plant-tracker/>`__
|
||||
@ -40,103 +51,237 @@ Upcoming Release
|
||||
and capacities of steel plants in Europe. This data is used as a spatial
|
||||
distribution key for the steel production, which is now separated by process
|
||||
type (EAF, DRI + EAF, integrated).
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1241)
|
||||
|
||||
* Added data on the locations and capacities of ammonia plants in Europe. This
|
||||
data is used as a spatial distribution key for the ammonia demand. The data
|
||||
manually collected with sources noted in ``data/ammonia_plants.csv``.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1241)
|
||||
|
||||
* Added data on the locations and capacities of cement plants in Europe that are
|
||||
not included in the Hotmaps industrial database. The data sourced from the
|
||||
`USGS 2019 Minerals Yearbooks
|
||||
<https://www.usgs.gov/centers/national-minerals-information-center/international-minerals-statistics-and-information>`__
|
||||
of specific countries is used as a spatial distribution key for the cement
|
||||
demand. The data is stored in ``data/cement-plants-noneu.csv``.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1241)
|
||||
|
||||
* Added data on the locations and capacities of refineries in Europe that are
|
||||
not included in the Hotmaps industrial database. The data is mostly sourced
|
||||
from the `Wikipedia list of oil refineries
|
||||
<https://en.wikipedia.org/wiki/List_of_oil_refineries>`__. The data is stored
|
||||
in ``data/refineries-noneu.csv``.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1241)
|
||||
|
||||
* Retrieve share of urban population from `World Bank API
|
||||
<https://data.worldbank.org/indicator/SP.URB.TOTL.IN.ZS>`__. The data
|
||||
originates from the United Nations Population Division. Previously, a file
|
||||
``data/urban_percent.csv`` with an undocumented source was used.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1248)
|
||||
|
||||
* Updated Global Energy Monitor's Europe Gas Tracker to May 2024 version.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1235)
|
||||
|
||||
* Updated country-specific Energy Availability Factors (EAFs) for nuclear power
|
||||
plants based on `IAEA 2021-2023 reported country averages
|
||||
<https://pris.iaea.org/PRIS/WorldStatistics/ThreeYrsEnergyAvailabilityFactor.aspx>`__.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1236)
|
||||
|
||||
* Update GEM Europe Gas Tracker to May 2024 version.
|
||||
* Updated technology-data to v0.9.2, with added methanol and biomass
|
||||
assumptions.
|
||||
|
||||
* Add investment period dependent CO2 sequestration potentials
|
||||
* Updated EEZ shapes to v12. This data is now automatically retrieved and was
|
||||
removed from the data bundle. (https://github.com/PyPSA/pypsa-eur/pull/1188,
|
||||
https://github.com/PyPSA/pypsa-eur/pull/1210)
|
||||
|
||||
* Add option to produce hydrogen from solid biomass (flag ``solid biomass to hydrogen``), combined with carbon capture
|
||||
* The country shapes from Naturalearth are now automatically retrieved and are
|
||||
removed from the data bundle. (https://github.com/PyPSA/pypsa-eur/pull/1190)
|
||||
|
||||
* Fixed PDF encoding in ``build_biomass_transport_costs`` with update of tabula-py and jpype1
|
||||
**New Features**
|
||||
|
||||
* More modular and flexible handling of transmission projects. One can now add new transmission projects in a subfolder of `data/transmission projects` similar to the files in the template folder. After adding the new files and updating the config section `transmission_projects:`, transmission projects will be included if they are not duplicates of existing lines or other projects.
|
||||
* Improved biomass representation:
|
||||
|
||||
* Add option to apply a gaussian kernel density smoothing to wind turbine power curves.
|
||||
* Added unsustainable biomass potentials for solid, gaseous, and liquid biomass
|
||||
based on current consumption levels from Eurostat energy balances. The
|
||||
potentials can be phased-out and/or substituted by the phase-in of sustainable
|
||||
biomass types using the config parameters ``biomass:
|
||||
share_unsustainable_use_retained`` and ``biomass:
|
||||
share_sustainable_potential_available``.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1139)
|
||||
|
||||
* Update JRC-IDEES-2015 to `JRC-IDEES-2021 <https://publications.jrc.ec.europa.eu/repository/handle/JRC137809>`__. The reference year is changed from 2015 to 2019.
|
||||
* Added energy penalty for BECC applications.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1130)
|
||||
|
||||
* Made central heating supply temperatures dynamic based on an adaptation of a reference curve from Pieper et al. (2019) (https://www.sciencedirect.com/science/article/pii/S0360544219305857?via%3Dihub).
|
||||
* Added option to enable the import of solid biomass.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1194)
|
||||
|
||||
* Added option to use country-specific district heating forward and return temperatures. Defaults to lower temperatures in Scandinavia.
|
||||
* Added option to produce electrobiofuels from solid biomass and hydrogen. This
|
||||
process combined BtL and Fischer-Tropsch to efficiently use the available
|
||||
biogenic carbon. (https://github.com/PyPSA/pypsa-eur/pull/1193)
|
||||
|
||||
* Added unsustainable biomass potentials for solid, gaseous, and liquid biomass. The potentials can be phased-out and/or
|
||||
substituted by the phase-in of sustainable biomass types using the config parameters
|
||||
``biomass: share_unsustainable_use_retained`` and ``biomass: share_sustainable_potential_available``.
|
||||
* Added option to split municipal solid waste from solid biomass.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1195,
|
||||
https://github.com/PyPSA/pypsa-eur/pull/1134)
|
||||
|
||||
* The rule ``prepare_links_p_nom`` was removed since it was outdated and not used.
|
||||
* Added option to produce hydrogen from solid biomass with or without carbon
|
||||
capture. (https://github.com/PyPSA/pypsa-eur/pull/1213)
|
||||
|
||||
* Changed heat pump COP approximation for central heating to be based on `Jensen et al. (2018) <https://backend.orbit.dtu.dk/ws/portalfiles/portal/151965635/MAIN_Final.pdf>`__ and a default forward temperature of 90C. This is more realistic for district heating than the previously used approximation method.
|
||||
* Improved district heating representation:
|
||||
|
||||
* split solid biomass potentials into solid biomass and municipal solid waste. Add option to use municipal solid waste. This option is only activated in combination with the flag ``waste_to_energy``
|
||||
* Added option to use country-specific district heating forward and return
|
||||
temperatures. Defaults to lower temperatures in Scandinavia.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1180)
|
||||
|
||||
* Add option to import solid biomass
|
||||
* Made central heating supply temperatures dynamic based on an adaptation of a
|
||||
reference curve from Pieper et al. (2019)
|
||||
(https://www.sciencedirect.com/science/article/pii/S0360544219305857?via%3Dihub).
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1206/)
|
||||
|
||||
* Add option to produce electrobiofuels (flag ``electrobiofuels``) from solid biomass and hydrogen, as a combination of BtL and Fischer-Tropsch to make more use of the biogenic carbon
|
||||
* Changed heat pump COP approximation for central heating to be based on
|
||||
`Jensen et al. (2018)
|
||||
<https://backend.orbit.dtu.dk/ws/portalfiles/portal/151965635/MAIN_Final.pdf>`__
|
||||
and a default forward temperature of 90C. This is more realistic for
|
||||
district heating than the previously used approximation method.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1176)
|
||||
|
||||
* Add flag ``sector: fossil_fuels`` in config to remove the option of importing fossil fuels
|
||||
* Added option for various power-to-X processes to specify their share of waste
|
||||
heat that can be used in district heating. The default was changed from 100%
|
||||
to 25%. (https://github.com/PyPSA/pypsa-eur/pull/1141)
|
||||
|
||||
* Renamed the carrier of batteries in BEVs from `battery storage` to `EV battery` and the corresponding bus carrier from `Li ion` to `EV battery`. This is to avoid confusion with stationary battery storage.
|
||||
|
||||
* Changed default assumptions about waste heat usage from PtX and fuel cells in district heating.
|
||||
The default value for the link efficiency scaling factor was changed from 100% to 25%.
|
||||
It can be set to other values in the configuration ``sector: use_TECHNOLOGY_waste_heat``.
|
||||
|
||||
* In simplifying polygons in :mod:`build_shapes` default to no tolerance.
|
||||
|
||||
* Set non-zero capital_cost for methanol stores to avoid unrealistic storage sizes
|
||||
|
||||
* Set p_nom = p_nom_min for generators with baseyear == grouping_year in add_existing_baseyear. This has no effect on the optimization but helps n.statistics to correctly report already installed capacities.
|
||||
|
||||
* Reverted outdated hotfix for doubled renewable capacity in myopic optimization.
|
||||
* Added option to specify emissions fuel processing (e.g. oil in petrochemical
|
||||
refinieries) with setting ``industry: oil_refining_emissions:``.
|
||||
|
||||
* Added Enhanced Geothermal Systems for generation of electricity and district heat.
|
||||
Cost and available capacity assumptions based on `Aghahosseini et al. (2020)
|
||||
<https://www.sciencedirect.com/science/article/pii/S0306261920312551>`__.
|
||||
See configuration ``sector: enhanced_geothermal`` for details; by default switched off.
|
||||
|
||||
* Partially revert https://github.com/PyPSA/pypsa-eur/pull/967 to return to old grouping year logic (which was mostly correct)
|
||||
* Represent Kosovo (XK) as separate country.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1249)
|
||||
|
||||
* Bugfix: Correctly read in threshold capacity below which to remove components from previous planning horizons in :mod:`add_brownfield`.
|
||||
* Add option to specify carbon sequestration potentials per investment period.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1228)
|
||||
|
||||
* For countries not contained in the NUTS3-specific datasets (i.e. MD and UA), the mapping of GDP per capita and population per bus region used to spatially distribute electricity demand is now endogenised in a new rule :mod:`build_gdp_ppp_non_nuts3`. https://github.com/PyPSA/pypsa-eur/pull/1146
|
||||
* Add option to completely eliminate the use of fossil fuels.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1187)
|
||||
|
||||
* The databundle has been updated to release v0.3.0, which includes raw GDP and population data for countries outside the NUTS system (UA, MD). https://github.com/PyPSA/pypsa-eur/pull/1146
|
||||
* Added more modular and flexible handling of planned transmission reinforcement
|
||||
projects (e.g. TYNDP). See configuration settings ``transmission_projects:``.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1085)
|
||||
|
||||
* Updated filtering in :mod:`determine_availability_matrix_MD_UA.py` to improve speed. https://github.com/PyPSA/pypsa-eur/pull/1146
|
||||
|
||||
* Bugfix: Impose minimum value of zero for district heating progress between current and future market share in :mod:`build_district_heat_share`.
|
||||
|
||||
* The ``{scope}`` wildcard was removed, since its outputs were not used.
|
||||
|
||||
* Enable parallelism in :mod:`determine_availability_matrix_MD_UA.py` and remove plots. This requires the use of temporary files.
|
||||
|
||||
* Added new major feature to create the base_network from OpenStreetMap (OSM) data (PR https://github.com/PyPSA/pypsa-eur/pull/1079). Note that a heuristics based cleaning process is used for lines and links where electrical parameters are incomplete, missing, or ambiguous. Through ``electricity["base_network"]``, the base network can be set to "entsoegridkit" (now deprecated), "osm-prebuilt" (default, downloads the latest prebuilt snapshot based on OSM data from Zenodo), or "osm-raw" which retrieves (once) and cleans the raw OSM data and subsequently builds the network. Note that this process may take a few minutes.
|
||||
|
||||
* Updated pre-built `weather data cutouts
|
||||
<https://zenodo.org/records/12791128>`__. These are now merged cutouts with
|
||||
solar irradiation from the new SARAH-3 dataset while taking all other
|
||||
variables from ERA5. Cutouts are now available for multiple years (2010, 2013,
|
||||
2019, and 2023).
|
||||
* Added option to smooth wind turbine power curves with a Gaussian kernel density.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1209).
|
||||
|
||||
* Added option ``solving: curtailment_mode``` which fixes the dispatch profiles
|
||||
of generators with time-varying p_max_pu by setting ``p_min_pu = p_max_pu``
|
||||
and adds an auxiliary curtailment generator with negative sign (to absorb
|
||||
excess power) at every AC bus. This can speed up the solving process as the
|
||||
curtailment decision is aggregated into a single generator per region.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1177)
|
||||
|
||||
* Added capital costs to all liquid carbonaceous fuel stores.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1234)
|
||||
|
||||
**Breaking Changes**
|
||||
|
||||
* Due to memory issues, the feature ``n.shapes`` is temporarily disabled.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1238)
|
||||
|
||||
* Renamed the carrier of batteries in BEVs from `battery storage` to `EV
|
||||
battery` and the corresponding bus carrier from `Li ion` to `EV battery`. This
|
||||
is to avoid confusion with stationary battery storage.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1116)
|
||||
|
||||
**Changes**
|
||||
|
||||
* Powerplants can now be assigned to all buses, not just substations.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1239)
|
||||
|
||||
* Avoid adding existing gas pipelines repeatedly for different planning
|
||||
horizons.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1162https://github.com/PyPSA/pypsa-eur/pull/1162)
|
||||
|
||||
* Move custom busmaps to
|
||||
``data/busmaps/elec_s{simpl}_{clusters}_{base_network}.csv``. This allows for
|
||||
different busmaps depending on the base network.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1231)
|
||||
|
||||
* For countries not contained in the NUTS3-specific datasets (i.e. MD and UA),
|
||||
the mapping of GDP per capita and population per bus region used to spatially
|
||||
distribute electricity demand is now endogenised in a new rule
|
||||
:mod:`build_gdp_ppp_non_nuts3`. The databundle has been updated accordingly.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1146)
|
||||
|
||||
* Enable parallelism in :mod:`determine_availability_matrix_MD_UA.py` and remove
|
||||
plots. This requires the use of temporary files.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1170)
|
||||
|
||||
* In :mod:`base_network`, replace own voronoi polygon calculation function with
|
||||
Geopandas `gdf.voronoi_polygons` method.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1172)
|
||||
|
||||
* In simplifying polygons in :mod:`build_shapes` default to no tolerance.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1137)
|
||||
|
||||
* Updated filtering in :mod:`determine_availability_matrix_MD_UA.py` to improve
|
||||
speed. (https://github.com/PyPSA/pypsa-eur/pull/1146)
|
||||
|
||||
* Removed unused data files and rules.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1246,
|
||||
https://github.com/PyPSA/pypsa-eur/pull/1203)
|
||||
|
||||
* The ``{scope}`` wildcard was removed, since its outputs were not used.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1171)
|
||||
|
||||
* Unify how the oil bus is added.
|
||||
|
||||
* Set ``p_nom = p_nom_min`` for generators with ``baseyear == grouping_year`` in
|
||||
:mod:`add_existing_baseyear`. This has no effect on the optimization but helps
|
||||
to correctly report already installed capacities using ``n.statistics()``.
|
||||
|
||||
* Cutouts are no longer marked as ``protected()``.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1220)
|
||||
|
||||
**Bugfixes and Compatibility**
|
||||
|
||||
* Bugfix in :mod:`simplify_network` for spatially resolving Corsica.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1215)
|
||||
|
||||
* Bugfix for running without spatial resolution.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1183)
|
||||
|
||||
* Bugfix: Impose minimum value of zero for district heating progress between
|
||||
current and future market share in :mod:`build_district_heat_share`.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1168)
|
||||
|
||||
* Bugfix: Correctly read in threshold capacity below which to remove components
|
||||
from previous planning horizons in :mod:`add_brownfield`.
|
||||
|
||||
* Bugfix for passing function arguments in rule :mod:`solve_operations_network`.
|
||||
|
||||
* Bugfix avoiding infinity values in the intermediate industry sector ratios.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1227)
|
||||
|
||||
* Bugfix: Add floating wind to cost update function in
|
||||
:mod:`prepare_sector_network`. (https://github.com/PyPSA/pypsa-eur/pull/1106)
|
||||
|
||||
* Fixed PDF encoding in ``build_biomass_transport_costs``.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1219)
|
||||
|
||||
* Dropped ``pycountry`` dependency in favour of ``country_converter``.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1188)
|
||||
|
||||
* Use temporary mirror for broken link to Eurostat energy balances (April 2023).
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1147)
|
||||
|
||||
* Compatibility with geopandas 1.0+.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1136)
|
||||
|
||||
* Compatibility with snakemake 8.14+.
|
||||
(https://github.com/PyPSA/pypsa-eur/pull/1112)
|
||||
|
||||
* Address various deprecations.
|
||||
|
||||
* Move custom busmaps to ```data/busmaps/elec_s{simpl}_{clusters}_{base_network}.csv``` (if enabled). This allows for different busmaps depending on the base network and scenario.
|
||||
|
||||
PyPSA-Eur 0.11.0 (25th May 2024)
|
||||
=====================================
|
||||
|
||||
@ -19,13 +19,43 @@ Rule ``retrieve_databundle``
|
||||
|
||||
.. automodule:: retrieve_databundle
|
||||
|
||||
Rule ``retrieve_eurostat_data``
|
||||
===============================
|
||||
|
||||
.. automodule:: retrieve_eurostat_data
|
||||
|
||||
|
||||
Rule ``retrieve_jrc_idees``
|
||||
===============================
|
||||
|
||||
.. automodule:: retrieve_jrc_idees
|
||||
|
||||
|
||||
|
||||
Rule ``retrieve_eurostat_household_data``
|
||||
=========================================
|
||||
|
||||
.. automodule:: retrieve_eurostat_household_data
|
||||
|
||||
|
||||
Rule ``retrieve_gas_infrastructure_data``
|
||||
=========================================
|
||||
|
||||
.. automodule:: retrieve_gas_infrastructure_data
|
||||
|
||||
|
||||
Rule ``retrieve_osm_data``
|
||||
=========================================
|
||||
|
||||
.. automodule:: retrieve_osm_data
|
||||
|
||||
Rule ``retrieve_cutout``
|
||||
============================
|
||||
|
||||
.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.6382570.svg
|
||||
:target: https://doi.org/10.5281/zenodo.6382570
|
||||
|
||||
Cutouts are spatio-temporal subsets of the European weather data from the `ECMWF ERA5 <https://software.ecmwf.int/wiki/display/CKB/ERA5+data+documentation>`__ reanalysis dataset and the `CMSAF SARAH-2 <https://wui.cmsaf.eu/safira/action/viewDoiDetails?acronym=SARAH_V002>`__ solar surface radiation dataset for the year 2013.
|
||||
Cutouts are spatio-temporal subsets of the European weather data from the `ECMWF ERA5 <https://software.ecmwf.int/wiki/display/CKB/ERA5+data+documentation>`__ reanalysis dataset and the `CMSAF SARAH-3 <https://wui.cmsaf.eu/safira/action/viewDoiDetails?acronym=SARAH_V002>`__ solar surface radiation dataset for the year 2013, 2019 or 2023.
|
||||
They have been prepared by and are for use with the `atlite <https://github.com/PyPSA/atlite>`__ tool. You can either generate them yourself using the ``build_cutouts`` rule or retrieve them directly from `zenodo <https://doi.org/10.5281/zenodo.6382570>`__ through the rule ``retrieve_cutout``.
|
||||
The :ref:`tutorial` uses a smaller cutout than required for the full model (30 MB), which is also automatically downloaded.
|
||||
|
||||
@ -47,7 +77,7 @@ The :ref:`tutorial` uses a smaller cutout than required for the full model (30 M
|
||||
|
||||
**Outputs**
|
||||
|
||||
- ``cutouts/{cutout}``: weather data from either the `ERA5 <https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5>`__ reanalysis weather dataset or `SARAH-2 <https://wui.cmsaf.eu/safira/action/viewProduktSearch>`__ satellite-based historic weather data.
|
||||
- ``cutouts/{cutout}``: weather data from either the `ERA5 <https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5>`__ reanalysis weather dataset and/or `SARAH-3 <https://wui.cmsaf.eu/safira/action/viewProduktSearch>`__ satellite-based historic weather data.
|
||||
|
||||
.. seealso::
|
||||
For details see :mod:`build_cutout` and read the `atlite documentation <https://atlite.readthedocs.io>`__.
|
||||
|
||||
@ -43,6 +43,11 @@ Rule ``build_biomass_potentials``
|
||||
|
||||
.. automodule:: build_biomass_potentials
|
||||
|
||||
Rule ``build_egs_potentials``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_egs_potentials
|
||||
|
||||
Rule ``build_biomass_transport_costs``
|
||||
==============================================================================
|
||||
|
||||
@ -58,6 +63,11 @@ Rule ``build_cop_profiles``
|
||||
|
||||
.. automodule:: build_cop_profiles
|
||||
|
||||
Rule ``build_central_heating_temperature_profiles``
|
||||
==============================================================================
|
||||
|
||||
.. automodule:: build_central_heating_temperature_profiles
|
||||
|
||||
Rule ``build_energy_totals``
|
||||
==============================================================================
|
||||
|
||||
|
||||
148
doc/tutorial.rst
148
doc/tutorial.rst
@ -80,7 +80,7 @@ adapt the required range of coordinates to the selection of countries.
|
||||
|
||||
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.
|
||||
want to use the ERA-5 dataset for solar and not the default SARAH-3 dataset.
|
||||
|
||||
.. literalinclude:: ../config/test/config.electricity.yaml
|
||||
:language: yaml
|
||||
@ -132,88 +132,98 @@ This triggers a workflow of multiple preceding jobs that depend on each rule's i
|
||||
graph[bgcolor=white, margin=0];
|
||||
node[shape=box, style=rounded, fontname=sans, fontsize=10, penwidth=2];
|
||||
edge[penwidth=2, color=grey];
|
||||
0[label = "solve_network", color = "0.21 0.6 0.85", style="rounded"];
|
||||
1[label = "prepare_network\nll: copt\nopts: ", color = "0.51 0.6 0.85", style="rounded"];
|
||||
2[label = "add_extra_components", color = "0.43 0.6 0.85", style="rounded"];
|
||||
3[label = "cluster_network\nclusters: 6", color = "0.17 0.6 0.85", style="rounded"];
|
||||
4[label = "simplify_network\nsimpl: ", color = "0.49 0.6 0.85", style="rounded"];
|
||||
5[label = "add_electricity", color = "0.26 0.6 0.85", style="rounded"];
|
||||
6[label = "build_renewable_profiles\ntechnology: solar", color = "0.02 0.6 0.85", style="rounded"];
|
||||
7[label = "base_network", color = "0.35 0.6 0.85", style="rounded"];
|
||||
8[label = "build_shapes", color = "0.62 0.6 0.85", style="rounded"];
|
||||
9[label = "retrieve_databundle", color = "0.24 0.6 0.85", style="rounded"];
|
||||
10[label = "retrieve_cutout\ncutout: be-03-2013-era5", color = "0.36 0.6 0.85", style="rounded"];
|
||||
11[label = "build_renewable_profiles\ntechnology: solar-hsat", color = "0.02 0.6 0.85", style="rounded"];
|
||||
12[label = "build_renewable_profiles\ntechnology: onwind", color = "0.02 0.6 0.85", style="rounded"];
|
||||
13[label = "build_renewable_profiles\ntechnology: offwind-ac", color = "0.02 0.6 0.85", style="rounded"];
|
||||
14[label = "build_ship_raster", color = "0.08 0.6 0.85", style="rounded"];
|
||||
15[label = "retrieve_ship_raster", color = "0.28 0.6 0.85", style="rounded"];
|
||||
16[label = "build_renewable_profiles\ntechnology: offwind-dc", color = "0.02 0.6 0.85", style="rounded"];
|
||||
17[label = "build_renewable_profiles\ntechnology: offwind-float", color = "0.02 0.6 0.85", style="rounded"];
|
||||
18[label = "build_line_rating", color = "0.07 0.6 0.85", style="rounded"];
|
||||
19[label = "retrieve_cost_data\nyear: 2030", color = "0.47 0.6 0.85", style="rounded"];
|
||||
20[label = "build_powerplants", color = "0.11 0.6 0.85", style="rounded"];
|
||||
21[label = "build_electricity_demand", color = "0.05 0.6 0.85", style="rounded"];
|
||||
22[label = "retrieve_electricity_demand", color = "0.58 0.6 0.85", style="rounded"];
|
||||
23[label = "retrieve_synthetic_electricity_demand", color = "0.11 0.6 0.85", style="rounded"];
|
||||
0[label = "solve_network", color = "0.16 0.6 0.85", style="rounded"];
|
||||
1[label = "prepare_network\nll: copt\nopts: ", color = "0.40 0.6 0.85", style="rounded"];
|
||||
2[label = "add_extra_components", color = "0.03 0.6 0.85", style="rounded"];
|
||||
3[label = "cluster_network\nclusters: 6", color = "0.26 0.6 0.85", style="rounded"];
|
||||
4[label = "simplify_network\nsimpl: ", color = "0.17 0.6 0.85", style="rounded"];
|
||||
5[label = "add_electricity", color = "0.39 0.6 0.85", style="rounded"];
|
||||
6[label = "build_renewable_profiles\ntechnology: solar", color = "0.13 0.6 0.85", style="rounded"];
|
||||
7[label = "base_network", color = "0.01 0.6 0.85", style="rounded"];
|
||||
8[label = "retrieve_osm_prebuilt", color = "0.27 0.6 0.85", style="rounded"];
|
||||
9[label = "build_shapes", color = "0.18 0.6 0.85", style="rounded"];
|
||||
10[label = "retrieve_naturalearth_countries", color = "0.41 0.6 0.85", style="rounded"];
|
||||
11[label = "retrieve_eez", color = "0.14 0.6 0.85", style="rounded"];
|
||||
12[label = "retrieve_databundle", color = "0.38 0.6 0.85", style="rounded"];
|
||||
13[label = "retrieve_cutout\ncutout: be-03-2013-era5", color = "0.51 0.6 0.85", style="rounded"];
|
||||
14[label = "build_renewable_profiles\ntechnology: solar-hsat", color = "0.13 0.6 0.85", style="rounded"];
|
||||
15[label = "build_renewable_profiles\ntechnology: onwind", color = "0.13 0.6 0.85", style="rounded"];
|
||||
16[label = "build_renewable_profiles\ntechnology: offwind-ac", color = "0.13 0.6 0.85", style="rounded"];
|
||||
17[label = "build_ship_raster", color = "0.16 0.6 0.85", style="rounded"];
|
||||
18[label = "retrieve_ship_raster", color = "0.53 0.6 0.85", style="rounded"];
|
||||
19[label = "build_renewable_profiles\ntechnology: offwind-dc", color = "0.13 0.6 0.85", style="rounded"];
|
||||
20[label = "build_renewable_profiles\ntechnology: offwind-float", color = "0.13 0.6 0.85", style="rounded"];
|
||||
21[label = "build_line_rating", color = "0.46 0.6 0.85", style="rounded"];
|
||||
22[label = "build_transmission_projects", color = "0.29 0.6 0.85", style="rounded"];
|
||||
23[label = "retrieve_cost_data\nyear: 2030", color = "0.11 0.6 0.85", style="rounded"];
|
||||
24[label = "build_powerplants", color = "0.18 0.6 0.85", style="rounded"];
|
||||
25[label = "build_electricity_demand", color = "0.30 0.6 0.85", style="rounded"];
|
||||
26[label = "retrieve_electricity_demand", color = "0.13 0.6 0.85", style="rounded"];
|
||||
27[label = "retrieve_synthetic_electricity_demand", color = "0.43 0.6 0.85", style="rounded"];
|
||||
1 -> 0
|
||||
2 -> 1
|
||||
19 -> 1
|
||||
23 -> 1
|
||||
3 -> 2
|
||||
19 -> 2
|
||||
23 -> 2
|
||||
4 -> 3
|
||||
19 -> 3
|
||||
23 -> 3
|
||||
5 -> 4
|
||||
19 -> 4
|
||||
23 -> 4
|
||||
7 -> 4
|
||||
6 -> 5
|
||||
11 -> 5
|
||||
12 -> 5
|
||||
13 -> 5
|
||||
14 -> 5
|
||||
15 -> 5
|
||||
16 -> 5
|
||||
17 -> 5
|
||||
7 -> 5
|
||||
18 -> 5
|
||||
19 -> 5
|
||||
20 -> 5
|
||||
7 -> 5
|
||||
21 -> 5
|
||||
8 -> 5
|
||||
22 -> 5
|
||||
23 -> 5
|
||||
24 -> 5
|
||||
25 -> 5
|
||||
9 -> 5
|
||||
7 -> 6
|
||||
12 -> 6
|
||||
9 -> 6
|
||||
8 -> 6
|
||||
10 -> 6
|
||||
13 -> 6
|
||||
8 -> 7
|
||||
9 -> 8
|
||||
7 -> 11
|
||||
9 -> 11
|
||||
8 -> 11
|
||||
10 -> 11
|
||||
7 -> 12
|
||||
9 -> 12
|
||||
8 -> 12
|
||||
10 -> 12
|
||||
7 -> 13
|
||||
9 -> 13
|
||||
14 -> 13
|
||||
8 -> 13
|
||||
10 -> 13
|
||||
15 -> 14
|
||||
10 -> 14
|
||||
9 -> 7
|
||||
10 -> 9
|
||||
11 -> 9
|
||||
12 -> 9
|
||||
7 -> 14
|
||||
12 -> 14
|
||||
9 -> 14
|
||||
13 -> 14
|
||||
7 -> 15
|
||||
12 -> 15
|
||||
9 -> 15
|
||||
13 -> 15
|
||||
7 -> 16
|
||||
12 -> 16
|
||||
17 -> 16
|
||||
9 -> 16
|
||||
14 -> 16
|
||||
8 -> 16
|
||||
10 -> 16
|
||||
7 -> 17
|
||||
9 -> 17
|
||||
14 -> 17
|
||||
8 -> 17
|
||||
10 -> 17
|
||||
7 -> 18
|
||||
10 -> 18
|
||||
13 -> 16
|
||||
18 -> 17
|
||||
13 -> 17
|
||||
7 -> 19
|
||||
12 -> 19
|
||||
17 -> 19
|
||||
9 -> 19
|
||||
13 -> 19
|
||||
7 -> 20
|
||||
22 -> 21
|
||||
23 -> 21
|
||||
12 -> 20
|
||||
17 -> 20
|
||||
9 -> 20
|
||||
13 -> 20
|
||||
7 -> 21
|
||||
13 -> 21
|
||||
7 -> 22
|
||||
9 -> 22
|
||||
7 -> 24
|
||||
26 -> 25
|
||||
27 -> 25
|
||||
}
|
||||
|
||||
|
|
||||
@ -235,17 +245,21 @@ In the terminal, this will show up as a list of jobs to be run:
|
||||
build_renewable_profiles 6
|
||||
build_shapes 1
|
||||
build_ship_raster 1
|
||||
build_transmission_projects 1
|
||||
cluster_network 1
|
||||
prepare_network 1
|
||||
retrieve_cost_data 1
|
||||
retrieve_cutout 1
|
||||
retrieve_databundle 1
|
||||
retrieve_eez 1
|
||||
retrieve_electricity_demand 1
|
||||
retrieve_naturalearth_countries 1
|
||||
retrieve_osm_prebuilt 1
|
||||
retrieve_ship_raster 1
|
||||
retrieve_synthetic_electricity_demand 1
|
||||
simplify_network 1
|
||||
solve_network 1
|
||||
total 24
|
||||
total 28
|
||||
|
||||
|
||||
``snakemake`` then runs these jobs in the correct order.
|
||||
|
||||
@ -74,6 +74,7 @@ which were already included in the electricity-only tutorial:
|
||||
base_network 1
|
||||
build_ammonia_production 1
|
||||
build_biomass_potentials 1
|
||||
build_central_heating_temperature_profiles 1
|
||||
build_clustered_population_layouts 1
|
||||
build_cop_profiles 1
|
||||
build_daily_heat_demand 1
|
||||
@ -102,8 +103,9 @@ which were already included in the electricity-only tutorial:
|
||||
build_ship_raster 1
|
||||
build_shipping_demand 1
|
||||
build_simplified_population_layouts 1
|
||||
build_solar_thermal_profiles 3
|
||||
build_temperature_profiles 3
|
||||
build_solar_thermal_profiles 1
|
||||
build_temperature_profiles 1
|
||||
build_transmission_projects 1
|
||||
build_transport_demand 1
|
||||
cluster_gas_network 1
|
||||
cluster_network 1
|
||||
@ -118,16 +120,23 @@ which were already included in the electricity-only tutorial:
|
||||
retrieve_cost_data 1
|
||||
retrieve_cutout 1
|
||||
retrieve_databundle 1
|
||||
retrieve_eez 1
|
||||
retrieve_electricity_demand 1
|
||||
retrieve_eurostat_data 1
|
||||
retrieve_eurostat_household_data 1
|
||||
retrieve_gas_infrastructure_data 1
|
||||
retrieve_gem_europe_gas_tracker 1
|
||||
retrieve_gem_steel_plant_tracker 1
|
||||
retrieve_jrc_idees 1
|
||||
retrieve_naturalearth_countries 1
|
||||
retrieve_osm_prebuilt 1
|
||||
retrieve_ship_raster 1
|
||||
retrieve_synthetic_electricity_demand 1
|
||||
retrieve_worldbank_urban_population 1
|
||||
simplify_network 1
|
||||
solve_sector_network 1
|
||||
time_aggregation 1
|
||||
total 69
|
||||
total 74
|
||||
|
||||
This covers the retrieval of additional raw data from online resources and
|
||||
preprocessing data about the transport, industry, and heating sectors as well as
|
||||
@ -146,264 +155,266 @@ successfully.
|
||||
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 = "0.28 0.6 0.85", style="rounded"];
|
||||
1[label = "plot_summary", color = "0.60 0.6 0.85", style="rounded"];
|
||||
0[label = "all", color = "0.22 0.6 0.85", style="rounded"];
|
||||
1[label = "plot_summary", color = "0.11 0.6 0.85", style="rounded"];
|
||||
2[label = "make_summary", color = "0.30 0.6 0.85", style="rounded"];
|
||||
3[label = "solve_sector_network", color = "0.36 0.6 0.85", style="rounded"];
|
||||
4[label = "prepare_sector_network\nsector_opts: ", color = "0.22 0.6 0.85", style="rounded"];
|
||||
5[label = "build_renewable_profiles\ntechnology: offwind-ac", color = "0.20 0.6 0.85", style="rounded"];
|
||||
6[label = "base_network", color = "0.00 0.6 0.85", style="rounded"];
|
||||
7[label = "build_shapes", color = "0.25 0.6 0.85", style="rounded"];
|
||||
8[label = "retrieve_databundle", color = "0.06 0.6 0.85", style="rounded"];
|
||||
9[label = "build_ship_raster", color = "0.06 0.6 0.85", style="rounded"];
|
||||
10[label = "retrieve_ship_raster", color = "0.27 0.6 0.85", style="rounded"];
|
||||
11[label = "retrieve_cutout\ncutout: be-03-2013-era5", color = "0.26 0.6 0.85", style="rounded"];
|
||||
12[label = "build_renewable_profiles\ntechnology: offwind-dc", color = "0.20 0.6 0.85", style="rounded"];
|
||||
13[label = "build_renewable_profiles\ntechnology: offwind-float", color = "0.20 0.6 0.85", style="rounded"];
|
||||
14[label = "cluster_gas_network", color = "0.37 0.6 0.85", style="rounded"];
|
||||
15[label = "build_gas_network", color = "0.44 0.6 0.85", style="rounded"];
|
||||
16[label = "retrieve_gas_infrastructure_data", color = "0.43 0.6 0.85", style="rounded"];
|
||||
17[label = "cluster_network\nclusters: 5", color = "0.08 0.6 0.85", style="rounded"];
|
||||
18[label = "simplify_network\nsimpl: ", color = "0.01 0.6 0.85", style="rounded"];
|
||||
19[label = "add_electricity", color = "0.53 0.6 0.85", style="rounded"];
|
||||
20[label = "build_renewable_profiles\ntechnology: solar", color = "0.20 0.6 0.85", style="rounded"];
|
||||
21[label = "build_renewable_profiles\ntechnology: solar-hsat", color = "0.20 0.6 0.85", style="rounded"];
|
||||
22[label = "build_renewable_profiles\ntechnology: onwind", color = "0.20 0.6 0.85", style="rounded"];
|
||||
23[label = "retrieve_cost_data\nyear: 2030", color = "0.11 0.6 0.85", style="rounded"];
|
||||
24[label = "build_powerplants", color = "0.62 0.6 0.85", style="rounded"];
|
||||
25[label = "build_electricity_demand", color = "0.66 0.6 0.85", style="rounded"];
|
||||
26[label = "retrieve_electricity_demand", color = "0.20 0.6 0.85", style="rounded"];
|
||||
27[label = "retrieve_synthetic_electricity_demand", color = "0.52 0.6 0.85", style="rounded"];
|
||||
28[label = "build_gas_input_locations", color = "0.21 0.6 0.85", style="rounded"];
|
||||
29[label = "time_aggregation", color = "0.58 0.6 0.85", style="rounded"];
|
||||
30[label = "prepare_network\nll: v1.5\nopts: ", color = "0.61 0.6 0.85", style="rounded"];
|
||||
31[label = "add_extra_components", color = "0.59 0.6 0.85", style="rounded"];
|
||||
32[label = "build_hourly_heat_demand", color = "0.48 0.6 0.85", style="rounded"];
|
||||
33[label = "build_daily_heat_demand\nscope: total", color = "0.12 0.6 0.85", style="rounded"];
|
||||
34[label = "build_population_layouts", color = "0.62 0.6 0.85", style="rounded"];
|
||||
35[label = "build_solar_thermal_profiles\nscope: total", color = "0.23 0.6 0.85", style="rounded"];
|
||||
36[label = "retrieve_eurostat_data", color = "0.45 0.6 0.85", style="rounded"];
|
||||
37[label = "build_population_weighted_energy_totals\nkind: energy", color = "0.22 0.6 0.85", style="rounded"];
|
||||
38[label = "build_energy_totals", color = "0.65 0.6 0.85", style="rounded"];
|
||||
39[label = "retrieve_eurostat_household_data", color = "0.36 0.6 0.85", style="rounded"];
|
||||
40[label = "build_clustered_population_layouts", color = "0.02 0.6 0.85", style="rounded"];
|
||||
41[label = "build_population_weighted_energy_totals\nkind: heat", color = "0.22 0.6 0.85", style="rounded"];
|
||||
42[label = "build_heat_totals", color = "0.53 0.6 0.85", style="rounded"];
|
||||
43[label = "build_shipping_demand", color = "0.17 0.6 0.85", style="rounded"];
|
||||
44[label = "build_transport_demand", color = "0.49 0.6 0.85", style="rounded"];
|
||||
45[label = "build_temperature_profiles\nscope: total", color = "0.32 0.6 0.85", style="rounded"];
|
||||
46[label = "build_biomass_potentials\nplanning_horizons: 2030", color = "0.34 0.6 0.85", style="rounded"];
|
||||
47[label = "build_salt_cavern_potentials", color = "0.55 0.6 0.85", style="rounded"];
|
||||
48[label = "build_simplified_population_layouts", color = "0.46 0.6 0.85", style="rounded"];
|
||||
49[label = "build_industrial_energy_demand_per_node", color = "0.14 0.6 0.85", style="rounded"];
|
||||
50[label = "build_industry_sector_ratios_intermediate\nplanning_horizons: 2030", color = "0.27 0.6 0.85", style="rounded"];
|
||||
51[label = "build_industry_sector_ratios", color = "0.11 0.6 0.85", style="rounded"];
|
||||
52[label = "build_ammonia_production", color = "0.25 0.6 0.85", style="rounded"];
|
||||
53[label = "build_industrial_energy_demand_per_country_today", color = "0.44 0.6 0.85", style="rounded"];
|
||||
54[label = "build_industrial_production_per_country", color = "0.18 0.6 0.85", style="rounded"];
|
||||
55[label = "build_industrial_production_per_node", color = "0.41 0.6 0.85", style="rounded"];
|
||||
56[label = "build_industrial_distribution_key", color = "0.04 0.6 0.85", style="rounded"];
|
||||
57[label = "build_industrial_production_per_country_tomorrow\nplanning_horizons: 2030", color = "0.09 0.6 0.85", style="rounded"];
|
||||
58[label = "build_industrial_energy_demand_per_node_today", color = "0.46 0.6 0.85", style="rounded"];
|
||||
59[label = "build_district_heat_share\nplanning_horizons: 2030", color = "0.39 0.6 0.85", style="rounded"];
|
||||
60[label = "build_temperature_profiles\nscope: rural", color = "0.32 0.6 0.85", style="rounded"];
|
||||
61[label = "build_temperature_profiles\nscope: urban", color = "0.32 0.6 0.85", style="rounded"];
|
||||
62[label = "build_cop_profiles", color = "0.55 0.6 0.85", style="rounded"];
|
||||
63[label = "build_solar_thermal_profiles\nscope: urban", color = "0.23 0.6 0.85", style="rounded"];
|
||||
64[label = "build_solar_thermal_profiles\nscope: rural", color = "0.23 0.6 0.85", style="rounded"];
|
||||
65[label = "plot_power_network_clustered", color = "0.41 0.6 0.85", style="rounded"];
|
||||
66[label = "plot_power_network", color = "0.40 0.6 0.85", style="rounded"];
|
||||
67[label = "plot_hydrogen_network", color = "0.42 0.6 0.85", style="rounded"];
|
||||
68[label = "plot_gas_network", color = "0.32 0.6 0.85", style="rounded"];
|
||||
3[label = "solve_sector_network", color = "0.42 0.6 0.85", style="rounded"];
|
||||
4[label = "prepare_sector_network\nsector_opts: ", color = "0.45 0.6 0.85", style="rounded"];
|
||||
5[label = "build_renewable_profiles\ntechnology: offwind-ac", color = "0.44 0.6 0.85", style="rounded"];
|
||||
6[label = "base_network", color = "0.26 0.6 0.85", style="rounded"];
|
||||
7[label = "retrieve_osm_prebuilt", color = "0.01 0.6 0.85", style="rounded"];
|
||||
8[label = "build_shapes", color = "0.50 0.6 0.85", style="rounded"];
|
||||
9[label = "retrieve_naturalearth_countries", color = "0.09 0.6 0.85", style="rounded"];
|
||||
10[label = "retrieve_eez", color = "0.52 0.6 0.85", style="rounded"];
|
||||
11[label = "retrieve_databundle", color = "0.00 0.6 0.85", style="rounded"];
|
||||
12[label = "build_ship_raster", color = "0.29 0.6 0.85", style="rounded"];
|
||||
13[label = "retrieve_ship_raster", color = "0.13 0.6 0.85", style="rounded"];
|
||||
14[label = "retrieve_cutout\ncutout: be-03-2013-era5", color = "0.06 0.6 0.85", style="rounded"];
|
||||
15[label = "build_renewable_profiles\ntechnology: offwind-dc", color = "0.44 0.6 0.85", style="rounded"];
|
||||
16[label = "build_renewable_profiles\ntechnology: offwind-float", color = "0.44 0.6 0.85", style="rounded"];
|
||||
17[label = "cluster_gas_network", color = "0.48 0.6 0.85", style="rounded"];
|
||||
18[label = "build_gas_network", color = "0.59 0.6 0.85", style="rounded"];
|
||||
19[label = "retrieve_gas_infrastructure_data", color = "0.14 0.6 0.85", style="rounded"];
|
||||
20[label = "cluster_network\nclusters: 5", color = "0.08 0.6 0.85", style="rounded"];
|
||||
21[label = "simplify_network\nsimpl: ", color = "0.25 0.6 0.85", style="rounded"];
|
||||
22[label = "add_electricity", color = "0.46 0.6 0.85", style="rounded"];
|
||||
23[label = "build_renewable_profiles\ntechnology: solar", color = "0.44 0.6 0.85", style="rounded"];
|
||||
24[label = "build_renewable_profiles\ntechnology: solar-hsat", color = "0.44 0.6 0.85", style="rounded"];
|
||||
25[label = "build_renewable_profiles\ntechnology: onwind", color = "0.44 0.6 0.85", style="rounded"];
|
||||
26[label = "build_transmission_projects", color = "0.63 0.6 0.85", style="rounded"];
|
||||
27[label = "retrieve_cost_data\nyear: 2030", color = "0.05 0.6 0.85", style="rounded"];
|
||||
28[label = "build_powerplants", color = "0.43 0.6 0.85", style="rounded"];
|
||||
29[label = "build_electricity_demand", color = "0.39 0.6 0.85", style="rounded"];
|
||||
30[label = "retrieve_electricity_demand", color = "0.62 0.6 0.85", style="rounded"];
|
||||
31[label = "retrieve_synthetic_electricity_demand", color = "0.31 0.6 0.85", style="rounded"];
|
||||
32[label = "build_gas_input_locations", color = "0.45 0.6 0.85", style="rounded"];
|
||||
33[label = "retrieve_gem_europe_gas_tracker", color = "0.33 0.6 0.85", style="rounded"];
|
||||
34[label = "time_aggregation", color = "0.60 0.6 0.85", style="rounded"];
|
||||
35[label = "prepare_network\nll: v1.5\nopts: ", color = "0.23 0.6 0.85", style="rounded"];
|
||||
36[label = "add_extra_components", color = "0.36 0.6 0.85", style="rounded"];
|
||||
37[label = "build_hourly_heat_demand", color = "0.15 0.6 0.85", style="rounded"];
|
||||
38[label = "build_daily_heat_demand", color = "0.57 0.6 0.85", style="rounded"];
|
||||
39[label = "build_population_layouts", color = "0.47 0.6 0.85", style="rounded"];
|
||||
40[label = "retrieve_worldbank_urban_population", color = "0.19 0.6 0.85", style="rounded"];
|
||||
41[label = "build_solar_thermal_profiles", color = "0.11 0.6 0.85", style="rounded"];
|
||||
42[label = "retrieve_eurostat_data", color = "0.04 0.6 0.85", style="rounded"];
|
||||
43[label = "build_population_weighted_energy_totals\nkind: energy", color = "0.04 0.6 0.85", style="rounded"];
|
||||
44[label = "build_energy_totals", color = "0.30 0.6 0.85", style="rounded"];
|
||||
45[label = "retrieve_jrc_idees", color = "0.02 0.6 0.85", style="rounded"];
|
||||
46[label = "retrieve_eurostat_household_data", color = "0.49 0.6 0.85", style="rounded"];
|
||||
47[label = "build_clustered_population_layouts", color = "0.19 0.6 0.85", style="rounded"];
|
||||
48[label = "build_population_weighted_energy_totals\nkind: heat", color = "0.04 0.6 0.85", style="rounded"];
|
||||
49[label = "build_heat_totals", color = "0.08 0.6 0.85", style="rounded"];
|
||||
50[label = "build_shipping_demand", color = "0.52 0.6 0.85", style="rounded"];
|
||||
51[label = "build_transport_demand", color = "0.16 0.6 0.85", style="rounded"];
|
||||
52[label = "build_temperature_profiles", color = "0.58 0.6 0.85", style="rounded"];
|
||||
53[label = "build_biomass_potentials\nplanning_horizons: 2030", color = "0.55 0.6 0.85", style="rounded"];
|
||||
54[label = "build_salt_cavern_potentials", color = "0.28 0.6 0.85", style="rounded"];
|
||||
55[label = "build_simplified_population_layouts", color = "0.14 0.6 0.85", style="rounded"];
|
||||
56[label = "build_industrial_energy_demand_per_node", color = "0.24 0.6 0.85", style="rounded"];
|
||||
57[label = "build_industry_sector_ratios_intermediate\nplanning_horizons: 2030", color = "0.60 0.6 0.85", style="rounded"];
|
||||
58[label = "build_industry_sector_ratios", color = "0.26 0.6 0.85", style="rounded"];
|
||||
59[label = "build_ammonia_production", color = "0.16 0.6 0.85", style="rounded"];
|
||||
60[label = "build_industrial_energy_demand_per_country_today", color = "0.18 0.6 0.85", style="rounded"];
|
||||
61[label = "build_industrial_production_per_country", color = "0.61 0.6 0.85", style="rounded"];
|
||||
62[label = "build_industrial_production_per_node", color = "0.65 0.6 0.85", style="rounded"];
|
||||
63[label = "build_industrial_distribution_key", color = "0.31 0.6 0.85", style="rounded"];
|
||||
64[label = "retrieve_gem_steel_plant_tracker", color = "0.27 0.6 0.85", style="rounded"];
|
||||
65[label = "build_industrial_production_per_country_tomorrow\nplanning_horizons: 2030", color = "0.09 0.6 0.85", style="rounded"];
|
||||
66[label = "build_industrial_energy_demand_per_node_today", color = "0.40 0.6 0.85", style="rounded"];
|
||||
67[label = "build_district_heat_share\nplanning_horizons: 2030", color = "0.07 0.6 0.85", style="rounded"];
|
||||
68[label = "build_cop_profiles", color = "0.38 0.6 0.85", style="rounded"];
|
||||
69[label = "build_central_heating_temperature_profiles", color = "0.55 0.6 0.85", style="rounded"];
|
||||
70[label = "plot_power_network_clustered", color = "0.20 0.6 0.85", style="rounded"];
|
||||
71[label = "plot_power_network", color = "0.53 0.6 0.85", style="rounded"];
|
||||
72[label = "plot_hydrogen_network", color = "0.64 0.6 0.85", style="rounded"];
|
||||
73[label = "plot_gas_network", color = "0.28 0.6 0.85", style="rounded"];
|
||||
1 -> 0
|
||||
2 -> 1
|
||||
36 -> 1
|
||||
8 -> 1
|
||||
42 -> 1
|
||||
11 -> 1
|
||||
3 -> 2
|
||||
23 -> 2
|
||||
65 -> 2
|
||||
66 -> 2
|
||||
67 -> 2
|
||||
68 -> 2
|
||||
27 -> 2
|
||||
70 -> 2
|
||||
71 -> 2
|
||||
72 -> 2
|
||||
73 -> 2
|
||||
4 -> 3
|
||||
5 -> 4
|
||||
12 -> 4
|
||||
13 -> 4
|
||||
14 -> 4
|
||||
28 -> 4
|
||||
29 -> 4
|
||||
30 -> 4
|
||||
36 -> 4
|
||||
37 -> 4
|
||||
41 -> 4
|
||||
43 -> 4
|
||||
44 -> 4
|
||||
38 -> 4
|
||||
8 -> 4
|
||||
46 -> 4
|
||||
23 -> 4
|
||||
47 -> 4
|
||||
18 -> 4
|
||||
15 -> 4
|
||||
16 -> 4
|
||||
17 -> 4
|
||||
40 -> 4
|
||||
48 -> 4
|
||||
49 -> 4
|
||||
32 -> 4
|
||||
59 -> 4
|
||||
45 -> 4
|
||||
60 -> 4
|
||||
61 -> 4
|
||||
62 -> 4
|
||||
34 -> 4
|
||||
35 -> 4
|
||||
63 -> 4
|
||||
64 -> 4
|
||||
42 -> 4
|
||||
43 -> 4
|
||||
48 -> 4
|
||||
50 -> 4
|
||||
51 -> 4
|
||||
44 -> 4
|
||||
11 -> 4
|
||||
53 -> 4
|
||||
27 -> 4
|
||||
54 -> 4
|
||||
21 -> 4
|
||||
20 -> 4
|
||||
47 -> 4
|
||||
55 -> 4
|
||||
56 -> 4
|
||||
37 -> 4
|
||||
67 -> 4
|
||||
52 -> 4
|
||||
68 -> 4
|
||||
41 -> 4
|
||||
6 -> 5
|
||||
8 -> 5
|
||||
9 -> 5
|
||||
7 -> 5
|
||||
11 -> 5
|
||||
12 -> 5
|
||||
8 -> 5
|
||||
14 -> 5
|
||||
7 -> 6
|
||||
8 -> 7
|
||||
10 -> 9
|
||||
11 -> 9
|
||||
6 -> 12
|
||||
8 -> 12
|
||||
9 -> 12
|
||||
7 -> 12
|
||||
11 -> 12
|
||||
6 -> 13
|
||||
8 -> 13
|
||||
9 -> 13
|
||||
7 -> 13
|
||||
11 -> 13
|
||||
15 -> 14
|
||||
17 -> 14
|
||||
16 -> 15
|
||||
8 -> 6
|
||||
9 -> 8
|
||||
10 -> 8
|
||||
11 -> 8
|
||||
13 -> 12
|
||||
14 -> 12
|
||||
6 -> 15
|
||||
11 -> 15
|
||||
12 -> 15
|
||||
8 -> 15
|
||||
14 -> 15
|
||||
6 -> 16
|
||||
11 -> 16
|
||||
12 -> 16
|
||||
8 -> 16
|
||||
14 -> 16
|
||||
18 -> 17
|
||||
23 -> 17
|
||||
20 -> 17
|
||||
19 -> 18
|
||||
23 -> 18
|
||||
6 -> 18
|
||||
20 -> 19
|
||||
21 -> 19
|
||||
22 -> 19
|
||||
5 -> 19
|
||||
12 -> 19
|
||||
13 -> 19
|
||||
6 -> 19
|
||||
23 -> 19
|
||||
24 -> 19
|
||||
25 -> 19
|
||||
7 -> 19
|
||||
6 -> 20
|
||||
8 -> 20
|
||||
7 -> 20
|
||||
11 -> 20
|
||||
21 -> 20
|
||||
27 -> 20
|
||||
22 -> 21
|
||||
27 -> 21
|
||||
6 -> 21
|
||||
8 -> 21
|
||||
7 -> 21
|
||||
11 -> 21
|
||||
23 -> 22
|
||||
24 -> 22
|
||||
25 -> 22
|
||||
5 -> 22
|
||||
15 -> 22
|
||||
16 -> 22
|
||||
6 -> 22
|
||||
26 -> 22
|
||||
27 -> 22
|
||||
28 -> 22
|
||||
29 -> 22
|
||||
8 -> 22
|
||||
7 -> 22
|
||||
11 -> 22
|
||||
6 -> 23
|
||||
11 -> 23
|
||||
8 -> 23
|
||||
14 -> 23
|
||||
6 -> 24
|
||||
26 -> 25
|
||||
27 -> 25
|
||||
16 -> 28
|
||||
17 -> 28
|
||||
11 -> 24
|
||||
8 -> 24
|
||||
14 -> 24
|
||||
6 -> 25
|
||||
11 -> 25
|
||||
8 -> 25
|
||||
14 -> 25
|
||||
6 -> 26
|
||||
8 -> 26
|
||||
6 -> 28
|
||||
30 -> 29
|
||||
32 -> 29
|
||||
35 -> 29
|
||||
31 -> 30
|
||||
23 -> 30
|
||||
17 -> 31
|
||||
23 -> 31
|
||||
31 -> 29
|
||||
33 -> 32
|
||||
34 -> 33
|
||||
17 -> 33
|
||||
11 -> 33
|
||||
7 -> 34
|
||||
11 -> 34
|
||||
34 -> 35
|
||||
17 -> 35
|
||||
11 -> 35
|
||||
19 -> 32
|
||||
20 -> 32
|
||||
35 -> 34
|
||||
37 -> 34
|
||||
41 -> 34
|
||||
36 -> 35
|
||||
27 -> 35
|
||||
20 -> 36
|
||||
27 -> 36
|
||||
38 -> 37
|
||||
40 -> 37
|
||||
7 -> 38
|
||||
8 -> 38
|
||||
36 -> 38
|
||||
39 -> 38
|
||||
34 -> 40
|
||||
17 -> 40
|
||||
11 -> 40
|
||||
42 -> 41
|
||||
40 -> 41
|
||||
38 -> 42
|
||||
7 -> 43
|
||||
17 -> 43
|
||||
38 -> 43
|
||||
40 -> 44
|
||||
37 -> 44
|
||||
38 -> 44
|
||||
20 -> 38
|
||||
14 -> 38
|
||||
8 -> 39
|
||||
40 -> 39
|
||||
14 -> 39
|
||||
39 -> 41
|
||||
20 -> 41
|
||||
14 -> 41
|
||||
44 -> 43
|
||||
47 -> 43
|
||||
8 -> 44
|
||||
11 -> 44
|
||||
45 -> 44
|
||||
34 -> 45
|
||||
17 -> 45
|
||||
11 -> 45
|
||||
8 -> 46
|
||||
17 -> 46
|
||||
7 -> 46
|
||||
8 -> 47
|
||||
17 -> 47
|
||||
34 -> 48
|
||||
18 -> 48
|
||||
11 -> 48
|
||||
50 -> 49
|
||||
55 -> 49
|
||||
58 -> 49
|
||||
51 -> 50
|
||||
53 -> 50
|
||||
54 -> 50
|
||||
42 -> 44
|
||||
46 -> 44
|
||||
39 -> 47
|
||||
20 -> 47
|
||||
14 -> 47
|
||||
49 -> 48
|
||||
47 -> 48
|
||||
44 -> 49
|
||||
8 -> 50
|
||||
20 -> 50
|
||||
44 -> 50
|
||||
47 -> 51
|
||||
43 -> 51
|
||||
44 -> 51
|
||||
11 -> 51
|
||||
52 -> 51
|
||||
8 -> 51
|
||||
8 -> 52
|
||||
39 -> 52
|
||||
20 -> 52
|
||||
14 -> 52
|
||||
42 -> 53
|
||||
11 -> 53
|
||||
20 -> 53
|
||||
8 -> 53
|
||||
54 -> 53
|
||||
52 -> 54
|
||||
8 -> 54
|
||||
36 -> 54
|
||||
56 -> 55
|
||||
57 -> 55
|
||||
17 -> 56
|
||||
40 -> 56
|
||||
54 -> 57
|
||||
56 -> 58
|
||||
53 -> 58
|
||||
38 -> 59
|
||||
40 -> 59
|
||||
34 -> 60
|
||||
17 -> 60
|
||||
11 -> 60
|
||||
34 -> 61
|
||||
17 -> 61
|
||||
11 -> 61
|
||||
45 -> 62
|
||||
60 -> 62
|
||||
61 -> 62
|
||||
34 -> 63
|
||||
17 -> 63
|
||||
11 -> 63
|
||||
34 -> 64
|
||||
17 -> 64
|
||||
11 -> 64
|
||||
17 -> 65
|
||||
3 -> 66
|
||||
17 -> 66
|
||||
3 -> 67
|
||||
17 -> 67
|
||||
3 -> 68
|
||||
17 -> 68
|
||||
11 -> 54
|
||||
20 -> 54
|
||||
39 -> 55
|
||||
21 -> 55
|
||||
14 -> 55
|
||||
57 -> 56
|
||||
62 -> 56
|
||||
66 -> 56
|
||||
58 -> 57
|
||||
60 -> 57
|
||||
61 -> 57
|
||||
59 -> 58
|
||||
45 -> 58
|
||||
44 -> 60
|
||||
45 -> 60
|
||||
61 -> 60
|
||||
59 -> 61
|
||||
45 -> 61
|
||||
42 -> 61
|
||||
63 -> 62
|
||||
65 -> 62
|
||||
20 -> 63
|
||||
47 -> 63
|
||||
64 -> 63
|
||||
61 -> 65
|
||||
63 -> 66
|
||||
60 -> 66
|
||||
44 -> 67
|
||||
47 -> 67
|
||||
69 -> 68
|
||||
52 -> 68
|
||||
20 -> 68
|
||||
52 -> 69
|
||||
20 -> 69
|
||||
20 -> 70
|
||||
3 -> 71
|
||||
20 -> 71
|
||||
3 -> 72
|
||||
20 -> 72
|
||||
3 -> 73
|
||||
20 -> 73
|
||||
}
|
||||
|
||||
|
|
||||
|
||||
@ -2,468 +2,9 @@
|
||||
#
|
||||
# SPDX-License-Identifier: CC0-1.0
|
||||
|
||||
name: pypsa-eur
|
||||
name: pypsa-eur-20240812
|
||||
channels:
|
||||
- http://conda.anaconda.org/gurobi
|
||||
- conda-forge
|
||||
- bioconda
|
||||
- gurobi
|
||||
- defaults
|
||||
dependencies:
|
||||
- _libgcc_mutex=0.1
|
||||
- _openmp_mutex=4.5
|
||||
- affine=2.4.0
|
||||
- alsa-lib=1.2.11
|
||||
- ampl-mp=3.1.0
|
||||
- amply=0.1.6
|
||||
- appdirs=1.4.4
|
||||
- argparse-dataclass=2.0.0
|
||||
- asttokens=2.4.1
|
||||
- atk-1.0=2.38.0
|
||||
- atlite=0.2.12
|
||||
- attr=2.5.1
|
||||
- attrs=23.2.0
|
||||
- aws-c-auth=0.7.22
|
||||
- aws-c-cal=0.6.14
|
||||
- aws-c-common=0.9.19
|
||||
- aws-c-compression=0.2.18
|
||||
- aws-c-event-stream=0.4.2
|
||||
- aws-c-http=0.8.1
|
||||
- aws-c-io=0.14.8
|
||||
- aws-c-mqtt=0.10.4
|
||||
- aws-c-s3=0.5.9
|
||||
- aws-c-sdkutils=0.1.16
|
||||
- aws-checksums=0.1.18
|
||||
- aws-crt-cpp=0.26.9
|
||||
- aws-sdk-cpp=1.11.329
|
||||
- azure-core-cpp=1.11.1
|
||||
- azure-identity-cpp=1.6.0
|
||||
- azure-storage-blobs-cpp=12.10.0
|
||||
- azure-storage-common-cpp=12.5.0
|
||||
- beautifulsoup4=4.12.3
|
||||
- blosc=1.21.5
|
||||
- bokeh=3.4.1
|
||||
- bottleneck=1.3.8
|
||||
- branca=0.7.2
|
||||
- brotli=1.1.0
|
||||
- brotli-bin=1.1.0
|
||||
- brotli-python=1.1.0
|
||||
- bzip2=1.0.8
|
||||
- c-ares=1.28.1
|
||||
- c-blosc2=2.14.4
|
||||
- ca-certificates=2024.2.2
|
||||
- cads-api-client=1.0.3
|
||||
- cairo=1.18.0
|
||||
- cartopy=0.23.0
|
||||
- cdsapi=0.7.0
|
||||
- certifi=2024.2.2
|
||||
- cffi=1.16.0
|
||||
- cfgv=3.3.1
|
||||
- cfitsio=4.4.0
|
||||
- cftime=1.6.3
|
||||
- charset-normalizer=3.3.2
|
||||
- click=8.1.7
|
||||
- click-plugins=1.1.1
|
||||
- cligj=0.7.2
|
||||
- cloudpickle=3.0.0
|
||||
- coin-or-cbc=2.10.10
|
||||
- coin-or-cgl=0.60.7
|
||||
- coin-or-clp=1.17.8
|
||||
- coin-or-osi=0.108.10
|
||||
- coin-or-utils=2.11.11
|
||||
- coincbc=2.10.10
|
||||
- colorama=0.4.6
|
||||
- conda-inject=1.3.1
|
||||
- configargparse=1.7
|
||||
- connection_pool=0.0.3
|
||||
- contourpy=1.2.1
|
||||
- country_converter=1.2
|
||||
- cppad=20240000.4
|
||||
- cycler=0.12.1
|
||||
- cytoolz=0.12.3
|
||||
- dask=2024.5.1
|
||||
- dask-core=2024.5.1
|
||||
- dask-expr=1.1.1
|
||||
- datrie=0.8.2
|
||||
- dbus=1.13.6
|
||||
- decorator=5.1.1
|
||||
- deprecation=2.1.0
|
||||
- descartes=1.1.0
|
||||
- distlib=0.3.8
|
||||
- distributed=2024.5.1
|
||||
- distro=1.9.0
|
||||
- docutils=0.21.2
|
||||
- dpath=2.1.6
|
||||
- entsoe-py=0.6.7
|
||||
- et_xmlfile=1.1.0
|
||||
- exceptiongroup=1.2.0
|
||||
- executing=2.0.1
|
||||
- expat=2.6.2
|
||||
- filelock=3.14.0
|
||||
- fiona=1.9.6
|
||||
- fmt=10.2.1
|
||||
- folium=0.16.0
|
||||
- font-ttf-dejavu-sans-mono=2.37
|
||||
- font-ttf-inconsolata=3.000
|
||||
- font-ttf-source-code-pro=2.038
|
||||
- font-ttf-ubuntu=0.83
|
||||
- fontconfig=2.14.2
|
||||
- fonts-conda-ecosystem=1
|
||||
- fonts-conda-forge=1
|
||||
- fonttools=4.52.1
|
||||
- freetype=2.12.1
|
||||
- freexl=2.0.0
|
||||
- fribidi=1.0.10
|
||||
- fsspec=2024.5.0
|
||||
- gdal=3.8.5
|
||||
- gdk-pixbuf=2.42.12
|
||||
- geographiclib=2.0
|
||||
- geojson-rewind=1.1.0
|
||||
- geopandas=0.14.4
|
||||
- geopandas-base=0.14.4
|
||||
- geopy=2.4.1
|
||||
- geos=3.12.1
|
||||
- geotiff=1.7.3
|
||||
- gettext=0.22.5
|
||||
- gettext-tools=0.22.5
|
||||
- gflags=2.2.2
|
||||
- giflib=5.2.2
|
||||
- gitdb=4.0.11
|
||||
- gitpython=3.1.43
|
||||
- glib=2.80.2
|
||||
- glib-tools=2.80.2
|
||||
- glog=0.7.0
|
||||
- glpk=5.0
|
||||
- gmp=6.3.0
|
||||
- graphite2=1.3.13
|
||||
- graphviz=11.0.0
|
||||
- gst-plugins-base=1.24.3
|
||||
- gstreamer=1.24.3
|
||||
- gtk2=2.24.33
|
||||
- gts=0.7.6
|
||||
- gurobi=11.0.2
|
||||
- harfbuzz=8.5.0
|
||||
- hdf4=4.2.15
|
||||
- hdf5=1.14.3
|
||||
- humanfriendly=10.0
|
||||
- icu=73.2
|
||||
- identify=2.5.36
|
||||
- idna=3.7
|
||||
- immutables=0.20
|
||||
- importlib-metadata=7.1.0
|
||||
- importlib_metadata=7.1.0
|
||||
- importlib_resources=6.4.0
|
||||
- iniconfig=2.0.0
|
||||
- ipopt=3.14.16
|
||||
- ipython=8.24.0
|
||||
- jedi=0.19.1
|
||||
- jinja2=3.1.4
|
||||
- joblib=1.4.2
|
||||
- json-c=0.17
|
||||
- jsonschema=4.22.0
|
||||
- jsonschema-specifications=2023.12.1
|
||||
- jupyter_core=5.7.2
|
||||
- kealib=1.5.3
|
||||
- keyutils=1.6.1
|
||||
- kiwisolver=1.4.5
|
||||
- krb5=1.21.2
|
||||
- lame=3.100
|
||||
- lcms2=2.16
|
||||
- ld_impl_linux-64=2.40
|
||||
- lerc=4.0.0
|
||||
- libabseil=20240116.2
|
||||
- libaec=1.1.3
|
||||
- libarchive=3.7.4
|
||||
- libarrow=16.1.0
|
||||
- libarrow-acero=16.1.0
|
||||
- libarrow-dataset=16.1.0
|
||||
- libarrow-substrait=16.1.0
|
||||
- libasprintf=0.22.5
|
||||
- libasprintf-devel=0.22.5
|
||||
- libblas=3.9.0
|
||||
- libboost-headers=1.85.0
|
||||
- libbrotlicommon=1.1.0
|
||||
- libbrotlidec=1.1.0
|
||||
- libbrotlienc=1.1.0
|
||||
- libcap=2.69
|
||||
- libcblas=3.9.0
|
||||
- libclang-cpp15=15.0.7
|
||||
- libclang13=18.1.5
|
||||
- libcrc32c=1.1.2
|
||||
- libcups=2.3.3
|
||||
- libcurl=8.8.0
|
||||
- libdeflate=1.20
|
||||
- libedit=3.1.20191231
|
||||
- libev=4.33
|
||||
- libevent=2.1.12
|
||||
- libexpat=2.6.2
|
||||
- libffi=3.4.2
|
||||
- libflac=1.4.3
|
||||
- libgcc-ng=13.2.0
|
||||
- libgcrypt=1.10.3
|
||||
- libgd=2.3.3
|
||||
- libgdal=3.8.5
|
||||
- libgettextpo=0.22.5
|
||||
- libgettextpo-devel=0.22.5
|
||||
- libgfortran-ng=13.2.0
|
||||
- libgfortran5=13.2.0
|
||||
- libglib=2.80.2
|
||||
- libgomp=13.2.0
|
||||
- libgoogle-cloud=2.24.0
|
||||
- libgoogle-cloud-storage=2.24.0
|
||||
- libgpg-error=1.49
|
||||
- libgrpc=1.62.2
|
||||
- libhwloc=2.9.3
|
||||
- libiconv=1.17
|
||||
- libjpeg-turbo=3.0.0
|
||||
- libkml=1.3.0
|
||||
- liblapack=3.9.0
|
||||
- liblapacke=3.9.0
|
||||
- libllvm15=15.0.7
|
||||
- libllvm18=18.1.6
|
||||
- libnetcdf=4.9.2
|
||||
- libnghttp2=1.58.0
|
||||
- libnsl=2.0.1
|
||||
- libogg=1.3.4
|
||||
- libopenblas=0.3.27
|
||||
- libopus=1.3.1
|
||||
- libparquet=16.1.0
|
||||
- libpng=1.6.43
|
||||
- libpq=16.3
|
||||
- libprotobuf=4.25.3
|
||||
- libre2-11=2023.09.01
|
||||
- librsvg=2.58.0
|
||||
- librttopo=1.1.0
|
||||
- libscotch=7.0.4
|
||||
- libsndfile=1.2.2
|
||||
- libspatialindex=1.9.3
|
||||
- libspatialite=5.1.0
|
||||
- libspral=2024.01.18
|
||||
- libsqlite=3.45.3
|
||||
- libssh2=1.11.0
|
||||
- libstdcxx-ng=13.2.0
|
||||
- libsystemd0=255
|
||||
- libthrift=0.19.0
|
||||
- libtiff=4.6.0
|
||||
- libutf8proc=2.8.0
|
||||
- libuuid=2.38.1
|
||||
- libvorbis=1.3.7
|
||||
- libwebp=1.4.0
|
||||
- libwebp-base=1.4.0
|
||||
- libxcb=1.15
|
||||
- libxcrypt=4.4.36
|
||||
- libxkbcommon=1.7.0
|
||||
- libxml2=2.12.7
|
||||
- libxslt=1.1.39
|
||||
- libzip=1.10.1
|
||||
- libzlib=1.2.13
|
||||
- linopy=0.3.9
|
||||
- locket=1.0.0
|
||||
- lxml=5.2.2
|
||||
- lz4=4.3.3
|
||||
- lz4-c=1.9.4
|
||||
- lzo=2.10
|
||||
- mapclassify=2.6.1
|
||||
- markupsafe=2.1.5
|
||||
- matplotlib=3.8.4
|
||||
- matplotlib-base=3.8.4
|
||||
- matplotlib-inline=0.1.7
|
||||
- memory_profiler=0.61.0
|
||||
- metis=5.1.0
|
||||
- minizip=4.0.5
|
||||
- mpfr=4.2.1
|
||||
- mpg123=1.32.6
|
||||
- msgpack-python=1.0.8
|
||||
- multiurl=0.3.1
|
||||
- mumps-include=5.7.1
|
||||
- mumps-seq=5.7.1
|
||||
- munkres=1.1.4
|
||||
- mysql-common=8.3.0
|
||||
- mysql-libs=8.3.0
|
||||
- nbformat=5.10.4
|
||||
- ncurses=6.5
|
||||
- netcdf4=1.6.5
|
||||
- networkx=3.3
|
||||
- nodeenv=1.8.0
|
||||
- nomkl=1.0
|
||||
- nspr=4.35
|
||||
- nss=3.100
|
||||
- numexpr=2.9.0
|
||||
- numpy=1.26.4
|
||||
- openjdk=22.0.1
|
||||
- openjpeg=2.5.2
|
||||
- openpyxl=3.1.2
|
||||
- openssl=3.3.0
|
||||
- orc=2.0.1
|
||||
- packaging=24.0
|
||||
- pandas=2.2.2
|
||||
- pango=1.52.2
|
||||
- parso=0.8.4
|
||||
- partd=1.4.2
|
||||
- patsy=0.5.6
|
||||
- pcre2=10.43
|
||||
- pexpect=4.9.0
|
||||
- pickleshare=0.7.5
|
||||
- pillow=10.3.0
|
||||
- pip=24.0
|
||||
- pixman=0.43.2
|
||||
- pkgutil-resolve-name=1.3.10
|
||||
- plac=1.4.3
|
||||
- platformdirs=4.2.2
|
||||
- pluggy=1.5.0
|
||||
- ply=3.11
|
||||
- poppler=24.04.0
|
||||
- poppler-data=0.4.12
|
||||
- postgresql=16.3
|
||||
- powerplantmatching=0.5.15
|
||||
- pre-commit=3.7.1
|
||||
- progressbar2=4.4.2
|
||||
- proj=9.4.0
|
||||
- prompt-toolkit=3.0.42
|
||||
- psutil=5.9.8
|
||||
- pthread-stubs=0.4
|
||||
- ptyprocess=0.7.0
|
||||
- pulp=2.8.0
|
||||
- pulseaudio-client=17.0
|
||||
- pure_eval=0.2.2
|
||||
- py-cpuinfo=9.0.0
|
||||
- pyarrow=16.1.0
|
||||
- pyarrow-core=16.1.0
|
||||
- pyarrow-hotfix=0.6
|
||||
- pycountry=22.3.5
|
||||
- pycparser=2.22
|
||||
- pygments=2.18.0
|
||||
- pyomo=6.6.1
|
||||
- pyparsing=3.1.2
|
||||
- pyproj=3.6.1
|
||||
- pypsa=0.29.0
|
||||
- pyqt=5.15.9
|
||||
- pyqt5-sip=12.12.2
|
||||
- pyscipopt=5.0.1
|
||||
- pyshp=2.3.1
|
||||
- pysocks=1.7.1
|
||||
- pytables=3.9.2
|
||||
- pytest=8.2.1
|
||||
- python=3.11.9
|
||||
- python-dateutil=2.9.0
|
||||
- python-fastjsonschema=2.19.1
|
||||
- python-tzdata=2024.1
|
||||
- python-utils=3.8.2
|
||||
- python_abi=3.11
|
||||
- pytz=2024.1
|
||||
- pyxlsb=1.0.10
|
||||
- pyyaml=6.0.1
|
||||
- qt-main=5.15.8
|
||||
- rasterio=1.3.10
|
||||
- re2=2023.09.01
|
||||
- readline=8.2
|
||||
- referencing=0.35.1
|
||||
- requests=2.32.2
|
||||
- reretry=0.11.8
|
||||
- rioxarray=0.15.5
|
||||
- rpds-py=0.18.1
|
||||
- rtree=1.2.0
|
||||
- s2n=1.4.15
|
||||
- scikit-learn=1.5.0
|
||||
- scip=9.0.1
|
||||
- scipy=1.13.1
|
||||
- scotch=7.0.4
|
||||
- seaborn=0.13.2
|
||||
- seaborn-base=0.13.2
|
||||
- setuptools=70.0.0
|
||||
- setuptools-scm=8.1.0
|
||||
- setuptools_scm=8.1.0
|
||||
- shapely=2.0.4
|
||||
- sip=6.7.12
|
||||
- six=1.16.0
|
||||
- smart_open=7.0.4
|
||||
- smmap=5.0.0
|
||||
- snakemake-interface-common=1.17.2
|
||||
- snakemake-interface-executor-plugins=9.1.1
|
||||
- snakemake-interface-report-plugins=1.0.0
|
||||
- snakemake-interface-storage-plugins=3.2.2
|
||||
- snakemake-minimal=8.11.6
|
||||
- snappy=1.2.0
|
||||
- snuggs=1.4.7
|
||||
- sortedcontainers=2.4.0
|
||||
- soupsieve=2.5
|
||||
- spdlog=1.13.0
|
||||
- sqlite=3.45.3
|
||||
- stack_data=0.6.2
|
||||
- statsmodels=0.14.2
|
||||
- stopit=1.1.2
|
||||
- jpype1=1.5.0
|
||||
- tabulate=0.9.0
|
||||
- tbb=2021.11.0
|
||||
- tblib=3.0.0
|
||||
- threadpoolctl=3.5.0
|
||||
- throttler=1.2.2
|
||||
- tiledb=2.23.0
|
||||
- tk=8.6.13
|
||||
- toml=0.10.2
|
||||
- tomli=2.0.1
|
||||
- toolz=0.12.1
|
||||
- toposort=1.10
|
||||
- tornado=6.4
|
||||
- tqdm=4.66.4
|
||||
- traitlets=5.14.3
|
||||
- typing-extensions=4.11.0
|
||||
- typing_extensions=4.11.0
|
||||
- tzcode=2024a
|
||||
- tzdata=2024a
|
||||
- ukkonen=1.0.1
|
||||
- unidecode=1.3.8
|
||||
- unixodbc=2.3.12
|
||||
- uriparser=0.9.8
|
||||
- urllib3=2.2.1
|
||||
- validators=0.28.2
|
||||
- virtualenv=20.26.2
|
||||
- wcwidth=0.2.13
|
||||
- wheel=0.43.0
|
||||
- wrapt=1.16.0
|
||||
- xarray=2024.5.0
|
||||
- xcb-util=0.4.0
|
||||
- xcb-util-image=0.4.0
|
||||
- xcb-util-keysyms=0.4.0
|
||||
- xcb-util-renderutil=0.3.9
|
||||
- xcb-util-wm=0.4.1
|
||||
- xerces-c=3.2.5
|
||||
- xkeyboard-config=2.41
|
||||
- xlrd=2.0.1
|
||||
- xorg-fixesproto=5.0
|
||||
- xorg-inputproto=2.3.2
|
||||
- xorg-kbproto=1.0.7
|
||||
- xorg-libice=1.1.1
|
||||
- xorg-libsm=1.2.4
|
||||
- xorg-libx11=1.8.9
|
||||
- xorg-libxau=1.0.11
|
||||
- xorg-libxdmcp=1.1.3
|
||||
- xorg-libxext=1.3.4
|
||||
- xorg-libxfixes=5.0.3
|
||||
- xorg-libxi=1.7.10
|
||||
- xorg-libxrender=0.9.11
|
||||
- xorg-libxt=1.3.0
|
||||
- xorg-libxtst=1.2.3
|
||||
- xorg-recordproto=1.14.2
|
||||
- xorg-renderproto=0.11.1
|
||||
- xorg-xextproto=7.3.0
|
||||
- xorg-xf86vidmodeproto=2.3.1
|
||||
- xorg-xproto=7.0.31
|
||||
- xyzservices=2024.4.0
|
||||
- xz=5.2.6
|
||||
- yaml=0.2.5
|
||||
- yte=1.5.4
|
||||
- zict=3.0.0
|
||||
- zipp=3.17.0
|
||||
- zlib=1.2.13
|
||||
- zlib-ng=2.0.7
|
||||
- zstd=1.5.6
|
||||
- pip:
|
||||
- highspy==1.5.3
|
||||
- oauthlib==3.2.2
|
||||
- requests-oauthlib==1.3.1
|
||||
- snakemake-executor-plugin-cluster-generic==1.0.9
|
||||
- snakemake-executor-plugin-slurm==0.5.1
|
||||
- snakemake-executor-plugin-slurm-jobstep==0.2.1
|
||||
- snakemake-storage-plugin-http==0.2.3
|
||||
- tsam==2.3.1
|
||||
- tabula-py=2.9.3
|
||||
prefix: /home/fneum/miniconda3/envs/pypsa-eur-20240812
|
||||
|
||||
0
rules/build_sector.smk
Normal file → Executable file
0
rules/build_sector.smk
Normal file → Executable file
@ -312,10 +312,9 @@ if config["enable"]["retrieve"]:
|
||||
run:
|
||||
import requests
|
||||
|
||||
response = requests.get(
|
||||
"https://globalenergymonitor.org/wp-content/uploads/2024/05/Europe-Gas-Tracker-2024-05.xlsx",
|
||||
headers={"User-Agent": "Mozilla/5.0"},
|
||||
)
|
||||
# mirror of https://globalenergymonitor.org/wp-content/uploads/2024/05/Europe-Gas-Tracker-2024-05.xlsx
|
||||
url = "https://tubcloud.tu-berlin.de/s/LMBJQCsN6Ez5cN2/download/Europe-Gas-Tracker-2024-05.xlsx"
|
||||
response = requests.get(url)
|
||||
with open(output[0], "wb") as f:
|
||||
f.write(response.content)
|
||||
|
||||
@ -329,10 +328,9 @@ if config["enable"]["retrieve"]:
|
||||
run:
|
||||
import requests
|
||||
|
||||
response = requests.get(
|
||||
"https://globalenergymonitor.org/wp-content/uploads/2024/04/Global-Steel-Plant-Tracker-April-2024-Standard-Copy-V1.xlsx",
|
||||
headers={"User-Agent": "Mozilla/5.0"},
|
||||
)
|
||||
# mirror or https://globalenergymonitor.org/wp-content/uploads/2024/04/Global-Steel-Plant-Tracker-April-2024-Standard-Copy-V1.xlsx
|
||||
url = "https://tubcloud.tu-berlin.de/s/Aqebo3rrQZWKGsG/download/Global-Steel-Plant-Tracker-April-2024-Standard-Copy-V1.xlsx"
|
||||
response = requests.get(url)
|
||||
with open(output[0], "wb") as f:
|
||||
f.write(response.content)
|
||||
|
||||
|
||||
6
scripts/build_biomass_potentials.py
Normal file → Executable file
6
scripts/build_biomass_potentials.py
Normal file → Executable file
@ -330,7 +330,7 @@ def add_unsustainable_potentials(df):
|
||||
)
|
||||
|
||||
share_sus = params.get("share_sustainable_potential_available").get(investment_year)
|
||||
df *= share_sus
|
||||
df.loc[df_wo_ch.index] *= share_sus
|
||||
|
||||
df = df.join(df_wo_ch.filter(like="unsustainable")).fillna(0)
|
||||
|
||||
@ -345,8 +345,8 @@ if __name__ == "__main__":
|
||||
snakemake = mock_snakemake(
|
||||
"build_biomass_potentials",
|
||||
simpl="",
|
||||
clusters="37",
|
||||
planning_horizons=2020,
|
||||
clusters="38",
|
||||
planning_horizons=2050,
|
||||
)
|
||||
|
||||
configure_logging(snakemake)
|
||||
|
||||
@ -79,7 +79,7 @@ def build_biomass_transport_costs():
|
||||
transport_costs.name = "EUR/km/MWh"
|
||||
|
||||
# rename country names
|
||||
to_rename = {"UK": "GB", "XK": "KO", "EL": "GR"}
|
||||
to_rename = {"UK": "GB", "EL": "GR"}
|
||||
transport_costs.rename(to_rename, inplace=True)
|
||||
|
||||
# add missing Norway with data from Sweden
|
||||
|
||||
@ -58,6 +58,15 @@ class CentralHeatingTemperatureApproximator:
|
||||
rolling_window_ambient_temperature : int
|
||||
Rolling window size for averaging ambient temperature.
|
||||
"""
|
||||
|
||||
if any(max_forward_temperature < min_forward_temperature):
|
||||
raise ValueError(
|
||||
"max_forward_temperature must be greater than min_forward_temperature"
|
||||
)
|
||||
if any(min_forward_temperature < fixed_return_temperature):
|
||||
raise ValueError(
|
||||
"min_forward_temperature must be greater than fixed_return_temperature"
|
||||
)
|
||||
self._ambient_temperature = ambient_temperature
|
||||
self.max_forward_temperature = max_forward_temperature
|
||||
self.min_forward_temperature = min_forward_temperature
|
||||
|
||||
@ -9,8 +9,8 @@ al. 2019, where for ambient temperatures below 0C, the highest possible forward
|
||||
temperature is assumed and vice versa for temperatures above 10C. Between these
|
||||
threshold levels, forward temperatures are linearly interpolated.
|
||||
|
||||
By default, temperature levels are increased for non-Scandinavian countries.
|
||||
The default ratios between min. and max. forward temperatures is based on AGFW-Hauptbericht 2022.
|
||||
By default, `max_forward_temperature` from Euroheat DHC Market Outlook 2024 is used; `min_forward_temperature` and `return_temperature` for Germany is used from AGFW-Hauptbericht 2022.
|
||||
`min_forward_temperature` and `return_temperature` for other countries are extrapolated based on the ratio between `max_forward_temperature` and `min_forward_temperature` and `return_temperature` for those countries not missing (by default only Germany).
|
||||
|
||||
Relevant Settings
|
||||
-----------------
|
||||
@ -47,26 +47,68 @@ from central_heating_temperature_approximator import (
|
||||
)
|
||||
|
||||
|
||||
def extrapolate_missing_supply_temperatures_by_country(
|
||||
extrapolate_from: dict, extrapolate_to: dict
|
||||
) -> xr.DataArray:
|
||||
"""
|
||||
Extrapolates missing supply temperatures by country.
|
||||
|
||||
Parameters:
|
||||
extrapolate_from (dict): A dictionary containing supply temperatures to extrapolate from. Should contain all countries.
|
||||
extrapolate_to (dict): A dictionary containing supply temperatures to extrapolate to. Where `country` is present, average ratio between `extrapolate_to[country]` and `extrapolate_from[country]` is applied to all countries for which `country` is not present in `extrapolate_from.keys()` to infer ratio for extrapolation.
|
||||
|
||||
Returns:
|
||||
xr.DataArray: A DataArray containing the extrapolated supply temperatures.
|
||||
"""
|
||||
|
||||
if not all([key in extrapolate_from.keys() for key in extrapolate_to.keys()]):
|
||||
raise ValueError(
|
||||
"Not all countries in extrapolate_to are present in extrapolate_from."
|
||||
)
|
||||
# average ratio between extrapolate_from and extrapolate_to for those countries that are in both dictionaries
|
||||
extrapolation_ratio = np.mean(
|
||||
[extrapolate_to[key] / extrapolate_from[key] for key in extrapolate_to.keys()]
|
||||
)
|
||||
|
||||
# apply extrapolation ratio to all keys missing in extrapolate_to
|
||||
return {
|
||||
key: (
|
||||
extrapolate_to[key]
|
||||
if key in extrapolate_to.keys()
|
||||
else extrapolate_from[key] * extrapolation_ratio
|
||||
)
|
||||
for key in extrapolate_from.keys()
|
||||
}
|
||||
|
||||
|
||||
def get_country_from_node_name(node_name: str) -> str:
|
||||
"""
|
||||
Extracts the country code from a given node name.
|
||||
|
||||
Parameters:
|
||||
node_name (str): The name of the node.
|
||||
|
||||
Returns:
|
||||
str: The country code extracted from the node name.
|
||||
"""
|
||||
return node_name[:2]
|
||||
|
||||
|
||||
def map_temperature_dict_to_onshore_regions(
|
||||
supply_temperature_by_country: dict,
|
||||
regions_onshore: pd.Index,
|
||||
snapshots: pd.DatetimeIndex,
|
||||
) -> xr.DataArray:
|
||||
"""
|
||||
Map dictionary of temperatures to onshore regions.
|
||||
|
||||
Missing values are replaced by the mean of all values.
|
||||
|
||||
Parameters:
|
||||
----------
|
||||
supply_temperature_by_country : dictionary
|
||||
Dictionary with temperatures as values and country keys as keys. One key must be named "default"
|
||||
Dictionary with temperatures as values and country keys as keys.
|
||||
regions_onshore : pd.Index
|
||||
Names of onshore regions
|
||||
snapshots : pd.DatetimeIndex
|
||||
Time stamps
|
||||
|
||||
Returns:
|
||||
-------
|
||||
@ -75,20 +117,16 @@ def map_temperature_dict_to_onshore_regions(
|
||||
"""
|
||||
return xr.DataArray(
|
||||
[
|
||||
[
|
||||
(
|
||||
supply_temperature_by_country[get_country_from_node_name(node_name)]
|
||||
if get_country_from_node_name(node_name)
|
||||
in supply_temperature_by_country.keys()
|
||||
else supply_temperature_by_country["default"]
|
||||
)
|
||||
for node_name in regions_onshore.values
|
||||
]
|
||||
# pass both nodes and snapshots as dimensions to preserve correct data structure
|
||||
for _ in snapshots
|
||||
(
|
||||
supply_temperature_by_country[get_country_from_node_name(node_name)]
|
||||
if get_country_from_node_name(node_name)
|
||||
in supply_temperature_by_country.keys()
|
||||
else np.mean(list(supply_temperature_by_country.values()))
|
||||
)
|
||||
for node_name in regions_onshore.values
|
||||
],
|
||||
dims=["time", "name"],
|
||||
coords={"time": snapshots, "name": regions_onshore},
|
||||
dims=["name"],
|
||||
coords={"name": regions_onshore},
|
||||
)
|
||||
|
||||
|
||||
@ -104,28 +142,35 @@ if __name__ == "__main__":
|
||||
|
||||
set_scenario_config(snakemake)
|
||||
|
||||
max_forward_temperature = snakemake.params.max_forward_temperature_central_heating
|
||||
min_forward_temperature = extrapolate_missing_supply_temperatures_by_country(
|
||||
extrapolate_from=max_forward_temperature,
|
||||
extrapolate_to=snakemake.params.min_forward_temperature_central_heating,
|
||||
)
|
||||
return_temperature = extrapolate_missing_supply_temperatures_by_country(
|
||||
extrapolate_from=max_forward_temperature,
|
||||
extrapolate_to=snakemake.params.return_temperature_central_heating,
|
||||
)
|
||||
|
||||
# map forward and return temperatures specified on country-level to onshore regions
|
||||
regions_onshore = gpd.read_file(snakemake.input.regions_onshore)["name"]
|
||||
snapshots = pd.date_range(freq="h", **snakemake.params.snapshots)
|
||||
max_forward_temperature_central_heating_by_node_and_time: xr.DataArray = (
|
||||
map_temperature_dict_to_onshore_regions(
|
||||
supply_temperature_by_country=snakemake.params.max_forward_temperature_central_heating,
|
||||
supply_temperature_by_country=max_forward_temperature,
|
||||
regions_onshore=regions_onshore,
|
||||
snapshots=snapshots,
|
||||
)
|
||||
)
|
||||
min_forward_temperature_central_heating_by_node_and_time: xr.DataArray = (
|
||||
map_temperature_dict_to_onshore_regions(
|
||||
supply_temperature_by_country=snakemake.params.min_forward_temperature_central_heating,
|
||||
supply_temperature_by_country=min_forward_temperature,
|
||||
regions_onshore=regions_onshore,
|
||||
snapshots=snapshots,
|
||||
)
|
||||
)
|
||||
return_temperature_central_heating_by_node_and_time: xr.DataArray = (
|
||||
map_temperature_dict_to_onshore_regions(
|
||||
supply_temperature_by_country=snakemake.params.return_temperature_central_heating,
|
||||
supply_temperature_by_country=return_temperature,
|
||||
regions_onshore=regions_onshore,
|
||||
snapshots=snapshots,
|
||||
)
|
||||
)
|
||||
|
||||
|
||||
@ -37,7 +37,7 @@ Outputs
|
||||
-------
|
||||
|
||||
- ``cutouts/{cutout}``: weather data from either the `ERA5 <https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5>`_
|
||||
reanalysis weather dataset or `SARAH-2 <https://wui.cmsaf.eu/safira/action/viewProduktSearch>`_
|
||||
reanalysis weather dataset or `SARAH-3 <https://wui.cmsaf.eu/safira/action/viewProduktSearch>`_
|
||||
satellite-based historic weather data with the following structure:
|
||||
|
||||
**ERA5 cutout:**
|
||||
@ -80,7 +80,7 @@ Outputs
|
||||
.. image:: img/era5.png
|
||||
:scale: 40 %
|
||||
|
||||
A **SARAH-2 cutout** can be used to amend the fields ``temperature``, ``influx_toa``, ``influx_direct``, ``albedo``,
|
||||
A **SARAH-3 cutout** can be used to amend the fields ``temperature``, ``influx_toa``, ``influx_direct``, ``albedo``,
|
||||
``influx_diffuse`` of ERA5 using satellite-based radiation observations.
|
||||
|
||||
.. image:: img/sarah.png
|
||||
|
||||
@ -5,8 +5,8 @@
|
||||
|
||||
from enum import Enum
|
||||
|
||||
from scripts.definitions.heat_sector import HeatSector
|
||||
from scripts.definitions.heat_system_type import HeatSystemType
|
||||
from definitions.heat_sector import HeatSector
|
||||
from definitions.heat_system_type import HeatSystemType
|
||||
|
||||
|
||||
class HeatSystem(Enum):
|
||||
|
||||
130
scripts/prepare_sector_network.py
Normal file → Executable file
130
scripts/prepare_sector_network.py
Normal file → Executable file
@ -63,7 +63,8 @@ def define_spatial(nodes, options):
|
||||
|
||||
if options.get("biomass_spatial", options["biomass_transport"]):
|
||||
spatial.biomass.nodes = nodes + " solid biomass"
|
||||
spatial.biomass.bioliquids = nodes + " bioliquids"
|
||||
spatial.biomass.nodes_unsustainable = nodes + " unsustainable solid biomass"
|
||||
spatial.biomass.bioliquids = nodes + " unsustainable bioliquids"
|
||||
spatial.biomass.locations = nodes
|
||||
spatial.biomass.industry = nodes + " solid biomass for industry"
|
||||
spatial.biomass.industry_cc = nodes + " solid biomass for industry CC"
|
||||
@ -71,6 +72,7 @@ def define_spatial(nodes, options):
|
||||
spatial.msw.locations = nodes
|
||||
else:
|
||||
spatial.biomass.nodes = ["EU solid biomass"]
|
||||
spatial.biomass.nodes_unsustainable = ["EU unsustainable solid biomass"]
|
||||
spatial.biomass.bioliquids = ["EU unsustainable bioliquids"]
|
||||
spatial.biomass.locations = ["EU"]
|
||||
spatial.biomass.industry = ["solid biomass for industry"]
|
||||
@ -573,12 +575,43 @@ def add_carrier_buses(n, carrier, nodes=None):
|
||||
fossils = ["coal", "gas", "oil", "lignite"]
|
||||
if options.get("fossil_fuels", True) and carrier in fossils:
|
||||
|
||||
suffix = ""
|
||||
|
||||
if carrier == "oil" and cf_industry["oil_refining_emissions"] > 0:
|
||||
|
||||
n.madd(
|
||||
"Bus",
|
||||
nodes + " primary",
|
||||
location=location,
|
||||
carrier=carrier + " primary",
|
||||
unit=unit,
|
||||
)
|
||||
|
||||
n.madd(
|
||||
"Link",
|
||||
nodes + " refining",
|
||||
bus0=nodes + " primary",
|
||||
bus1=nodes,
|
||||
bus2="co2 atmosphere",
|
||||
location=location,
|
||||
carrier=carrier + " refining",
|
||||
p_nom=1e6,
|
||||
efficiency=1
|
||||
- (
|
||||
cf_industry["oil_refining_emissions"]
|
||||
/ costs.at[carrier, "CO2 intensity"]
|
||||
),
|
||||
efficiency2=cf_industry["oil_refining_emissions"],
|
||||
)
|
||||
|
||||
suffix = " primary"
|
||||
|
||||
n.madd(
|
||||
"Generator",
|
||||
nodes,
|
||||
bus=nodes,
|
||||
nodes + suffix,
|
||||
bus=nodes + suffix,
|
||||
p_nom_extendable=True,
|
||||
carrier=carrier,
|
||||
carrier=carrier + suffix,
|
||||
marginal_cost=costs.at[carrier, "fuel"],
|
||||
)
|
||||
|
||||
@ -2148,8 +2181,6 @@ def add_heat(n: pypsa.Network, costs: pd.DataFrame, cop: xr.DataArray):
|
||||
|
||||
heat_demand = build_heat_demand(n)
|
||||
|
||||
overdim_factor = options["overdimension_individual_heating"]
|
||||
|
||||
district_heat_info = pd.read_csv(snakemake.input.district_heat_share, index_col=0)
|
||||
dist_fraction = district_heat_info["district fraction of node"]
|
||||
urban_fraction = district_heat_info["urban fraction"]
|
||||
@ -2178,6 +2209,9 @@ def add_heat(n: pypsa.Network, costs: pd.DataFrame, cop: xr.DataArray):
|
||||
HeatSystem
|
||||
): # this loops through all heat systems defined in _entities.HeatSystem
|
||||
|
||||
overdim_factor = options["overdimension_heat_generators"][
|
||||
heat_system.central_or_decentral
|
||||
]
|
||||
if heat_system == HeatSystem.URBAN_CENTRAL:
|
||||
nodes = dist_fraction.index[dist_fraction > 0]
|
||||
else:
|
||||
@ -2654,7 +2688,7 @@ def add_biomass(n, costs):
|
||||
if (
|
||||
options["municipal_solid_waste"]
|
||||
and not options["industry"]
|
||||
and (cf_industry["waste_to_energy"] or cf_industry["waste_to_energy_cc"])
|
||||
and not (cf_industry["waste_to_energy"] or cf_industry["waste_to_energy_cc"])
|
||||
):
|
||||
logger.warning(
|
||||
"Flag municipal_solid_waste can be only used with industry "
|
||||
@ -2674,12 +2708,9 @@ def add_biomass(n, costs):
|
||||
carrier="municipal solid waste",
|
||||
)
|
||||
|
||||
e_max_pu = np.array(
|
||||
len(spatial.msw.nodes) * [[1] * (len(n.snapshots) - 1) + [0]]
|
||||
).T
|
||||
e_max_pu = pd.DataFrame(
|
||||
e_max_pu, index=n.snapshots, columns=spatial.msw.nodes
|
||||
).astype(float)
|
||||
e_max_pu = pd.DataFrame(1, index=n.snapshots, columns=spatial.msw.nodes)
|
||||
e_max_pu.iloc[-1] = 0
|
||||
|
||||
n.madd(
|
||||
"Store",
|
||||
spatial.msw.nodes,
|
||||
@ -2794,14 +2825,23 @@ def add_biomass(n, costs):
|
||||
e_max_pu=e_max_pu,
|
||||
)
|
||||
|
||||
e_max_pu = pd.DataFrame(1, index=n.snapshots, columns=spatial.biomass.nodes)
|
||||
n.madd(
|
||||
"Bus",
|
||||
spatial.biomass.nodes_unsustainable,
|
||||
location=spatial.biomass.locations,
|
||||
carrier="unsustainable solid biomass",
|
||||
unit="MWh_LHV",
|
||||
)
|
||||
|
||||
e_max_pu = pd.DataFrame(
|
||||
1, index=n.snapshots, columns=spatial.biomass.nodes_unsustainable
|
||||
)
|
||||
e_max_pu.iloc[-1] = 0
|
||||
|
||||
n.madd(
|
||||
"Store",
|
||||
spatial.biomass.nodes,
|
||||
suffix=" unsustainable",
|
||||
bus=spatial.biomass.nodes,
|
||||
spatial.biomass.nodes_unsustainable,
|
||||
bus=spatial.biomass.nodes_unsustainable,
|
||||
carrier="unsustainable solid biomass",
|
||||
e_nom=unsustainable_solid_biomass_potentials_spatial,
|
||||
marginal_cost=costs.at["fuelwood", "fuel"],
|
||||
@ -2810,6 +2850,16 @@ def add_biomass(n, costs):
|
||||
e_max_pu=e_max_pu,
|
||||
)
|
||||
|
||||
n.madd(
|
||||
"Link",
|
||||
spatial.biomass.nodes_unsustainable,
|
||||
bus0=spatial.biomass.nodes_unsustainable,
|
||||
bus1=spatial.biomass.nodes,
|
||||
carrier="unsustainable solid biomass",
|
||||
efficiency=1,
|
||||
p_nom=unsustainable_solid_biomass_potentials_spatial,
|
||||
)
|
||||
|
||||
n.madd(
|
||||
"Bus",
|
||||
spatial.biomass.bioliquids,
|
||||
@ -2826,7 +2876,6 @@ def add_biomass(n, costs):
|
||||
n.madd(
|
||||
"Store",
|
||||
spatial.biomass.bioliquids,
|
||||
suffix=" unsustainable",
|
||||
bus=spatial.biomass.bioliquids,
|
||||
carrier="unsustainable bioliquids",
|
||||
e_nom=unsustainable_liquid_biofuel_potentials_spatial,
|
||||
@ -2836,6 +2885,8 @@ def add_biomass(n, costs):
|
||||
e_max_pu=e_max_pu,
|
||||
)
|
||||
|
||||
add_carrier_buses(n, "oil")
|
||||
|
||||
n.madd(
|
||||
"Link",
|
||||
spatial.biomass.bioliquids,
|
||||
@ -2964,6 +3015,32 @@ def add_biomass(n, costs):
|
||||
constant=biomass_potentials["solid biomass"].sum(),
|
||||
type="operational_limit",
|
||||
)
|
||||
if biomass_potentials["unsustainable solid biomass"].sum() > 0:
|
||||
n.madd(
|
||||
"Generator",
|
||||
spatial.biomass.nodes_unsustainable,
|
||||
bus=spatial.biomass.nodes_unsustainable,
|
||||
carrier="unsustainable solid biomass",
|
||||
p_nom=10000,
|
||||
marginal_cost=costs.at["fuelwood", "fuel"]
|
||||
+ bus_transport_costs * average_distance,
|
||||
)
|
||||
# Set last snapshot of e_max_pu for unsustainable solid biomass to 1 to make operational limit work
|
||||
unsus_stores_idx = n.stores.query(
|
||||
"carrier == 'unsustainable solid biomass'"
|
||||
).index
|
||||
unsus_stores_idx = unsus_stores_idx.intersection(
|
||||
n.stores_t.e_max_pu.columns
|
||||
)
|
||||
n.stores_t.e_max_pu.loc[n.snapshots[-1], unsus_stores_idx] = 1
|
||||
n.add(
|
||||
"GlobalConstraint",
|
||||
"unsustainable biomass limit",
|
||||
carrier_attribute="unsustainable solid biomass",
|
||||
sense="==",
|
||||
constant=biomass_potentials["unsustainable solid biomass"].sum(),
|
||||
type="operational_limit",
|
||||
)
|
||||
|
||||
if options["municipal_solid_waste"]:
|
||||
# Add municipal solid waste
|
||||
@ -3055,7 +3132,9 @@ def add_biomass(n, costs):
|
||||
efficiency=costs.at["biomass boiler", "efficiency"],
|
||||
capital_cost=costs.at["biomass boiler", "efficiency"]
|
||||
* costs.at["biomass boiler", "fixed"]
|
||||
* options["overdimension_individual_heating"],
|
||||
* options["overdimension_heat_generators"][
|
||||
HeatSystem(name).central_or_decentral
|
||||
],
|
||||
marginal_cost=costs.at["biomass boiler", "pelletizing cost"],
|
||||
lifetime=costs.at["biomass boiler", "lifetime"],
|
||||
)
|
||||
@ -3577,7 +3656,9 @@ def add_industry(n, costs):
|
||||
efficiency2=costs.at["oil", "CO2 intensity"],
|
||||
capital_cost=costs.at["decentral oil boiler", "efficiency"]
|
||||
* costs.at["decentral oil boiler", "fixed"]
|
||||
* options["overdimension_individual_heating"],
|
||||
* options["overdimension_heat_generators"][
|
||||
heat_system.central_or_decentral
|
||||
],
|
||||
lifetime=costs.at["decentral oil boiler", "lifetime"],
|
||||
)
|
||||
|
||||
@ -3680,9 +3761,13 @@ def add_industry(n, costs):
|
||||
spatial.msw.locations,
|
||||
bus0=spatial.msw.nodes,
|
||||
bus1=non_sequestered_hvc_locations,
|
||||
bus2="co2 atmosphere",
|
||||
carrier="municipal solid waste",
|
||||
p_nom_extendable=True,
|
||||
efficiency=1.0,
|
||||
efficiency2=-costs.at[
|
||||
"oil", "CO2 intensity"
|
||||
], # because msw is co2 neutral and will be burned in waste CHP or decomposed as oil
|
||||
)
|
||||
|
||||
n.madd(
|
||||
@ -4584,11 +4669,10 @@ if __name__ == "__main__":
|
||||
"prepare_sector_network",
|
||||
simpl="",
|
||||
opts="",
|
||||
clusters="37",
|
||||
clusters="38",
|
||||
ll="vopt",
|
||||
sector_opts="",
|
||||
planning_horizons="2050",
|
||||
run="enable_all",
|
||||
planning_horizons="2030",
|
||||
)
|
||||
|
||||
configure_logging(snakemake)
|
||||
|
||||
@ -330,8 +330,8 @@ def add_carbon_constraint(n, snapshots):
|
||||
continue
|
||||
|
||||
# stores
|
||||
n.stores["carrier"] = n.stores.bus.map(n.buses.carrier)
|
||||
stores = n.stores.query("carrier in @emissions.index and not e_cyclic")
|
||||
bus_carrier = n.stores.bus.map(n.buses.carrier)
|
||||
stores = n.stores[bus_carrier.isin(emissions.index) & ~n.stores.e_cyclic]
|
||||
if not stores.empty:
|
||||
last = n.snapshot_weightings.reset_index().groupby("period").last()
|
||||
last_i = last.set_index([last.index, last.timestep]).index
|
||||
@ -356,8 +356,8 @@ def add_carbon_budget_constraint(n, snapshots):
|
||||
continue
|
||||
|
||||
# stores
|
||||
n.stores["carrier"] = n.stores.bus.map(n.buses.carrier)
|
||||
stores = n.stores.query("carrier in @emissions.index and not e_cyclic")
|
||||
bus_carrier = n.stores.bus.map(n.buses.carrier)
|
||||
stores = n.stores[bus_carrier.isin(emissions.index) & ~n.stores.e_cyclic]
|
||||
if not stores.empty:
|
||||
last = n.snapshot_weightings.reset_index().groupby("period").last()
|
||||
last_i = last.set_index([last.index, last.timestep]).index
|
||||
@ -1000,8 +1000,8 @@ def add_co2_atmosphere_constraint(n, snapshots):
|
||||
continue
|
||||
|
||||
# stores
|
||||
n.stores["carrier"] = n.stores.bus.map(n.buses.carrier)
|
||||
stores = n.stores.query("carrier in @emissions.index and not e_cyclic")
|
||||
bus_carrier = n.stores.bus.map(n.buses.carrier)
|
||||
stores = n.stores[bus_carrier.isin(emissions.index) & ~n.stores.e_cyclic]
|
||||
if not stores.empty:
|
||||
last_i = snapshots[-1]
|
||||
lhs = n.model["Store-e"].loc[last_i, stores.index]
|
||||
|
||||
Loading…
Reference in New Issue
Block a user