merge master

.github/ISSUE_TEMPLATE/bug_report.md

@@ -11,7 +11,7 @@ assignees: ''
 ## Checklist
 
 - [ ] I am using the current [`master`](https://github.com/PyPSA/pypsa-eur/tree/master) branch or the latest [release](https://github.com/PyPSA/pypsa-eur/releases). Please indicate.
-- [ ] I am running on an up-to-date [`pypsa-eur` environment](https://github.com/PyPSA/pypsa-eur/blob/master/environment.yaml). Update via `conda env update -f environment.yaml`.
+- [ ] I am running on an up-to-date [`pypsa-eur` environment](https://github.com/PyPSA/pypsa-eur/blob/master/envs/environment.yaml). Update via `conda env update -f envs/environment.yaml`.
 
 ## Describe the Bug
 
@@ -24,4 +24,4 @@ assignees: ''
 
 ```
 <paste here>
-```
+```

.github/ISSUE_TEMPLATE/config.yml

@@ -2,4 +2,4 @@ blank_issues_enabled: false
 contact_links:
   - name: PyPSA Mailing List
     url: https://groups.google.com/forum/#!forum/pypsa
-    about: Please ask and answer general usage questions here.
+    about: Please ask and answer general usage questions here.

.github/pull_request_template.md

@@ -7,7 +7,7 @@ Closes # (if applicable).
 
 - [ ] I tested my contribution locally and it seems to work fine.
 - [ ] Code and workflow changes are sufficiently documented.
-- [ ] Newly introduced dependencies are added to `environment.yaml` and `environment.docs.yaml`.
+- [ ] Newly introduced dependencies are added to `envs/environment.yaml` and `envs/environment.docs.yaml`.
 - [ ] Changes in configuration options are added in all of `config.default.yaml`, `config.tutorial.yaml`, and `test/config.test1.yaml`.
 - [ ] Changes in configuration options are also documented in `doc/configtables/*.csv` and line references are adjusted in `doc/configuration.rst` and `doc/tutorial.rst`.
-- [ ] A note for the release notes `doc/release_notes.rst` is amended in the format of previous release notes.
+- [ ] A note for the release notes `doc/release_notes.rst` is amended in the format of previous release notes.

.gitignore

@@ -7,6 +7,7 @@
 __pycache__
 *dconf
 gurobi.log
+.vscode
 
 /bak
 /resources

.readthedocs.yml

@@ -5,4 +5,4 @@
 version: 2
 
 conda:
-    environment: environment.docs.yaml
+    environment: envs/environment.docs.yaml

.reuse/dep5

@@ -25,4 +25,4 @@ License: CC0-1.0
 
 Files: borg-it
 Copyright: : 2017-2020 The PyPSA-Eur Authors
-License: CC0-1.0
+License: CC0-1.0

.travis.yml

@@ -2,6 +2,10 @@
 #
 # SPDX-License-Identifier: GPL-3.0-or-later
 
+branches:
+  only:
+  - master
+
 os:
   - windows
   - linux
@@ -15,14 +19,18 @@ before_install:
   - source conda4travis.sh
 
   # install conda environment
-  - conda env create -f ./environment.yaml
+  - conda install -c conda-forge mamba
+  - mamba env create -f ./envs/environment.yaml
   - conda activate pypsa-eur
 
   # install open-source solver
-  - conda install -c conda-forge ipopt glpk
+  - mamba install -c conda-forge glpk ipopt'<3.13.3'
+
+  # list packages for easier debugging
+  - conda list
 
 script:
   - cp ./test/config.test1.yaml ./config.yaml
-  - snakemake -j all solve_all_elec_networks
+  - snakemake -j all solve_all_networks
   - rm -rf resources/*.nc resources/*.geojson resources/*.h5 networks results
   # could repeat for more configurations in future

README.md

@@ -7,7 +7,7 @@ SPDX-License-Identifier: CC-BY-4.0
 [![Build Status](https://travis-ci.org/PyPSA/pypsa-eur.svg?branch=master)](https://travis-ci.org/PyPSA/pypsa-eur)
 [![Documentation](https://readthedocs.org/projects/pypsa-eur/badge/?version=latest)](https://pypsa-eur.readthedocs.io/en/latest/?badge=latest)
 ![Size](https://img.shields.io/github/repo-size/pypsa/pypsa-eur)
-[![Zenodo](https://zenodo.org/badge/DOI/10.5281/zenodo.3520875.svg)](https://doi.org/10.5281/zenodo.3520875)
+[![Zenodo](https://zenodo.org/badge/DOI/10.5281/zenodo.3520874.svg)](https://doi.org/10.5281/zenodo.3520874)
 [![Gitter](https://badges.gitter.im/PyPSA/community.svg)](https://gitter.im/PyPSA/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
 [![Snakemake](https://img.shields.io/badge/snakemake-≥5.0.0-brightgreen.svg?style=flat)](https://snakemake.readthedocs.io)
 [![REUSE status](https://api.reuse.software/badge/github.com/pypsa/pypsa-eur)](https://api.reuse.software/info/github.com/pypsa/pypsa-eur)
@@ -36,13 +36,13 @@ and local grid
 bottlenecks may cause unrealistic load-shedding or generator
 curtailment. We recommend to cluster the network to a couple of
 hundred nodes to remove these local inconsistencies. See the
-discussion in Section 3.4 "Model validation" of the paper. 
+discussion in Section 3.4 "Model validation" of the paper.
 
 ![PyPSA-Eur Grid Model](doc/img/base.png)
 
 ![PyPSA-Eur Grid Model Simplified](doc/img/elec_s_X.png)
 
-The model is designed to be imported into the open toolbox
+The model building routines are defined through a snakemake workflow. The model is designed to be imported into the open toolbox
 [PyPSA](https://github.com/PyPSA/PyPSA) for operational studies as
 well as generation and transmission expansion planning studies.
 
@@ -61,7 +61,7 @@ The dataset consists of:
 - Geographical potentials for wind and solar generators based on land use (CORINE) and excluding nature reserves (Natura2000) are computed with the [vresutils library](https://github.com/FRESNA/vresutils) and the [glaes library](https://github.com/FZJ-IEK3-VSA/glaes).
 
 Already-built versions of the model can be found in the accompanying [Zenodo
-repository](https://doi.org/10.5281/zenodo.3601882).
+repository](https://doi.org/10.5281/zenodo.3601881).
 
 A version of the model that adds building heating, transport and
 industry sectors to the model, as well as gas networks, can be found

Snakefile

@@ -11,33 +11,30 @@ if not exists("config.yaml"):
 configfile: "config.yaml"
 
 COSTS="resources/costs.csv"
+ATLITE_NPROCESSES = config['atlite'].get('nprocesses', 4)
 
 wildcard_constraints:
-    ll="(v|c)([0-9\.]+|opt|all)|all", # line limit, can be volume or cost
     simpl="[a-zA-Z0-9]*|all",
     clusters="[0-9]+m?|all",
-    sectors="[+a-zA-Z0-9]+",
+    ll="(v|c)([0-9\.]+|opt|all)|all",
     opts="[-+a-zA-Z0-9\.]*"
 
-rule cluster_all_elec_networks:
-    input:
-        expand("networks/elec_s{simpl}_{clusters}.nc",
-               **config['scenario'])
 
-rule extra_components_all_elec_networks:
-    input:
-        expand("networks/elec_s{simpl}_{clusters}_ec.nc",
-               **config['scenario'])
+rule cluster_all_networks:
+    input: expand("networks/elec_s{simpl}_{clusters}.nc", **config['scenario'])
 
-rule prepare_all_elec_networks:
-    input:
-        expand("networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc",
-               **config['scenario'])
 
-rule solve_all_elec_networks:
-    input:
-        expand("results/networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc",
-               **config['scenario'])
+rule extra_components_all_networks:
+    input: expand("networks/elec_s{simpl}_{clusters}_ec.nc", **config['scenario'])
+
+
+rule prepare_all_networks:
+    input: expand("networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc", **config['scenario'])
+
+
+rule solve_all_networks:
+    input: expand("results/networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc", **config['scenario'])
+
 
 if config['enable'].get('prepare_links_p_nom', False):
     rule prepare_links_p_nom:
@@ -45,7 +42,6 @@ if config['enable'].get('prepare_links_p_nom', False):
         log: 'logs/prepare_links_p_nom.log'
         threads: 1
         resources: mem=500
-        # group: 'nonfeedin_preparation'
         script: 'scripts/prepare_links_p_nom.py'
 
 
@@ -53,19 +49,24 @@ datafiles = ['ch_cantons.csv', 'je-e-21.03.02.xls',
             'eez/World_EEZ_v8_2014.shp', 'EIA_hydro_generation_2000_2014.csv', 
             'hydro_capacities.csv', 'naturalearth/ne_10m_admin_0_countries.shp', 
             'NUTS_2013_60M_SH/data/NUTS_RG_60M_2013.shp', 'nama_10r_3popgdp.tsv.gz', 
-            'nama_10r_3gdp.tsv.gz', 'time_series_60min_singleindex_filtered.csv', 
-            'corine/g250_clc06_V18_5.tif']
+            'nama_10r_3gdp.tsv.gz', 'corine/g250_clc06_V18_5.tif']
+
 
 if not config.get('tutorial', False):
     datafiles.extend(["natura/Natura2000_end2015.shp", "GEBCO_2014_2D.nc"])
 
+
 if config['enable'].get('retrieve_databundle', True):
     rule retrieve_databundle:
-        output:  expand('data/bundle/{file}', file=datafiles)
+        output: expand('data/bundle/{file}', file=datafiles)
         log: "logs/retrieve_databundle.log"
         script: 'scripts/retrieve_databundle.py'
 
 
+rule build_load_data:
+    output: "resources/load.csv"
+    log: "logs/build_load_data.log"
+    script: 'scripts/build_load_data.py'
 
 rule build_powerplants:
     input:
@@ -75,9 +76,9 @@ rule build_powerplants:
     log: "logs/build_powerplants.log"
     threads: 1
     resources: mem=500
-    # group: 'nonfeedin_preparation'
     script: "scripts/build_powerplants.py"
 
+
 rule base_network:
     input:
         eg_buses='data/entsoegridkit/buses.csv',
@@ -96,9 +97,9 @@ rule base_network:
     benchmark: "benchmarks/base_network"
     threads: 1
     resources: mem=500
-    # group: 'nonfeedin_preparation'
     script: "scripts/base_network.py"
 
+
 rule build_shapes:
     input:
         naturalearth='data/bundle/naturalearth/ne_10m_admin_0_countries.shp',
@@ -116,9 +117,9 @@ rule build_shapes:
     log: "logs/build_shapes.log"
     threads: 1
     resources: mem=500
-    # group: 'nonfeedin_preparation'
     script: "scripts/build_shapes.py"
 
+
 rule build_bus_regions:
     input:
         country_shapes='resources/country_shapes.geojson',
@@ -128,20 +129,21 @@ rule build_bus_regions:
         regions_onshore="resources/regions_onshore.geojson",
         regions_offshore="resources/regions_offshore.geojson"
     log: "logs/build_bus_regions.log"
+    threads: 1
     resources: mem=1000
-    # group: 'nonfeedin_preparation'
     script: "scripts/build_bus_regions.py"
 
-if config['enable'].get('build_cutout', False):        
+
+if config['enable'].get('build_cutout', False):
     rule build_cutout:
         output: directory("cutouts/{cutout}")
         log: "logs/build_cutout/{cutout}.log"
-        resources: mem=config['atlite'].get('nprocesses', 4) * 1000
-        threads: config['atlite'].get('nprocesses', 4)
         benchmark: "benchmarks/build_cutout_{cutout}"
-        # group: 'feedin_preparation'
+        threads: ATLITE_NPROCESSES
+        resources: mem=ATLITE_NPROCESSES * 1000
         script: "scripts/build_cutout.py"
 
+
 if config['enable'].get('retrieve_cutout', True):
     rule retrieve_cutout:
         output: directory(expand("cutouts/{cutouts}", **config['atlite'])),
@@ -149,15 +151,16 @@ if config['enable'].get('retrieve_cutout', True):
         script: 'scripts/retrieve_cutout.py'
 
 
-if config['enable'].get('build_natura_raster', False):        
+if config['enable'].get('build_natura_raster', False):
     rule build_natura_raster:
-        input: 
+        input:
             natura="data/bundle/natura/Natura2000_end2015.shp",
             cutouts=expand("cutouts/{cutouts}", **config['atlite'])
         output: "resources/natura.tiff"
         log: "logs/build_natura_raster.log"
         script: "scripts/build_natura_raster.py"
 
+
 if config['enable'].get('retrieve_natura_raster', True):
     rule retrieve_natura_raster:
         output: "resources/natura.tiff"
@@ -177,23 +180,24 @@ rule build_renewable_profiles:
         base_network="networks/base.nc",
         corine="data/bundle/corine/g250_clc06_V18_5.tif",
         natura="resources/natura.tiff",
-        gebco=lambda wildcards: ("data/bundle/GEBCO_2014_2D.nc"
-                                 if "max_depth" in config["renewable"][wildcards.technology].keys()
-                                 else []),
+        gebco=lambda w: ("data/bundle/GEBCO_2014_2D.nc"
+                         if "max_depth" in config["renewable"][w.technology].keys()
+                         else []),
         country_shapes='resources/country_shapes.geojson',
         offshore_shapes='resources/offshore_shapes.geojson',
-        regions=lambda wildcards: ("resources/regions_onshore.geojson"
-                                   if wildcards.technology in ('onwind', 'solar')
-                                   else "resources/regions_offshore.geojson"),
-        cutout=lambda wildcards: "cutouts/" + config["renewable"][wildcards.technology]['cutout']
-    output: profile="resources/profile_{technology}.nc",
+        regions=lambda w: ("resources/regions_onshore.geojson"
+                           if w.technology in ('onwind', 'solar')
+                           else "resources/regions_offshore.geojson"),
+        cutout=lambda w: "cutouts/" + config["renewable"][w.technology]['cutout']
+    output:
+        profile="resources/profile_{technology}.nc",
     log: "logs/build_renewable_profile_{technology}.log"
-    resources: mem=config['atlite'].get('nprocesses', 2) * 5000
-    threads: config['atlite'].get('nprocesses', 2)
     benchmark: "benchmarks/build_renewable_profiles_{technology}"
-    # group: 'feedin_preparation'
+    threads: ATLITE_NPROCESSES
+    resources: mem=ATLITE_NPROCESSES * 5000
     script: "scripts/build_renewable_profiles.py"
 
+
 if 'hydro' in config['renewable'].keys():
     rule build_hydro_profile:
         input:
@@ -203,9 +207,9 @@ if 'hydro' in config['renewable'].keys():
         output: 'resources/profile_hydro.nc'
         log: "logs/build_hydro_profile.log"
         resources: mem=5000
-        # group: 'feedin_preparation'
         script: 'scripts/build_hydro_profile.py'
 
+
 rule add_electricity:
     input:
         base_network='networks/base.nc',
@@ -214,78 +218,80 @@ rule add_electricity:
         powerplants='resources/powerplants.csv',
         hydro_capacities='data/bundle/hydro_capacities.csv',
         geth_hydro_capacities='data/geth2015_hydro_capacities.csv',
-        opsd_load='data/bundle/time_series_60min_singleindex_filtered.csv',
+        load='resources/load.csv',
         nuts3_shapes='resources/nuts3_shapes.geojson',
-        **{'profile_' + t: "resources/profile_" + t + ".nc"
-           for t in config['renewable']}
+        **{f"profile_{tech}": f"resources/profile_{tech}.nc"
+           for tech in config['renewable']}
     output: "networks/elec.nc"
     log: "logs/add_electricity.log"
     benchmark: "benchmarks/add_electricity"
     threads: 1
     resources: mem=3000
-    # group: 'build_pypsa_networks'
     script: "scripts/add_electricity.py"
 
+
 rule simplify_network:
     input:
-        network='networks/{network}.nc',
+        network='networks/elec.nc',
         tech_costs=COSTS,
         regions_onshore="resources/regions_onshore.geojson",
         regions_offshore="resources/regions_offshore.geojson"
     output:
-        network='networks/{network}_s{simpl}.nc',
-        regions_onshore="resources/regions_onshore_{network}_s{simpl}.geojson",
-        regions_offshore="resources/regions_offshore_{network}_s{simpl}.geojson",
-        clustermaps='resources/clustermaps_{network}_s{simpl}.h5'
-    log: "logs/simplify_network/{network}_s{simpl}.log"
-    benchmark: "benchmarks/simplify_network/{network}_s{simpl}"
+        network='networks/elec_s{simpl}.nc',
+        regions_onshore="resources/regions_onshore_elec_s{simpl}.geojson",
+        regions_offshore="resources/regions_offshore_elec_s{simpl}.geojson",
+        busmap='resources/busmap_elec_s{simpl}.csv'
+    log: "logs/simplify_network/elec_s{simpl}.log"
+    benchmark: "benchmarks/simplify_network/elec_s{simpl}"
     threads: 1
     resources: mem=4000
-    # group: 'build_pypsa_networks'
     script: "scripts/simplify_network.py"
 
+
 rule cluster_network:
     input:
-        network='networks/{network}_s{simpl}.nc',
-        regions_onshore="resources/regions_onshore_{network}_s{simpl}.geojson",
-        regions_offshore="resources/regions_offshore_{network}_s{simpl}.geojson",
-        clustermaps=ancient('resources/clustermaps_{network}_s{simpl}.h5'),
+        network='networks/elec_s{simpl}.nc',
+        regions_onshore="resources/regions_onshore_elec_s{simpl}.geojson",
+        regions_offshore="resources/regions_offshore_elec_s{simpl}.geojson",
+        busmap=ancient('resources/busmap_elec_s{simpl}.csv'),
+        custom_busmap=("data/custom_busmap_elec_s{simpl}_{clusters}.csv"
+                       if config["enable"].get("custom_busmap", False) else []),
         tech_costs=COSTS
     output:
-        network='networks/{network}_s{simpl}_{clusters}.nc',
-        regions_onshore="resources/regions_onshore_{network}_s{simpl}_{clusters}.geojson",
-        regions_offshore="resources/regions_offshore_{network}_s{simpl}_{clusters}.geojson",
-        clustermaps='resources/clustermaps_{network}_s{simpl}_{clusters}.h5'
-    log: "logs/cluster_network/{network}_s{simpl}_{clusters}.log"
-    benchmark: "benchmarks/cluster_network/{network}_s{simpl}_{clusters}"
+        network='networks/elec_s{simpl}_{clusters}.nc',
+        regions_onshore="resources/regions_onshore_elec_s{simpl}_{clusters}.geojson",
+        regions_offshore="resources/regions_offshore_elec_s{simpl}_{clusters}.geojson",
+        busmap="resources/busmap_elec_s{simpl}_{clusters}.csv",
+        linemap="resources/linemap_elec_s{simpl}_{clusters}.csv"
+    log: "logs/cluster_network/elec_s{simpl}_{clusters}.log"
+    benchmark: "benchmarks/cluster_network/elec_s{simpl}_{clusters}"
     threads: 1
     resources: mem=3000
-    # group: 'build_pypsa_networks'
     script: "scripts/cluster_network.py"
 
 
 rule add_extra_components:
     input:
-        network='networks/{network}_s{simpl}_{clusters}.nc',
+        network='networks/elec_s{simpl}_{clusters}.nc',
         tech_costs=COSTS,
-    output: 'networks/{network}_s{simpl}_{clusters}_ec.nc'
-    log: "logs/add_extra_components/{network}_s{simpl}_{clusters}.log"
-    benchmark: "benchmarks/add_extra_components/{network}_s{simpl}_{clusters}_ec"
+    output: 'networks/elec_s{simpl}_{clusters}_ec.nc'
+    log: "logs/add_extra_components/elec_s{simpl}_{clusters}.log"
+    benchmark: "benchmarks/add_extra_components/elec_s{simpl}_{clusters}_ec"
     threads: 1
     resources: mem=3000
-    # group: 'build_pypsa_networks'
     script: "scripts/add_extra_components.py"
 
 
 rule prepare_network:
-    input: 'networks/{network}_s{simpl}_{clusters}_ec.nc', tech_costs=COSTS
-    output: 'networks/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc'
-    log: "logs/prepare_network/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}.log"
+    input: 'networks/elec_s{simpl}_{clusters}_ec.nc', tech_costs=COSTS
+    output: 'networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc'
+    log: "logs/prepare_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.log"
+    benchmark: "benchmarks/prepare_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}"
     threads: 1
-    resources: mem=1000
-    # benchmark: "benchmarks/prepare_network/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}"
+    resources: mem=4000
     script: "scripts/prepare_network.py"
 
+
 def memory(w):
     factor = 3.
     for o in w.opts.split('-'):
@@ -293,52 +299,58 @@ def memory(w):
         if m is not None:
             factor /= int(m.group(1))
             break
+    for o in w.opts.split('-'):
+        m = re.match(r'^(\d+)seg$', o, re.IGNORECASE)
+        if m is not None:
+            factor *= int(m.group(1)) / 8760
+            break
     if w.clusters.endswith('m'):
         return int(factor * (18000 + 180 * int(w.clusters[:-1])))
     else:
         return int(factor * (10000 + 195 * int(w.clusters)))
-        # return 4890+310 * int(w.clusters)
+
 
 rule solve_network:
-    input: "networks/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc"
-    output: "results/networks/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc"
-    shadow: "shallow"
+    input: "networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc"
+    output: "results/networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc"
     log:
-        solver=normpath("logs/solve_network/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}_solver.log"),
-        python="logs/solve_network/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}_python.log",
-        memory="logs/solve_network/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}_memory.log"
-    benchmark: "benchmarks/solve_network/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}"
+        solver=normpath("logs/solve_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_solver.log"),
+        python="logs/solve_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_python.log",
+        memory="logs/solve_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_memory.log"
+    benchmark: "benchmarks/solve_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}"
     threads: 4
     resources: mem=memory
-    # group: "solve" # with group, threads is ignored https://bitbucket.org/snakemake/snakemake/issues/971/group-job-description-does-not-contain
+    shadow: "shallow"
     script: "scripts/solve_network.py"
 
+
 rule solve_operations_network:
     input:
-        unprepared="networks/{network}_s{simpl}_{clusters}_ec.nc",
-        optimized="results/networks/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc"
-    output: "results/networks/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}_op.nc"
-    shadow: "shallow"
+        unprepared="networks/elec_s{simpl}_{clusters}_ec.nc",
+        optimized="results/networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc"
+    output: "results/networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_op.nc"
     log:
-        solver=normpath("logs/solve_operations_network/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}_op_solver.log"),
-        python="logs/solve_operations_network/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}_op_python.log",
-        memory="logs/solve_operations_network/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}_op_memory.log"
-    benchmark: "benchmarks/solve_operations_network/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}"
+        solver=normpath("logs/solve_operations_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_op_solver.log"),
+        python="logs/solve_operations_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_op_python.log",
+        memory="logs/solve_operations_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_op_memory.log"
+    benchmark: "benchmarks/solve_operations_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}"
     threads: 4
     resources: mem=(lambda w: 5000 + 372 * int(w.clusters))
-    # group: "solve_operations"
+    shadow: "shallow"
     script: "scripts/solve_operations_network.py"
 
+
 rule plot_network:
     input:
-        network="results/networks/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc",
+        network="results/networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc",
         tech_costs=COSTS
     output:
-        only_map="results/plots/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}_{attr}.{ext}",
-        ext="results/plots/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}_{attr}_ext.{ext}"
-    log: "logs/plot_network/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}_{attr}_{ext}.log"
+        only_map="results/plots/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{attr}.{ext}",
+        ext="results/plots/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{attr}_ext.{ext}"
+    log: "logs/plot_network/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{attr}_{ext}.log"
     script: "scripts/plot_network.py"
 
+
 def input_make_summary(w):
     # It's mildly hacky to include the separate costs input as first entry
     if w.ll.endswith("all"):
@@ -348,48 +360,54 @@ def input_make_summary(w):
     else:
         ll = w.ll
     return ([COSTS] +
-            expand("results/networks/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc",
+            expand("results/networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc",
                    network=w.network,
                    ll=ll,
                    **{k: config["scenario"][k] if getattr(w, k) == "all" else getattr(w, k)
                       for k in ["simpl", "clusters", "opts"]}))
 
+
 rule make_summary:
     input: input_make_summary
-    output: directory("results/summaries/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}_{country}")
-    log: "logs/make_summary/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}_{country}.log",
+    output: directory("results/summaries/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{country}")
+    log: "logs/make_summary/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{country}.log",
     script: "scripts/make_summary.py"
 
+
 rule plot_summary:
-    input: "results/summaries/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}_{country}"
-    output: "results/plots/summary_{summary}_{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}_{country}.{ext}"
-    log: "logs/plot_summary/{summary}_{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}_{country}_{ext}.log"
+    input: "results/summaries/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{country}"
+    output: "results/plots/summary_{summary}_elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{country}.{ext}"
+    log: "logs/plot_summary/{summary}_elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{country}_{ext}.log"
     script: "scripts/plot_summary.py"
 
-def input_plot_p_nom_max(wildcards):
-    return [('networks/{network}_s{simpl}{maybe_cluster}.nc'
-             .format(maybe_cluster=('' if c == 'full' else ('_' + c)), **wildcards))
-            for c in wildcards.clusts.split(",")]
+
+def input_plot_p_nom_max(w):
+    return [("networks/elec_s{simpl}{maybe_cluster}.nc"
+             .format(maybe_cluster=('' if c == 'full' else ('_' + c)), **w))
+            for c in w.clusts.split(",")]
+
+
 rule plot_p_nom_max:
     input: input_plot_p_nom_max
-    output: "results/plots/{network}_s{simpl}_cum_p_nom_max_{clusts}_{techs}_{country}.{ext}"
-    log: "logs/plot_p_nom_max/{network}_s{simpl}_{clusts}_{techs}_{country}_{ext}.log"
+    output: "results/plots/elec_s{simpl}_cum_p_nom_max_{clusts}_{techs}_{country}.{ext}"
+    log: "logs/plot_p_nom_max/elec_s{simpl}_{clusts}_{techs}_{country}_{ext}.log"
     script: "scripts/plot_p_nom_max.py"
 
+
 rule build_country_flh:
     input:
         base_network="networks/base.nc",
         corine="data/bundle/corine/g250_clc06_V18_5.tif",
         natura="resources/natura.tiff",
-        gebco=lambda wildcards: ("data/bundle/GEBCO_2014_2D.nc"
-                                 if "max_depth" in config["renewable"][wildcards.technology].keys()
-                                 else []),
+        gebco=lambda w: ("data/bundle/GEBCO_2014_2D.nc"
+                         if "max_depth" in config["renewable"][w.technology].keys()
+                         else []),
         country_shapes='resources/country_shapes.geojson',
         offshore_shapes='resources/offshore_shapes.geojson',
         pietzker="data/pietzker2014.xlsx",
         regions=lambda w: ("resources/country_shapes.geojson"
-                                   if w.technology in ('onwind', 'solar')
-                                   else "resources/offshore_shapes.geojson"),
+                           if w.technology in ('onwind', 'solar')
+                           else "resources/offshore_shapes.geojson"),
         cutout=lambda w: "cutouts/" + config["renewable"][w.technology]['cutout']
     output:
         area="resources/country_flh_area_{technology}.csv",
@@ -400,9 +418,4 @@ rule build_country_flh:
     log: "logs/build_country_flh_{technology}.log"
     resources: mem=10000
     benchmark: "benchmarks/build_country_flh_{technology}"
-    # group: 'feedin_preparation'
     script: "scripts/build_country_flh.py"
-
-# Local Variables:
-# mode: python
-# End:

cluster.yaml

@@ -1,22 +0,0 @@
-# SPDX-FileCopyrightText: : 2017-2020 The PyPSA-Eur Authors
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-__default__:
-  log: "logs/cluster/{{name}}.log"
-
-feedin_preparation:
-  walltime: "12:00:00"
-
-solve_network:
-  walltime: "05:00:00:00"
-
-trace_solve_network:
-  walltime: "05:00:00:00"
-
-solve:
-  walltime: "05:00:00:00"
-  threads: 4 # Group threads are not aggregated
-
-solve_operations:
-  walltime: "01:00:00:00"

config.default.yaml

@@ -2,7 +2,7 @@
 #
 # SPDX-License-Identifier: CC0-1.0
 
-version: 0.2.0
+version: 0.3.0
 tutorial: false
 
 logging:
@@ -12,7 +12,6 @@ logging:
 summary_dir: results
 
 scenario:
-  sectors: [E]
   simpl: ['']
   ll: ['copt']
   clusters: [37, 128, 256, 512, 1024]
@@ -33,17 +32,18 @@ enable:
   retrieve_cutout: true
   build_natura_raster: false
   retrieve_natura_raster: true
+  custom_busmap: false
 
 electricity:
   voltages: [220., 300., 380.]
   co2limit: 7.75e+7 # 0.05 * 3.1e9*0.5
-  co2base: 3.1e+9 # 1 * 3.1e9*0.5
+  co2base: 1.487e9
   agg_p_nom_limits: data/agg_p_nom_minmax.csv
 
   extendable_carriers:
     Generator: []
-    StorageUnit: [battery, H2]
-    Store: [] # battery, H2
+    StorageUnit: [] # battery, H2
+    Store: [battery, H2]
     Link: []
 
   max_hours:
@@ -53,6 +53,7 @@ electricity:
   powerplants_filter: false # use pandas query strings here, e.g. Country not in ['Germany']
   custom_powerplants: false # use pandas query strings here, e.g. Country in ['Germany']
   conventional_carriers: [nuclear, oil, OCGT, CCGT, coal, lignite, geothermal, biomass]
+  renewable_capacities_from_OPSD: [] # onwind, offwind, solar
 
   # estimate_renewable_capacities_from_capacity_stats:
   #   # Wind is the Fueltype in ppm.data.Capacity_stats, onwind, offwind-{ac,dc} the carrier in PyPSA-Eur
@@ -143,8 +144,7 @@ renewable:
     cutout: europe-2013-era5
     carriers: [ror, PHS, hydro]
     PHS_max_hours: 6
-    hydro_max_hours: "energy_capacity_totals_by_country" # one of energy_capacity_totals_by_country,
-                                                         # estimate_by_large_installations or a float
+    hydro_max_hours: "energy_capacity_totals_by_country" # one of energy_capacity_totals_by_country, estimate_by_large_installations or a float
     clip_min_inflow: 1.0
 
 lines:
@@ -153,11 +153,13 @@ lines:
     300.: "Al/St 240/40 3-bundle 300.0"
     380.: "Al/St 240/40 4-bundle 380.0"
   s_max_pu: 0.7
+  s_nom_max: .inf
   length_factor: 1.25
   under_construction: 'zero' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity
 
 links:
   p_max_pu: 1.0
+  p_nom_max: .inf
   include_tyndp: true
   under_construction: 'zero' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity
 
@@ -167,6 +169,11 @@ transformers:
   type: ''
 
 load:
+  url: https://data.open-power-system-data.org/time_series/2019-06-05/time_series_60min_singleindex.csv
+  power_statistics: True # only for files from <2019; set false in order to get ENTSOE transparency data 
+  interpolate_limit: 3 # data gaps up until this size are interpolated linearly
+  time_shift_for_large_gaps: 1w # data gaps up until this size are copied by copying from 
+  manual_adjustments: true # false
   scaling_factor: 1.0
 
 costs:
@@ -188,7 +195,10 @@ costs:
     offwind: 0.015
     hydro: 0.
     H2: 0.
+    electrolysis: 0.
+    fuel cell: 0.
     battery: 0.
+    battery inverter: 0.
   emission_prices: # in currency per tonne emission, only used with the option Ep
     co2: 0.
 
@@ -267,67 +277,18 @@ plotting:
     'waste' : '#68896b'
     'geothermal' : '#ba91b1'
     "OCGT" : "#d35050"
-    "OCGT marginal" : "#d35050"
-    "OCGT-heat" : "#d35050"
-    "gas boiler" : "#d35050"
-    "gas boilers" : "#d35050"
-    "gas boiler marginal" : "#d35050"
-    "gas-to-power/heat" : "#d35050"
     "gas" : "#d35050"
     "natural gas" : "#d35050"
     "CCGT" : "#b20101"
-    "CCGT marginal" : "#b20101"
-    "Nuclear" : "#ff9000"
-    "Nuclear marginal" : "#ff9000"
     "nuclear" : "#ff9000"
     "coal" : "#707070"
-    "Coal" : "#707070"
-    "Coal marginal" : "#707070"
     "lignite" : "#9e5a01"
-    "Lignite" : "#9e5a01"
-    "Lignite marginal" : "#9e5a01"
-    "Oil" : "#262626"
     "oil" : "#262626"
     "H2" : "#ea048a"
     "hydrogen storage" : "#ea048a"
-    "Sabatier" : "#a31597"
-    "methanation" : "#a31597"
-    "helmeth" : "#a31597"
-    "DAC" : "#d284ff"
-    "co2 stored" : "#e5e5e5"
-    "CO2 sequestration" : "#e5e5e5"
     "battery" : "#b8ea04"
-    "battery storage" : "#b8ea04"
-    "Li ion" : "#b8ea04"
-    "BEV charger" : "#e2ff7c"
-    "V2G" : "#7a9618"
-    "transport fuel cell" : "#e884be"
-    "retrofitting" : "#e0d6a8"
-    "building retrofitting" : "#e0d6a8"
-    "heat pumps" : "#ff9768"
-    "heat pump" : "#ff9768"
-    "air heat pump" : "#ffbea0"
-    "ground heat pump" : "#ff7a3d"
-    "power-to-heat" : "#a59e7c"
-    "power-to-gas" : "#db8585"
-    "power-to-liquid" : "#a9acd1"
-    "Fischer-Tropsch" : "#a9acd1"
-    "resistive heater" : "#aa4925"
-    "water tanks" : "#401f75"
-    "hot water storage" : "#401f75"
-    "hot water charging" : "#351c5e"
-    "hot water discharging" : "#683ab2"
-    "CHP" : "#d80a56"
-    "CHP heat" : "#d80a56"
-    "CHP electric" : "#d80a56"
-    "district heating" : "#93864b"
-    "Ambient" : "#262626"
     "Electric load" : "#f9d002"
     "electricity" : "#f9d002"
-    "Heat load" : "#d35050"
-    "heat" : "#d35050"
-    "Transport load" : "#235ebc"
-    "transport" : "#235ebc"
     "lines" : "#70af1d"
     "transmission lines" : "#70af1d"
     "AC-AC" : "#70af1d"
@@ -347,18 +308,5 @@ plotting:
     hydro: "Reservoir & Dam"
     battery: "Battery Storage"
     H2: "Hydrogen Storage"
-    lines: "Transmission lines"
-    ror: "Run of river"
-  nice_names_n:
-    OCGT: "Open-Cycle\nGas"
-    CCGT: "Combined-Cycle\nGas"
-    offwind-ac: "Offshore\nWind (AC)"
-    offwind-dc: "Offshore\nWind (DC)"
-    onwind: "Onshore\nWind"
-    battery: "Battery\nStorage"
-    H2: "Hydrogen\nStorage"
-    lines: "Transmission\nlines"
-    ror: "Run of\nriver"
-    PHS: "Pumped Hydro\nStorage"
-    hydro: "Reservoir\n& Dam"
-
+    lines: "Transmission Lines"
+    ror: "Run of River"

config.tutorial.yaml

@@ -2,8 +2,9 @@
 #
 # SPDX-License-Identifier: CC0-1.0
 
-version: 0.2.0
+version: 0.3.0
 tutorial: true
+
 logging:
   level: INFO
   format: '%(levelname)s:%(name)s:%(message)s'
@@ -11,7 +12,6 @@ logging:
 summary_dir: results
 
 scenario:
-  sectors: [E]
   simpl: ['']
   ll: ['copt']
   clusters: [5]
@@ -32,6 +32,7 @@ enable:
   retrieve_cutout: true
   build_natura_raster: false
   retrieve_natura_raster: true
+  custom_busmap: false
 
 electricity:
   voltages: [220., 300., 380.]
@@ -39,8 +40,8 @@ electricity:
 
   extendable_carriers:
     Generator: [OCGT]
-    StorageUnit: [battery, H2]
-    Store: [] #battery, H2
+    StorageUnit: [] #battery, H2
+    Store: [battery, H2]
     Link: []
 
   max_hours:
@@ -131,11 +132,13 @@ lines:
     300.: "Al/St 240/40 3-bundle 300.0"
     380.: "Al/St 240/40 4-bundle 380.0"
   s_max_pu: 0.7
+  s_nom_max: .inf
   length_factor: 1.25
   under_construction: 'zero' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity
 
 links:
   p_max_pu: 1.0
+  p_nom_max: .inf
   include_tyndp: true
   under_construction: 'zero' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity
 
@@ -145,6 +148,11 @@ transformers:
   type: ''
 
 load:
+  url: https://data.open-power-system-data.org/time_series/2019-06-05/time_series_60min_singleindex.csv
+  power_statistics: True # only for files from <2019; set false in order to get ENTSOE transparency data 
+  interpolate_limit: 3 # data gaps up until this size are interpolated linearly
+  time_shift_for_large_gaps: 1w # data gaps up until this size are copied by copying from 
+  manual_adjustments: true # false
   scaling_factor: 1.0
 
 costs:
@@ -179,26 +187,8 @@ solving:
     clip_p_max_pu: 0.01
     skip_iterations: false
     track_iterations: false
-    #nhours: 10
   solver:
     name: cbc
-  # solver:
-    # name: gurobi
-    # threads: 4
-    # method: 2 # barrier
-    # crossover: 0
-    # BarConvTol: 1.e-5
-    # FeasibilityTol: 1.e-6
-    # AggFill: 0
-    # PreDual: 0
-    # GURO_PAR_BARDENSETHRESH: 200
-  # solver:
-  #   name: cplex
-  #   threads: 4
-  #   lpmethod: 4 # barrier
-  #   solutiontype: 2 # non basic solution, ie no crossover
-  #   barrier_convergetol: 1.e-5
-  #   feasopt_tolerance: 1.e-6
 
 plotting:
   map:
@@ -246,67 +236,18 @@ plotting:
     'waste' : '#68896b'
     'geothermal' : '#ba91b1'
     "OCGT" : "#d35050"
-    "OCGT marginal" : "#d35050"
-    "OCGT-heat" : "#d35050"
-    "gas boiler" : "#d35050"
-    "gas boilers" : "#d35050"
-    "gas boiler marginal" : "#d35050"
-    "gas-to-power/heat" : "#d35050"
     "gas" : "#d35050"
     "natural gas" : "#d35050"
     "CCGT" : "#b20101"
-    "CCGT marginal" : "#b20101"
-    "Nuclear" : "#ff9000"
-    "Nuclear marginal" : "#ff9000"
     "nuclear" : "#ff9000"
     "coal" : "#707070"
-    "Coal" : "#707070"
-    "Coal marginal" : "#707070"
     "lignite" : "#9e5a01"
-    "Lignite" : "#9e5a01"
-    "Lignite marginal" : "#9e5a01"
-    "Oil" : "#262626"
     "oil" : "#262626"
     "H2" : "#ea048a"
     "hydrogen storage" : "#ea048a"
-    "Sabatier" : "#a31597"
-    "methanation" : "#a31597"
-    "helmeth" : "#a31597"
-    "DAC" : "#d284ff"
-    "co2 stored" : "#e5e5e5"
-    "CO2 sequestration" : "#e5e5e5"
     "battery" : "#b8ea04"
-    "battery storage" : "#b8ea04"
-    "Li ion" : "#b8ea04"
-    "BEV charger" : "#e2ff7c"
-    "V2G" : "#7a9618"
-    "transport fuel cell" : "#e884be"
-    "retrofitting" : "#e0d6a8"
-    "building retrofitting" : "#e0d6a8"
-    "heat pumps" : "#ff9768"
-    "heat pump" : "#ff9768"
-    "air heat pump" : "#ffbea0"
-    "ground heat pump" : "#ff7a3d"
-    "power-to-heat" : "#a59e7c"
-    "power-to-gas" : "#db8585"
-    "power-to-liquid" : "#a9acd1"
-    "Fischer-Tropsch" : "#a9acd1"
-    "resistive heater" : "#aa4925"
-    "water tanks" : "#401f75"
-    "hot water storage" : "#401f75"
-    "hot water charging" : "#351c5e"
-    "hot water discharging" : "#683ab2"
-    "CHP" : "#d80a56"
-    "CHP heat" : "#d80a56"
-    "CHP electric" : "#d80a56"
-    "district heating" : "#93864b"
-    "Ambient" : "#262626"
     "Electric load" : "#f9d002"
     "electricity" : "#f9d002"
-    "Heat load" : "#d35050"
-    "heat" : "#d35050"
-    "Transport load" : "#235ebc"
-    "transport" : "#235ebc"
     "lines" : "#70af1d"
     "transmission lines" : "#70af1d"
     "AC-AC" : "#70af1d"
@@ -326,17 +267,5 @@ plotting:
     hydro: "Reservoir & Dam"
     battery: "Battery Storage"
     H2: "Hydrogen Storage"
-    lines: "Transmission lines"
-    ror: "Run of river"
-  nice_names_n:
-    OCGT: "Open-Cycle\nGas"
-    CCGT: "Combined-Cycle\nGas"
-    offwind-ac: "Offshore\nWind (AC)"
-    offwind-dc: "Offshore\nWind (DC)"
-    onwind: "Onshore\nWind"
-    battery: "Battery\nStorage"
-    H2: "Hydrogen\nStorage"
-    lines: "Transmission\nlines"
-    ror: "Run of\nriver"
-    PHS: "Pumped Hydro\nStorage"
-    hydro: "Reservoir\n& Dam"
+    lines: "Transmission Lines"
+    ror: "Run of River"

data/costs.csv

@@ -0,0 +1,195 @@
+technology,year,parameter,value,unit,source
+solar-rooftop,2030,discount rate,0.04,per unit,standard for decentral
+onwind,2030,lifetime,30,years,DEA https://ens.dk/en/our-services/projections-and-models/technology-data
+offwind,2030,lifetime,30,years,DEA https://ens.dk/en/our-services/projections-and-models/technology-data
+solar,2030,lifetime,25,years,IEA2010
+solar-rooftop,2030,lifetime,25,years,IEA2010
+solar-utility,2030,lifetime,25,years,IEA2010
+PHS,2030,lifetime,80,years,IEA2010
+hydro,2030,lifetime,80,years,IEA2010
+ror,2030,lifetime,80,years,IEA2010
+OCGT,2030,lifetime,30,years,IEA2010
+nuclear,2030,lifetime,45,years,ECF2010 in DIW DataDoc http://hdl.handle.net/10419/80348
+CCGT,2030,lifetime,30,years,IEA2010
+coal,2030,lifetime,40,years,IEA2010
+lignite,2030,lifetime,40,years,IEA2010
+geothermal,2030,lifetime,40,years,IEA2010
+biomass,2030,lifetime,30,years,ECF2010 in DIW DataDoc http://hdl.handle.net/10419/80348
+oil,2030,lifetime,30,years,ECF2010 in DIW DataDoc http://hdl.handle.net/10419/80348
+onwind,2030,investment,1040,EUR/kWel,DEA https://ens.dk/en/our-services/projections-and-models/technology-data
+offwind,2030,investment,1640,EUR/kWel,DEA https://ens.dk/en/our-services/projections-and-models/technology-data
+offwind-ac-station,2030,investment,250,EUR/kWel,DEA https://ens.dk/en/our-services/projections-and-models/technology-data
+offwind-ac-connection-submarine,2030,investment,2685,EUR/MW/km,DEA https://ens.dk/en/our-services/projections-and-models/technology-data
+offwind-ac-connection-underground,2030,investment,1342,EUR/MW/km,DEA https://ens.dk/en/our-services/projections-and-models/technology-data
+offwind-dc-station,2030,investment,400,EUR/kWel,Haertel 2017; assuming one onshore and one offshore node + 13% learning reduction
+offwind-dc-connection-submarine,2030,investment,2000,EUR/MW/km,DTU report based on Fig 34 of https://ec.europa.eu/energy/sites/ener/files/documents/2014_nsog_report.pdf
+offwind-dc-connection-underground,2030,investment,1000,EUR/MW/km,Haertel 2017; average + 13% learning reduction
+solar,2030,investment,600,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348
+biomass,2030,investment,2209,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348
+geothermal,2030,investment,3392,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348
+coal,2030,investment,1300,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348 PC (Advanced/SuperC)
+lignite,2030,investment,1500,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348
+solar-rooftop,2030,investment,725,EUR/kWel,ETIP PV
+solar-utility,2030,investment,425,EUR/kWel,ETIP PV
+PHS,2030,investment,2000,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348
+hydro,2030,investment,2000,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348
+ror,2030,investment,3000,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348
+OCGT,2030,investment,400,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348
+nuclear,2030,investment,6000,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348
+CCGT,2030,investment,800,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348
+oil,2030,investment,400,EUR/kWel,DIW DataDoc http://hdl.handle.net/10419/80348
+onwind,2030,FOM,2.450549,%/year,DEA https://ens.dk/en/our-services/projections-and-models/technology-data
+offwind,2030,FOM,2.304878,%/year,DEA https://ens.dk/en/our-services/projections-and-models/technology-data
+solar,2030,FOM,4.166667,%/year,DIW DataDoc http://hdl.handle.net/10419/80348
+solar-rooftop,2030,FOM,2,%/year,ETIP PV
+solar-utility,2030,FOM,3,%/year,ETIP PV
+biomass,2030,FOM,4.526935,%/year,DIW DataDoc http://hdl.handle.net/10419/80348
+geothermal,2030,FOM,2.358491,%/year,DIW DataDoc http://hdl.handle.net/10419/80348
+coal,2030,FOM,1.923076,%/year,DIW DataDoc http://hdl.handle.net/10419/80348 PC (Advanced/SuperC)
+lignite,2030,FOM,2.0,%/year,DIW DataDoc http://hdl.handle.net/10419/80348 PC (Advanced/SuperC)
+oil,2030,FOM,1.5,%/year,DIW DataDoc http://hdl.handle.net/10419/80348
+PHS,2030,FOM,1,%/year,DIW DataDoc http://hdl.handle.net/10419/80348
+hydro,2030,FOM,1,%/year,DIW DataDoc http://hdl.handle.net/10419/80348
+ror,2030,FOM,2,%/year,DIW DataDoc http://hdl.handle.net/10419/80348
+CCGT,2030,FOM,2.5,%/year,DIW DataDoc http://hdl.handle.net/10419/80348
+OCGT,2030,FOM,3.75,%/year,DIW DataDoc http://hdl.handle.net/10419/80348
+onwind,2030,VOM,2.3,EUR/MWhel,DEA https://ens.dk/en/our-services/projections-and-models/technology-data
+offwind,2030,VOM,2.7,EUR/MWhel,DEA https://ens.dk/en/our-services/projections-and-models/technology-data
+solar,2030,VOM,0.01,EUR/MWhel,RES costs made up to fix curtailment order
+coal,2030,VOM,6,EUR/MWhel,DIW DataDoc http://hdl.handle.net/10419/80348 PC (Advanced/SuperC)
+lignite,2030,VOM,7,EUR/MWhel,DIW DataDoc http://hdl.handle.net/10419/80348
+CCGT,2030,VOM,4,EUR/MWhel,DIW DataDoc http://hdl.handle.net/10419/80348
+OCGT,2030,VOM,3,EUR/MWhel,DIW DataDoc http://hdl.handle.net/10419/80348
+nuclear,2030,VOM,8,EUR/MWhel,DIW DataDoc http://hdl.handle.net/10419/80348
+gas,2030,fuel,21.6,EUR/MWhth,IEA2011b
+uranium,2030,fuel,3,EUR/MWhth,DIW DataDoc http://hdl.handle.net/10419/80348
+oil,2030,VOM,3,EUR/MWhel,DIW DataDoc http://hdl.handle.net/10419/80348
+nuclear,2030,fuel,3,EUR/MWhth,IEA2011b
+biomass,2030,fuel,7,EUR/MWhth,IEA2011b
+coal,2030,fuel,8.4,EUR/MWhth,IEA2011b
+lignite,2030,fuel,2.9,EUR/MWhth,IEA2011b
+oil,2030,fuel,50,EUR/MWhth,IEA WEM2017 97USD/boe = http://www.iea.org/media/weowebsite/2017/WEM_Documentation_WEO2017.pdf
+PHS,2030,efficiency,0.75,per unit,DIW DataDoc http://hdl.handle.net/10419/80348
+hydro,2030,efficiency,0.9,per unit,DIW DataDoc http://hdl.handle.net/10419/80348
+ror,2030,efficiency,0.9,per unit,DIW DataDoc http://hdl.handle.net/10419/80348
+OCGT,2030,efficiency,0.39,per unit,DIW DataDoc http://hdl.handle.net/10419/80348
+CCGT,2030,efficiency,0.5,per unit,DIW DataDoc http://hdl.handle.net/10419/80348
+biomass,2030,efficiency,0.468,per unit,DIW DataDoc http://hdl.handle.net/10419/80348
+geothermal,2030,efficiency,0.239,per unit,DIW DataDoc http://hdl.handle.net/10419/80348
+nuclear,2030,efficiency,0.337,per unit,DIW DataDoc http://hdl.handle.net/10419/80348
+gas,2030,CO2 intensity,0.187,tCO2/MWth,https://www.eia.gov/environment/emissions/co2_vol_mass.php
+coal,2030,efficiency,0.464,per unit,DIW DataDoc http://hdl.handle.net/10419/80348 PC (Advanced/SuperC)
+lignite,2030,efficiency,0.447,per unit,DIW DataDoc http://hdl.handle.net/10419/80348
+oil,2030,efficiency,0.393,per unit,DIW DataDoc http://hdl.handle.net/10419/80348 CT
+coal,2030,CO2 intensity,0.354,tCO2/MWth,https://www.eia.gov/environment/emissions/co2_vol_mass.php
+lignite,2030,CO2 intensity,0.334,tCO2/MWth,https://www.eia.gov/environment/emissions/co2_vol_mass.php
+oil,2030,CO2 intensity,0.248,tCO2/MWth,https://www.eia.gov/environment/emissions/co2_vol_mass.php
+geothermal,2030,CO2 intensity,0.026,tCO2/MWth,https://www.eia.gov/environment/emissions/co2_vol_mass.php
+electrolysis,2030,investment,350,EUR/kWel,Palzer Thesis
+electrolysis,2030,FOM,4,%/year,NREL http://www.nrel.gov/docs/fy09osti/45873.pdf; budischak2013
+electrolysis,2030,lifetime,18,years,NREL http://www.nrel.gov/docs/fy09osti/45873.pdf; budischak2013
+electrolysis,2030,efficiency,0.8,per unit,NREL http://www.nrel.gov/docs/fy09osti/45873.pdf; budischak2013
+fuel cell,2030,investment,339,EUR/kWel,NREL http://www.nrel.gov/docs/fy09osti/45873.pdf; budischak2013
+fuel cell,2030,FOM,3,%/year,NREL http://www.nrel.gov/docs/fy09osti/45873.pdf; budischak2013
+fuel cell,2030,lifetime,20,years,NREL http://www.nrel.gov/docs/fy09osti/45873.pdf; budischak2013
+fuel cell,2030,efficiency,0.58,per unit,NREL http://www.nrel.gov/docs/fy09osti/45873.pdf; budischak2013 conservative 2020
+hydrogen storage,2030,investment,11.2,USD/kWh,budischak2013
+hydrogen storage,2030,lifetime,20,years,budischak2013
+hydrogen underground storage,2030,investment,0.5,EUR/kWh,maximum from https://www.nrel.gov/docs/fy10osti/46719.pdf
+hydrogen underground storage,2030,lifetime,40,years,http://www.acatech.de/fileadmin/user_upload/Baumstruktur_nach_Website/Acatech/root/de/Publikationen/Materialien/ESYS_Technologiesteckbrief_Energiespeicher.pdf
+H2 pipeline,2030,investment,267,EUR/MW/km,Welder et al https://doi.org/10.1016/j.ijhydene.2018.12.156
+H2 pipeline,2030,lifetime,40,years,Krieg2012 http://juser.fz-juelich.de/record/136392/files/Energie%26Umwelt_144.pdf
+H2 pipeline,2030,FOM,5,%/year,Krieg2012 http://juser.fz-juelich.de/record/136392/files/Energie%26Umwelt_144.pdf
+H2 pipeline,2030,efficiency,0.98,per unit,Krieg2012 http://juser.fz-juelich.de/record/136392/files/Energie%26Umwelt_144.pdf
+methanation,2030,investment,1000,EUR/kWH2,Schaber thesis
+methanation,2030,lifetime,25,years,Schaber thesis
+methanation,2030,FOM,3,%/year,Schaber thesis
+methanation,2030,efficiency,0.6,per unit,Palzer; Breyer for DAC
+helmeth,2030,investment,1000,EUR/kW,no source
+helmeth,2030,lifetime,25,years,no source
+helmeth,2030,FOM,3,%/year,no source
+helmeth,2030,efficiency,0.8,per unit,HELMETH press release
+DAC,2030,investment,250,EUR/(tCO2/a),Fasihi/Climeworks
+DAC,2030,lifetime,30,years,Fasihi
+DAC,2030,FOM,4,%/year,Fasihi
+battery inverter,2030,investment,411,USD/kWel,budischak2013
+battery inverter,2030,lifetime,20,years,budischak2013
+battery inverter,2030,efficiency,0.9,per unit charge/discharge,budischak2013; Lund and Kempton (2008) http://dx.doi.org/10.1016/j.enpol.2008.06.007
+battery inverter,2030,FOM,3,%/year,budischak2013
+battery storage,2030,investment,192,USD/kWh,budischak2013
+battery storage,2030,lifetime,15,years,budischak2013
+decentral air-sourced heat pump,2030,investment,1050,EUR/kWth,HP; Palzer thesis
+decentral air-sourced heat pump,2030,lifetime,20,years,HP; Palzer thesis
+decentral air-sourced heat pump,2030,FOM,3.5,%/year,Palzer thesis
+decentral air-sourced heat pump,2030,efficiency,3,per unit,default for costs
+decentral air-sourced heat pump,2030,discount rate,0.04,per unit,Palzer thesis
+decentral ground-sourced heat pump,2030,investment,1400,EUR/kWth,Palzer thesis
+decentral ground-sourced heat pump,2030,lifetime,20,years,Palzer thesis
+decentral ground-sourced heat pump,2030,FOM,3.5,%/year,Palzer thesis
+decentral ground-sourced heat pump,2030,efficiency,4,per unit,default for costs
+decentral ground-sourced heat pump,2030,discount rate,0.04,per unit,Palzer thesis
+central air-sourced heat pump,2030,investment,700,EUR/kWth,Palzer thesis
+central air-sourced heat pump,2030,lifetime,20,years,Palzer thesis
+central air-sourced heat pump,2030,FOM,3.5,%/year,Palzer thesis
+central air-sourced heat pump,2030,efficiency,3,per unit,default for costs
+retrofitting I,2030,discount rate,0.04,per unit,Palzer thesis
+retrofitting I,2030,lifetime,50,years,Palzer thesis
+retrofitting I,2030,FOM,1,%/year,Palzer thesis
+retrofitting I,2030,investment,50,EUR/m2/fraction reduction,Palzer thesis
+retrofitting II,2030,discount rate,0.04,per unit,Palzer thesis
+retrofitting II,2030,lifetime,50,years,Palzer thesis
+retrofitting II,2030,FOM,1,%/year,Palzer thesis
+retrofitting II,2030,investment,250,EUR/m2/fraction reduction,Palzer thesis
+water tank charger,2030,efficiency,0.9,per unit,HP
+water tank discharger,2030,efficiency,0.9,per unit,HP
+decentral water tank storage,2030,investment,860,EUR/m3,IWES Interaktion
+decentral water tank storage,2030,FOM,1,%/year,HP
+decentral water tank storage,2030,lifetime,20,years,HP
+decentral water tank storage,2030,discount rate,0.04,per unit,Palzer thesis
+central water tank storage,2030,investment,30,EUR/m3,IWES Interaktion
+central water tank storage,2030,FOM,1,%/year,HP
+central water tank storage,2030,lifetime,40,years,HP
+decentral resistive heater,2030,investment,100,EUR/kWhth,Schaber thesis
+decentral resistive heater,2030,lifetime,20,years,Schaber thesis
+decentral resistive heater,2030,FOM,2,%/year,Schaber thesis
+decentral resistive heater,2030,efficiency,0.9,per unit,Schaber thesis
+decentral resistive heater,2030,discount rate,0.04,per unit,Palzer thesis
+central resistive heater,2030,investment,100,EUR/kWhth,Schaber thesis
+central resistive heater,2030,lifetime,20,years,Schaber thesis
+central resistive heater,2030,FOM,2,%/year,Schaber thesis
+central resistive heater,2030,efficiency,0.9,per unit,Schaber thesis
+decentral gas boiler,2030,investment,175,EUR/kWhth,Palzer thesis
+decentral gas boiler,2030,lifetime,20,years,Palzer thesis
+decentral gas boiler,2030,FOM,2,%/year,Palzer thesis
+decentral gas boiler,2030,efficiency,0.9,per unit,Palzer thesis
+decentral gas boiler,2030,discount rate,0.04,per unit,Palzer thesis
+central gas boiler,2030,investment,63,EUR/kWhth,Palzer thesis
+central gas boiler,2030,lifetime,22,years,Palzer thesis
+central gas boiler,2030,FOM,1,%/year,Palzer thesis
+central gas boiler,2030,efficiency,0.9,per unit,Palzer thesis
+decentral CHP,2030,lifetime,25,years,HP
+decentral CHP,2030,investment,1400,EUR/kWel,HP
+decentral CHP,2030,FOM,3,%/year,HP
+decentral CHP,2030,discount rate,0.04,per unit,Palzer thesis
+central CHP,2030,lifetime,25,years,HP
+central CHP,2030,investment,650,EUR/kWel,HP
+central CHP,2030,FOM,3,%/year,HP
+decentral solar thermal,2030,discount rate,0.04,per unit,Palzer thesis
+decentral solar thermal,2030,FOM,1.3,%/year,HP
+decentral solar thermal,2030,investment,270000,EUR/1000m2,HP
+decentral solar thermal,2030,lifetime,20,years,HP
+central solar thermal,2030,FOM,1.4,%/year,HP
+central solar thermal,2030,investment,140000,EUR/1000m2,HP
+central solar thermal,2030,lifetime,20,years,HP
+HVAC overhead,2030,investment,400,EUR/MW/km,Hagspiel
+HVAC overhead,2030,lifetime,40,years,Hagspiel
+HVAC overhead,2030,FOM,2,%/year,Hagspiel
+HVDC overhead,2030,investment,400,EUR/MW/km,Hagspiel
+HVDC overhead,2030,lifetime,40,years,Hagspiel
+HVDC overhead,2030,FOM,2,%/year,Hagspiel
+HVDC submarine,2030,investment,2000,EUR/MW/km,DTU report based on Fig 34 of https://ec.europa.eu/energy/sites/ener/files/documents/2014_nsog_report.pdf
+HVDC submarine,2030,lifetime,40,years,Hagspiel
+HVDC submarine,2030,FOM,2,%/year,Hagspiel
+HVDC inverter pair,2030,investment,150000,EUR/MW,Hagspiel
+HVDC inverter pair,2030,lifetime,40,years,Hagspiel
+HVDC inverter pair,2030,FOM,2,%/year,Hagspiel

data/links_tyndp.csv

@@ -6,8 +6,8 @@ Italy-Montenegro,Villanova (IT),Latsva (MT),445,,1200,under construction,Link.14
 NordLink,Tonstad (NO),Wilster (DE),514,,1400,under construction,,https://tyndp.entsoe.eu/tyndp2018/projects/projects/37,6.716948,58.662631,9.373979,53.922479
 COBRA cable,Endrup (DK),Eemshaven (NL),325,,700,under construction,,https://tyndp.entsoe.eu/tyndp2018/projects/projects/71,8.718392,55.523115,6.835494,53.438589
 Thames Estuary Cluster (NEMO-Link),Richborough (GB),Gezelle (BE),140,,1000,under construction,,https://tyndp.entsoe.eu/tyndp2018/projects/projects/74,1.324854,51.295891,3.23043,51.24902
-Anglo-Scottish -1,Hunterston (UK),Deeside (UK),422,,2400,under construction,,https://tyndp.entsoe.eu/tyndp2018/projects/projects/77,-4.898329,55.723331,-3.032972,53.199735
-ALEGrO,Lixhe (BE),Oberzier (DE),100,,1000,in permitting,,https://tyndp.entsoe.eu/tyndp2018/projects/projects/92,5.67933,50.7567965,6.474704,50.867532
+Anglo-Scottish -1,Hunterston (UK),Deeside (UK),422,,2400,built,,https://tyndp.entsoe.eu/tyndp2018/projects/projects/77,-4.898329,55.723331,-3.032972,53.199735
+ALEGrO,Lixhe (BE),Oberzier (DE),100,,1000,built,,https://tyndp.entsoe.eu/tyndp2018/projects/projects/92,5.67933,50.7567965,6.474704,50.867532
 North Sea Link,Kvilldal (NO),Blythe (GB),720,,1400,under construction,,https://tyndp.entsoe.eu/tyndp2018/projects/projects/110,6.637527,59.515096,-1.510277,55.126957
 HVDC SuedOstLink,Wolmirstedt (DE),Isar (DE),,557,2000,in permitting,,https://tyndp.entsoe.eu/tyndp2018/projects/projects/130,11.629014,52.252137,12.091596,48.080837
 HVDC Line A-North,Emden East (DE),Osterath (DE),,284,2000,in permitting,,https://tyndp.entsoe.eu/tyndp2018/projects/projects/132,7.206009,53.359403,6.619451,51.272935
@@ -23,4 +23,4 @@ HVDC Ultranet,Osterath (DE),Philippsburg (DE),,314,600,in permitting,,https://ty
 Gridlink,Kingsnorth (UK),Warande (FR),160,,1400,in permitting,,https://tyndp.entsoe.eu/tyndp2018/projects/projects/285,0.596111111111111,51.41972,2.376776,51.034368
 NeuConnect,Grain (UK),Fedderwarden (DE),680,,1400,in permitting,,https://tyndp.entsoe.eu/tyndp2018/projects/projects/309,0.716666666666667,51.44,8.046524,53.562763
 NordBalt,Klaipeda (LT),Nybro (SE),450,,700,built,,https://en.wikipedia.org/wiki/NordBalt,21.256667,55.681667,15.854167,56.767778
-Estlink 1,Harku (EE),Espoo (FI),105,,350,built,,https://en.wikipedia.org/wiki/Estlink,24.560278,59.384722,24.551667,60.203889
+Estlink 1,Harku (EE),Espoo (FI),105,,350,built,,https://en.wikipedia.org/wiki/Estlink,24.560278,59.384722,24.551667,60.203889

data/parameter_corrections.yaml

@@ -33,12 +33,13 @@ Link:
       "14559": "6240" # fix wrong bus allocation from 6241
       "12998": "1333" # combine link 12998 + 12997 in 12998
       "5627": '2309' # combine link 5627 + 5628 in 5627
+      "8068": "5819" # fix GB location of Anglo-Scottish interconnector
   length: 
     index:
-      "12998": 409.0 
+      "12998": 409.0
       "5627": 26.39
   bus0: 
     index: 
-      # set bus0 == bus1 for removing the link in remove_unconnected_components
-      "5628": "7276" 
-      "12997": "7276"
+      "14552": "5819" # fix GB location of GB-IE interconnector
+      "5628": "7276" # bus0 == bus1 to remove link in remove_unconnected_components
+      "12997": "7276" # bus0 == bus1 to remove link in remove_unconnected_components

doc/_static/theme_overrides.css

@@ -2,22 +2,73 @@
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+}
+
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+}
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+    color: rgb(34, 97, 156)
+}
+
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+.wy-menu-vertical p.caption,
+.rst-versions a {
+    color: #999999;
+}
+
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+.wy-menu-vertical a.reference.internal:hover {
+    background: #dddddd;
+    color: #fff;
+}
+
+.wy-nav-side {
+    background: #efefef;
+}
+
+.wy-menu-vertical a.reference {
+    color: #000;
+}
+
+.rst-versions .rst-current-version,
+.wy-nav-top,
+.wy-menu-vertical li.toctree-l2.current li.toctree-l3>a:hover {
+    background: #002221;
+}
+
+.wy-nav-content .highlight {
+    background: #ffffff;
+}
+
+.rst-content code.literal,
+.rst-content tt.literal {
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+}
+
+.wy-nav-content a.reference {
+    color: rgb(34, 97, 156);
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+
+
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+
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-       /* !important prevents the common CSS stylesheets from overriding
+        /* !important prevents the common CSS stylesheets from overriding
           this as on RTD they are loaded after this stylesheet */
-       white-space: normal !important;
-       /* background: #eeeeee !important; */
+        white-space: normal !important;
+        background: rgb(250, 250, 250) !important;
     }
- 
     .wy-table-responsive {
-       max-width: 100%;
-       overflow: visible !important;
+        max-width: 100%;
+        overflow: visible !important;
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doc/cloudcomputing.rst

@@ -1,6 +1,6 @@
 ..
   SPDX-FileCopyrightText: 2020 Maximilian Parzen and Emmanuel Paez
-  
+
   SPDX-License-Identifier: CC-BY-4.0
 
 
@@ -18,7 +18,7 @@ Google Cloud Platform (GCP)
     We are happy to take pull requests explaining where the procedures deviate from the descriptions below for other operating systems.
     Likewise, tutorials for other cloud computing solutions are also highly welcome.
 
-The Google Cloud Platform (GCP) is a cloud computing service you can use to run PyPSA-Eur calculations, especially if 
+The Google Cloud Platform (GCP) is a cloud computing service you can use to run PyPSA-Eur calculations, especially if
 
 - you do not have immediate access to high-performance computating facilities,
 - you have problems with the Windows operating system and want a quick run on a linux-based system,
@@ -26,7 +26,7 @@ The Google Cloud Platform (GCP) is a cloud computing service you can use to run
 - you need quick results (trial version includes 32 vCPU cores and up to 800 GB of memory).
 
 With the Google Cloud Platform you set up a virtual machine in the cloud which can store and operate data.
-Like on your local computer, you have to install all software and solvers, and create paths on the virtual machine to set up the required environment. 
+Like on your local computer, you have to install all software and solvers, and create paths on the virtual machine to set up the required environment.
 The 300$ free trial budget is offered which equals roughly 10-20 simulations with 180 nodes at hourly basis.
 The following steps are required:
 
@@ -38,7 +38,7 @@ The following steps are required:
 Step 1 - Google Cloud Platform registration
 -------------------------------------------
 
-First, register at the `Google Cloud Platform <https://console.cloud.google.com>`_ (GCP). 
+First, register at the `Google Cloud Platform <https://console.cloud.google.com>`_ (GCP).
 Ann active bank account is required, which will not be charged unless you exceed the trial budget.
 
 Step 2 - Create your Virtual Machine instance
@@ -60,7 +60,7 @@ Now a window with the machine details will open. You have to configure the follo
   You can edit your machine configuration later. So use a cheap machine type configuration to transfer data and
   only when everything is ready and tested, your expensive machine type, for instance a custom 8 vCPU with 160 GB memory.
   Solvers do not parallelise well, so we recommend not to choose more than 8 vCPU.
-  Check ``snakemake -j -n 1 solve_all_elec_networks`` as a dry run to see how much memory is required.
+  Check ``snakemake -n -j 1 solve_all_networks`` as a dry run to see how much memory is required.
   The memory requirements will vary depending on the spatial and temporal resoulution of your optimisation.
   Example: for an hourly, 181 node full European network, set 8 vCPU and 150 GB memory since the dry-run calculated a 135 GB memory requirement.)
 - Boot disk: As default, your VM is created with 10 GB. Depending on how much you want to handle on one VM you should increase the disk size.
@@ -73,26 +73,26 @@ Step 3 - Installation of Cloud SDK
 - Download Google Cloud SDK `SDK <https://cloud.google.com/sdk>`_. Check that you are logged in in your Google account. The link should lead you to the Windows installation of Google Cloud SDK.
 - Follow the "Quickstart for Windows - Before you begin" steps.
 - After the successfull installation and initialization, close the Google Cloud SDK reopen it again. Type the following command into the "Google Cloud SDK Shell":
-    
+
     .. code:: bash
-        
+
         gcloud compute ssh <your VM instance name> -- -L 8888:localhost:8888
-        
+
 - This command above will open a PuTTy command window that is connected to your Virtual Machine. Time to celebrate if it works!
-- Now install all necessary tools. As little help, the first steps: 
+- Now install all necessary tools. As little help, the first steps:
     .. code:: bash
-        
+
         sudo apt-get update
         sudo apt-get install bzip2 libxml2-dev
         sudo apt-get install wget
-        wget https://repo.anaconda.com/archive/Anaconda3-2020.07-Linux-x86_64.sh    (Check the link. To be up to date with anaconda, check the Anaconda website https://www.anaconda.com/products/individual )
+        wget https://repo.anaconda.com/archive/Anaconda3-2020.07-Linux-x86_64.sh
         ls  (to see what anaconda file to bash)
-        bash Anaconda3-2020.07-Linux-x86_64.sh  
-        source ~/.bashrc  
-        
+        bash Anaconda3-2020.07-Linux-x86_64.sh
+        source ~/.bashrc
+
 - Close and reopen the PuTTy file (-> open Google Cloud SDK -> initialize again with the command above to open the PuTTY command window). Now ``conda`` can be listed with ``conda list``.
   Noq you can follow the standard installation instructions to finalize your machine (don't forget the solvers - for bigger simulations use commercial solvers such as Gurobi).
-        
+
 Step 4 - Installation of WinSCP
 -------------------------------
 
@@ -102,22 +102,22 @@ Make sure that your instance is operating for the next steps.
 - Download `WinSCP <https://winscp.net/eng/download.php>`_ and follow the default installation steps.
 - Open WinSCP after the installation. A login window will open.
 - Keep SFTP as file protocol.
-- As host name insert the External IP of your VM (click in your internet browser on your GCP VM instance to see the external IP) 
+- As host name insert the External IP of your VM (click in your internet browser on your GCP VM instance to see the external IP)
 - Set the User name in WinSCP to the name you see in your PuTTy window (check step 3 - for instance [username]@[VM-name]:~$)
-- Click on the advanced setting. SSH -> Authentication. 
-- Option 1. Click on the Tools button and "Install Public Key into Server..". Somewhere in your folder structure must be a public key. I found it with the following folder syntax on my local windows computer -> :\Users\...\.ssh (there should be a PKK file). 
-- Option 2. Click on the Tools button and "Generate new key pair...". Save the private key at a folder you remember and add it to the "private key file" field in WinSCP. Upload the public key to the metadeta of your instance. 
+- Click on the advanced setting. SSH -> Authentication.
+- Option 1. Click on the Tools button and "Install Public Key into Server..". Somewhere in your folder structure must be a public key. I found it with the following folder syntax on my local windows computer -> :\Users\...\.ssh (there should be a PKK file).
+- Option 2. Click on the Tools button and "Generate new key pair...". Save the private key at a folder you remember and add it to the "private key file" field in WinSCP. Upload the public key to the metadeta of your instance.
 - Click ok and save. Then click Login. If successfull WinSCP will open on the left side your local computer folder structure and on the right side the folder strucutre of your VM. (If you followed Option 2 and its not initially working. Stop your instance, refresh the website, reopen the WinSCP field. Afterwards your your Login should be successfull)
 If you had struggle with the above steps, you could also try `this video <https://www.youtube.com/watch?v=lYx1oQkEF0E>`_.
 
 .. note::
     Double check the External IP of your VM before you try to login with WinSCP. It's often a cause for an error.
-    
+
 Step 5 - Extra. Copying your instance with all its data and paths included
 --------------------------------------------------------------------------
 
 Especially if you think about operating several instance for quicker simulations, you can create a so called `"image" <https://console.cloud.google.com/compute/images?authuser=1&project=exalted-country-284917>`_ of the virtual machine.
-The "image" includes all the data and software set-ups from your VM. Afterwards you can create a VM from an image and avoid all the installation steps above. 
+The "image" includes all the data and software set-ups from your VM. Afterwards you can create a VM from an image and avoid all the installation steps above.
 
 Important points when to solve networks in PyPSA
 ------------------------------------------------
@@ -126,4 +126,4 @@ If you use the GCP with the default PyPSA-Eur settings, your budget will be used
 
 - Always test using low resolution networks; i.e. a single country at 5 nodes and 24h resolution for 2 month of weather data.
 - Adjust your solver in the ``config.yaml`` file. Set ``solving: skip_iterations: true``.
-  This will lead to a single solver iteration which is often precise enough. 
+  This will lead to a single solver iteration which is often precise enough.

doc/conf.py

@@ -74,9 +74,9 @@ author = u'Jonas Hoersch (KIT, FIAS), Fabian Hofmann (FIAS), David Schlachtberge
 # built documents.
 #
 # The short X.Y version.
-version = u'0.2'
+version = u'0.3'
 # The full version, including alpha/beta/rc tags.
-release = u'0.2.0'
+release = u'0.3.0'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

doc/configtables/atlite.csv

@@ -5,4 +5,4 @@ cutouts,,,
 -- -- module,--,"One 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>`_)"
 -- -- xs,°,"Float interval within [-180, 180]","Range of longitudes to download weather data for."
 -- -- ys,°,"Float interval within [-90, 90]","Range of latitudes to download weather data for."
--- -- years,--,"Integer interval within [1979,2018]","Range of years to download weather data for."
+-- -- years,--,"Integer interval within [1979,2018]","Range of years to download weather data for."

doc/configtables/costs.csv

@@ -6,4 +6,4 @@ fill_values,--,float,"Default values if not specified for a technology in ``reso
 capital_cost,EUR/MW,"Keys should be in the 'technology' column of ``resources/costs.csv``. Values can be any float.","For the given technologies, assumptions about their capital investment costs are set to the corresponding value. Optional; overwrites cost assumptions from ``resources/costs.csv``."
 marginal_cost,EUR/MWh,"Keys should be in the 'technology' column of ``resources/costs.csv``. Values can be any float.","For the given technologies, assumptions about their marginal operating costs are set to the corresponding value. Optional; overwrites cost assumptions from ``resources/costs.csv``."
 emission_prices,,,"Specify exogenous prices for emission types listed in ``network.carriers`` to marginal costs."
--- co2,EUR/t,float,"Exogenous price of carbon-dioxide added to the marginal costs of fossil-fuelled generators according to their carbon intensity. Added through the keyword ``Ep`` in the ``{opts}`` wildcard only in the rule :mod:`prepare_network``."
+-- co2,EUR/t,float,"Exogenous price of carbon-dioxide added to the marginal costs of fossil-fuelled generators according to their carbon intensity. Added through the keyword ``Ep`` in the ``{opts}`` wildcard only in the rule :mod:`prepare_network``."

doc/configtables/electricity.csv

@@ -1,16 +1,19 @@
-,Unit,Values,Description
-voltages,kV,"Any subset of {220., 300., 380.}","Voltage levels to consider when"
-co2limit,:math:`t_{CO_2-eq}/a`,float,"Cap on total annual system carbon dioxide emissions"
-co2base,:math:`t_{CO_2-eq}/a`,float,"Reference value of total annual system carbon dioxide emissions if relative emission reduction target is specified in ``{opts}`` wildcard."
-agg_p_nom_limits,--,file path,"Reference to ``.csv`` file specifying per carrier generator nominal capacity constraints for individual countries if ``'CCL'`` is in ``{opts}`` wildcard. Defaults to ``data/agg_p_nom_minmax.csv``."
-extendable_carriers,,,
--- Generator,--,"Any subset  of {'OCGT','CCGT'}","Places extendable conventional power plants (OCGT and/or CCGT) where gas power plants are located today without capacity limits."
--- StorageUnit,--,"Any subset of {'battery','H2'}","Adds extendable storage units (battery and/or hydrogen) at every node/bus after clustering without capacity limits and with zero initial capacity."
--- Store,--,"Any subset of {'battery','H2'}","Adds extendable storage units (battery and/or hydrogen) at every node/bus after clustering without capacity limits and with zero initial capacity."
--- Link,--,"Any subset of {'H2 pipeline'}","Adds extendable links (H2 pipelines only) at every connection where there are lines or HVDC links without capacity limits and with zero initial capacity. Hydrogen pipelines require hydrogen storage to be modelled as ``Store``."
-max_hours,,,
--- battery,h,float,"Maximum state of charge capacity of the battery in terms of hours at full output capacity ``p_nom``. Cf. `PyPSA documentation <https://pypsa.readthedocs.io/en/latest/components.html#storage-unit>`_."
--- H2,h,float,"Maximum state of charge capacity of the hydrogen storage in terms of hours at full output capacity ``p_nom``. Cf. `PyPSA documentation <https://pypsa.readthedocs.io/en/latest/components.html#storage-unit>`_."
-powerplants_filter,--,"use `pandas.query <https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.query.html>`_ strings here, e.g. Country not in ['Germany']","Filter query for the default powerplant database."
-custom_powerplants,--,"use `pandas.query <https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.query.html>`_ strings here, e.g. Country in ['Germany']","Filter query for the custom powerplant database."
-conventional_carriers,--,"Any subset of {nuclear, oil, OCGT, CCGT, coal, lignite, geothermal, biomass}","List of conventional power plants to include in the model from ``resources/powerplants.csv``."
+,Unit,Values,Description,
+voltages,kV,"Any subset of {220., 300., 380.}",Voltage levels to consider when,
+co2limit,:math:`t_{CO_2-eq}/a`,float,Cap on total annual system carbon dioxide emissions,
+co2base,:math:`t_{CO_2-eq}/a`,float,Reference value of total annual system carbon dioxide emissions if relative emission reduction target is specified in ``{opts}`` wildcard.,
+agg_p_nom_limits,file,path,Reference to ``.csv`` file specifying per carrier generator nominal capacity constraints for individual countries if ``'CCL'`` is in ``{opts}`` wildcard. Defaults to ``data/agg_p_nom_minmax.csv``.
+extendable_carriers,,,,
+-- Generator,--,"Any subset  of {'OCGT','CCGT'}",Places extendable conventional power plants (OCGT and/or CCGT) where gas power plants are located today without capacity limits.
+-- StorageUnit,--,"Any subset of {'battery','H2'}",Adds extendable storage units (battery and/or hydrogen) at every node/bus after clustering without capacity limits and with zero initial capacity.
+-- Store,--,"Any subset of {'battery','H2'}",Adds extendable storage units (battery and/or hydrogen) at every node/bus after clustering without capacity limits and with zero initial capacity.
+-- Link,--,Any subset of {'H2 pipeline'},Adds extendable links (H2 pipelines only) at every connection where there are lines or HVDC links without capacity limits and with zero initial capacity. Hydrogen pipelines require hydrogen storage to be modelled as ``Store``.
+max_hours,,,,
+-- battery,h,float,Maximum state of charge capacity of the battery in terms of hours at full output capacity ``p_nom``. Cf. `PyPSA documentation <https://pypsa.readthedocs.io/en/latest/components.html#storage-unit>`_.
+-- H2,h,float,Maximum state of charge capacity of the hydrogen storage in terms of hours at full output capacity ``p_nom``. Cf. `PyPSA documentation <https://pypsa.readthedocs.io/en/latest/components.html#storage-unit>`_.
+powerplants_filter,--,"use `pandas.query <https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.query.html>`_ strings here, e.g. Country not in ['Germany']",Filter query for the default powerplant database.,
+custom_powerplants,--,"use `pandas.query <https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.query.html>`_ strings here, e.g. Country in ['Germany']",Filter query for the custom powerplant database.,
+conventional_carriers,--,"Any subset of {nuclear, oil, OCGT, CCGT, coal, lignite, geothermal, biomass}",List of conventional power plants to include in the model from ``resources/powerplants.csv``.,
+renewable_capacities_from_OPSD,,"[solar, onwind, offwind]",List of carriers (offwind-ac and offwind-dc are included in offwind) whose capacities 'p_nom' are aligned to the `OPSD renewable power plant list <https://data.open-power-system-data.org/renewable_power_plants/>`_,
+estimate_renewable_capacities_from_capacitiy_stats,,,,
+"-- Fueltype [ppm], e.g. Wind",,"list of fueltypes strings in PyPSA-Eur, e.g. [onwind, offwind-ac, offwind-dc]",converts ppm Fueltype to PyPSA-EUR Fueltype,

doc/configtables/hydro.csv

@@ -3,4 +3,4 @@ cutout,--,"Must be 'europe-2013-era5'","Specifies the directory where the releva
 carriers,--,"Any subset of {'ror', 'PHS', 'hydro'}","Specifies the types of hydro power plants to build per-unit availability time series for. 'ror' stands for run-of-river plants, 'PHS' represents pumped-hydro storage, and 'hydro' stands for hydroelectric dams."
 PHS_max_hours,h,float,"Maximum state of charge capacity of the pumped-hydro storage (PHS) in terms of hours at full output capacity ``p_nom``. Cf. `PyPSA documentation <https://pypsa.readthedocs.io/en/latest/components.html#storage-unit>`_."
 hydro_max_hours,h,"Any of {float, 'energy_capacity_totals_by_country', 'estimate_by_large_installations'}","Maximum state of charge capacity of the pumped-hydro storage (PHS) in terms of hours at full output capacity ``p_nom`` or heuristically determined. Cf. `PyPSA documentation <https://pypsa.readthedocs.io/en/latest/components.html#storage-unit>`_."
-clip_min_inflow,MW,float,"To avoid too small values in the inflow time series, values below this threshold are set to zero."
+clip_min_inflow,MW,float,"To avoid too small values in the inflow time series, values below this threshold are set to zero."

doc/configtables/lines.csv

@@ -1,5 +1,6 @@
 ,Unit,Values,Description
 types,--,"Values should specify a `line type in PyPSA <https://pypsa.readthedocs.io/en/latest/components.html#line-types>`_. Keys should specify the corresponding voltage level (e.g. 220., 300. and 380. kV)","Specifies line types to assume for the different voltage levels of the ENTSO-E grid extraction. Should normally handle voltage levels 220, 300, and 380 kV"
 s_max_pu,--,"Value in [0.,1.]","Correction factor for line capacities (``s_nom``) to approximate :math:`N-1` security and reserve capacity for reactive power flows"
+s_nom_max,MW,"float","Global upper limit for the maximum capacity of each extendable line."
 length_factor,--,float,"Correction factor to account for the fact that buses are *not* connected by lines through air-line distance."
-under_construction,--,"One of {'zero': set capacity to zero, 'remove': remove completely, 'keep': keep with full capacity}","Specifies how to handle lines which are currently under construction."
+under_construction,--,"One of {'zero': set capacity to zero, 'remove': remove completely, 'keep': keep with full capacity}","Specifies how to handle lines which are currently under construction."

doc/configtables/links.csv

@@ -1,4 +1,5 @@
 ,Unit,Values,Description
 p_max_pu,--,"Value in [0.,1.]","Correction factor for link capacities ``p_nom``."
+p_nom_max,MW,"float","Global upper limit for the maximum capacity of each extendable DC link."
 include_tyndp,bool,"{'true', 'false'}","Specifies whether to add HVDC link projects from the `TYNDP 2018 <https://tyndp.entsoe.eu/tyndp2018/projects/>`_ which are at least in permitting."
-under_construction,--,"One of {'zero': set capacity to zero, 'remove': remove completely, 'keep': keep with full capacity}","Specifies how to handle lines which are currently under construction."
+under_construction,--,"One of {'zero': set capacity to zero, 'remove': remove completely, 'keep': keep with full capacity}","Specifies how to handle lines which are currently under construction."

doc/configtables/load.csv

@@ -1,2 +1,7 @@
 ,Unit,Values,Description
-scaling_factor,--,float,"Global correction factor for the load time series."
+url,--,string,"Link to open power system data time series data."
+power_statistics,bool,"{true, false}",Whether to load the electricity consumption data of the ENTSOE power statistics (only for files from 2019 and before) or from the ENTSOE transparency data (only has load data from 2015 onwards). 
+interpolate_limit,hours,integer,"Maximum gap size (consecutive nans) which interpolated linearly."
+time_shift_for_large_gaps,string,string,"Periods which are used for copying time-slices in order to fill large gaps of nans. Have to be valid ``pandas`` period strings."
+manual_adjustments,bool,"{true, false}","Whether to adjust the load data manually according to the function in :func:`manual_adjustment`."
+scaling_factor,--,float,"Global correction factor for the load time series."

doc/configtables/offwind-ac.csv

@@ -10,4 +10,4 @@ max_depth,m,float,"Maximum sea water depth at which wind turbines can be build.
 min_shore_distance,m,float,"Minimum distance to the shore below which wind turbines cannot be build. Such areas close to the shore are excluded in the process of calculating the AC-connected offshore wind potential."
 potential,--,"One of {'simple', 'conservative'}","Method to compute the maximal installable potential for a node; confer :ref:`renewableprofiles`"
 clip_p_max_pu,p.u.,float,"To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero."
-keep_all_available_areas,bool,"{'true', 'false'}","Use all availabe weather cells for renewable profile and potential generation. The default ignores weather cells where only less than 1 MW can be installed."
+keep_all_available_areas,bool,"{'true', 'false'}","Use all availabe weather cells for renewable profile and potential generation. The default ignores weather cells where only less than 1 MW can be installed."

doc/configtables/offwind-dc.csv

@@ -10,4 +10,4 @@ max_depth,m,float,"Maximum sea water depth at which wind turbines can be build.
 min_shore_distance,m,float,"Minimum distance to the shore below which wind turbines cannot be build. Such areas close to the shore are excluded in the process of calculating the AC-connected offshore wind potential."
 potential,--,"One of {'simple', 'conservative'}","Method to compute the maximal installable potential for a node; confer :ref:`renewableprofiles`"
 clip_p_max_pu,p.u.,float,"To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero."
-keep_all_available_areas,bool,"{'true', 'false'}","Use all availabe weather cells for renewable profile and potential generation. The default ignores weather cells where only less than 1 MW can be installed."
+keep_all_available_areas,bool,"{'true', 'false'}","Use all availabe weather cells for renewable profile and potential generation. The default ignores weather cells where only less than 1 MW can be installed."

doc/configtables/onwind.csv

@@ -11,4 +11,4 @@ corine,,,
 natura,bool,"{true, false}","Switch to exclude `Natura 2000 <https://en.wikipedia.org/wiki/Natura_2000>`_ natural protection areas. Area is excluded if ``true``."
 potential,--,"One of {'simple', 'conservative'}","Method to compute the maximal installable potential for a node; confer :ref:`renewableprofiles`"
 clip_p_max_pu,p.u.,float,"To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero."
-keep_all_available_areas,bool,"{'true', 'false'}","Use all availabe weather cells for renewable profile and potential generation. The default ignores weather cells where only less than 1 MW can be installed."
+keep_all_available_areas,bool,"{'true', 'false'}","Use all availabe weather cells for renewable profile and potential generation. The default ignores weather cells where only less than 1 MW can be installed."

doc/configtables/opts.csv

@@ -1,8 +1,11 @@
 Trigger, Description, Definition, Status
 ``nH``; i.e. ``2H``-``6H``, Resample the time-resolution by averaging over every ``n`` snapshots, ``prepare_network``: `average_every_nhours() <https://github.com/PyPSA/pypsa-eur/blob/6b964540ed39d44079cdabddee8333f486d0cd63/scripts/prepare_network.py#L110>`_ and its `caller <https://github.com/PyPSA/pypsa-eur/blob/6b964540ed39d44079cdabddee8333f486d0cd63/scripts/prepare_network.py#L146>`_), In active use
+``nSEG``; e.g. ``4380SEG``, "Apply time series segmentation with `tsam <https://tsam.readthedocs.io/en/latest/index.html>`_ package to ``n`` adjacent snapshots of varying lengths based on capacity factors of varying renewables, hydro inflow and load.", ``prepare_network``: apply_time_segmentation(), In active use
 ``Co2L``, Add an overall absolute carbon-dioxide emissions limit configured in ``electricity: co2limit``. If a float is appended an overall emission limit relative to the emission level given in ``electricity: co2base`` is added (e.g. ``Co2L0.05`` limits emissisions to 5% of what is given in ``electricity: co2base``), ``prepare_network``: `add_co2limit() <https://github.com/PyPSA/pypsa-eur/blob/6b964540ed39d44079cdabddee8333f486d0cd63/scripts/prepare_network.py#L19>`_ and its `caller <https://github.com/PyPSA/pypsa-eur/blob/6b964540ed39d44079cdabddee8333f486d0cd63/scripts/prepare_network.py#L154>`_, In active use
 ``Ep``, Add cost for a carbon-dioxide price configured in ``costs: emission_prices: co2`` to ``marginal_cost`` of generators (other emission types listed in ``network.carriers`` possible as well), ``prepare_network``: `add_emission_prices() <https://github.com/PyPSA/pypsa-eur/blob/6b964540ed39d44079cdabddee8333f486d0cd63/scripts/prepare_network.py#L24>`_ and its `caller <https://github.com/PyPSA/pypsa-eur/blob/6b964540ed39d44079cdabddee8333f486d0cd63/scripts/prepare_network.py#L158>`_, In active use
 ``CCL``, Add minimum and maximum levels of generator nominal capacity per carrier for individual countries. These can be specified in the file linked at ``electricity: agg_p_nom_limits`` in the configuration. File defaults to ``data/agg_p_nom_minmax.csv``., ``solve_network``, In active use
+``EQ``, "Require each country or node to on average produce a minimal share of its total consumption itself. Example: ``EQ0.5c`` demands each country to produce on average at least 50% of its consumption; ``EQ0.5`` demands each node to produce on average at least 50% of its consumption.", ``solve_network``, In active use
+``ATK``, "Require each node to be autarkic. Example: ``ATK`` removes all lines and links. ``ATKc`` removes all cross-border lines and links.", ``prepare_network``, In active use
 ``BAU``, Add a per-``carrier`` minimal overall capacity; i.e. at least ``40GW`` of ``OCGT`` in Europe; configured in ``electricity: BAU_mincapacities``, ``solve_network``: `add_opts_constraints() <https://github.com/PyPSA/pypsa-eur/blob/6b964540ed39d44079cdabddee8333f486d0cd63/scripts/solve_network.py#L66>`_, Untested
 ``SAFE``, Add a capacity reserve margin of a certain fraction above the peak demand to which renewable generators and storage do *not* contribute. Ignores network., ``solve_network`` `add_opts_constraints() <https://github.com/PyPSA/pypsa-eur/blob/6b964540ed39d44079cdabddee8333f486d0cd63/scripts/solve_network.py#L73>`_, Untested
-``carrier+factor``, "Alter the capital cost of a carrier by a factor. Example: ``solar+0.5`` reduces the capital cost of solar to 50\% of original values.", ``prepare_network``, In active use
+``carrier+{c|p}factor``, "Alter the capital cost (``c``) or installable potential (``p``) of a carrier by a factor. Example: ``solar+c0.5`` reduces the capital cost of solar to 50\% of original values.", ``prepare_network``, In active use

doc/configtables/plotting.csv

@@ -12,4 +12,3 @@ energy_min,TWh,float,"Lower y-axis limit in energy bar plots."
 energy_threshold,TWh,float,"Threshold below which technologies will not be shown in energy bar plots."
 tech_colors,--,"carrier -> HEX colour code","Mapping from network ``carrier`` to a colour (`HEX colour code <https://en.wikipedia.org/wiki/Web_colors#Hex_triplet>`_)."
 nice_names,--,"str -> str","Mapping from network ``carrier`` to a more readable name."
-nice_names_n,--,"str -> str","Same as nice_names, but with linebreaks."

doc/configtables/scenario.csv

@@ -1,6 +1,5 @@
 ,Unit,Values,Description
-sectors,--,"Must be 'elec'","Placeholder for integration of other energy sectors."
 simpl,--,cf. :ref:`simpl`,"List of ``{simpl}`` wildcards to run."
-ll,--,cf. :ref:`ll`,"List of ``{ll}`` wildcards to run."
 clusters,--,cf. :ref:`clusters`,"List of ``{clusters}`` wildcards to run."
-opts,--,cf. :ref:`opts`,"List of ``{opts}`` wildcards to run."
+ll,--,cf. :ref:`ll`,"List of ``{ll}`` wildcards to run."
+opts,--,cf. :ref:`opts`,"List of ``{opts}`` wildcards to run."

doc/configtables/snapshots.csv

@@ -1,4 +1,4 @@
 ,Unit,Values,Description
 start,--,"str or datetime-like; e.g. YYYY-MM-DD","Left bound of date range"
 end,--,"str or datetime-like; e.g. YYYY-MM-DD","Right bound of date range"
-closed,--,"One of {None, ‘left’, ‘right’}","Make the time interval closed to the ``left``, ``right``, or both sides ``None``."
+closed,--,"One of {None, ‘left’, ‘right’}","Make the time interval closed to the ``left``, ``right``, or both sides ``None``."

doc/configtables/solar.csv

@@ -12,4 +12,4 @@ corine,--,"Any subset of the `CORINE Land Cover code list <http://www.eea.europa
 natura,bool,"{true, false}","Switch to exclude `Natura 2000 <https://en.wikipedia.org/wiki/Natura_2000>`_ natural protection areas. Area is excluded if ``true``."
 potential,--,"One of {'simple', 'conservative'}","Method to compute the maximal installable potential for a node; confer :ref:`renewableprofiles`"
 clip_p_max_pu,p.u.,float,"To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero."
-keep_all_available_areas,bool,"{'true', 'false'}","Use all availabe weather cells for renewable profile and potential generation. The default ignores weather cells where only less than 1 MW can be installed."
+keep_all_available_areas,bool,"{'true', 'false'}","Use all availabe weather cells for renewable profile and potential generation. The default ignores weather cells where only less than 1 MW can be installed."

doc/configtables/solving-options.csv

@@ -7,4 +7,4 @@ max_iterations,--,int,"Maximum number of solving iterations in between which res
 nhours,--,int,"Specifies the :math:`n` first snapshots to take into account. Must be less than the total number of snapshots. Rather recommended only for debugging."
 clip_p_max_pu,p.u.,float,"To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero."
 skip_iterations,bool,"{'true','false'}","Skip iterating, do not update impedances of branches."
-track_iterations,bool,"{'true','false'}","Flag whether to store the intermediate branch capacities and objective function values are recorded for each iteration in ``network.lines['s_nom_opt_X']`` (where ``X`` labels the iteration)"
+track_iterations,bool,"{'true','false'}","Flag whether to store the intermediate branch capacities and objective function values are recorded for each iteration in ``network.lines['s_nom_opt_X']`` (where ``X`` labels the iteration)"

doc/configtables/solving-solver.csv

@@ -1,3 +1,3 @@
 ,Unit,Values,Description
 name,--,"One of {'gurobi', 'cplex', 'cbc', 'glpk', 'ipopt'}; potentially more possible","Solver to use for optimisation problems in the workflow; e.g. clustering and linear optimal power flow."
-opts,--,"Parameter list for `Gurobi <https://www.gurobi.com/documentation/8.1/refman/parameters.html>`_ and `CPLEX <https://www.ibm.com/support/knowledgecenter/SSSA5P_12.5.1/ilog.odms.cplex.help/CPLEX/Parameters/topics/introListAlpha.html>`_","Solver specific parameter settings."
+opts,--,"Parameter list for `Gurobi <https://www.gurobi.com/documentation/8.1/refman/parameters.html>`_ and `CPLEX <https://www.ibm.com/support/knowledgecenter/SSSA5P_12.5.1/ilog.odms.cplex.help/CPLEX/Parameters/topics/introListAlpha.html>`_","Solver specific parameter settings."

doc/configtables/toplevel.csv

@@ -3,7 +3,7 @@ version,--,0.x.x,"Version of PyPSA-Eur"
 tutorial,bool,"{true, false}","Switch to retrieve the tutorial data set instead of the full data set."
 logging,,,
 -- level,--,"Any of {'INFO', 'WARNING', 'ERROR'}","Restrict console outputs to all infos, warning or errors only"
--- format,--,"e.g. ``%(levelname)s:%(name)s:%(message)s``","Custom format for log messages. See `LogRecord <https://docs.python.org/3/library/logging.html#logging.LogRecord>`_ attributes."
+-- format,--,"","Custom format for log messages. See `LogRecord <https://docs.python.org/3/library/logging.html#logging.LogRecord>`_ attributes."
 summary_dir,--,"e.g. 'results'","Directory into which results are written."
 countries,--,"Subset of {'AL', 'AT', 'BA', 'BE', 'BG', 'CH', 'CZ', 'DE', 'DK', 'EE', 'ES', 'FI', 'FR', 'GB', 'GR', 'HR', 'HU', 'IE', 'IT', 'LT', 'LU', 'LV', 'ME', 'MK', 'NL', 'NO', 'PL', 'PT', 'RO', 'RS', 'SE', 'SI', 'SK'}","European countries defined by their `Two-letter country codes (ISO 3166-1) <https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2>`_ which should be included in the energy system model."
 focus_weights,--,"Keys should be two-digit country codes (e.g. DE) and values should range between 0 and 1","Ratio of total clusters for particular countries. the remaining weight is distributed according to mean load. An example: ``focus_weights: DE: 0.6 FR: 0.2``."
@@ -13,4 +13,5 @@ enable,,,
 -- build_cutout,bool,"{true, false}","Switch to enable the building of cutouts via the rule :mod:`build_cutout`."
 -- retrieve_cutout,bool,"{true, false}","Switch to enable the retrieval of cutouts from zenodo with :mod:`retrieve_cutout`."
 -- build_natura_raster,bool,"{true, false}","Switch to enable the creation of the raster ``natura.tiff`` via the rule :mod:`build_natura_raster`."
--- retrieve_natura_raster,bool,"{true, false}","Switch to enable the retrieval of ``natura.tiff`` from zenodo with :mod:`retrieve_natura_raster`."
+-- retrieve_natura_raster,bool,"{true, false}","Switch to enable the retrieval of ``natura.tiff`` from zenodo with :mod:`retrieve_natura_raster`."
+-- custom_busmap,bool,"{true, false}","Switch to enable the use of custom busmaps in rule :mod:`cluster_network`. If activated the rule looks for provided busmaps at ``data/custom_busmap_elec_s{simpl}_{clusters}.csv`` which should have the same format as ``resources/busmap_elec_s{simpl}_{clusters}.csv``, i.e. the index should contain the buses of ``networks/elec_s{simpl}.nc``."

doc/configtables/transformers.csv

@@ -1,4 +1,4 @@
 ,Unit,Values,Description
 x,p.u.,float,"Series reactance (per unit, using ``s_nom`` as base power of the transformer. Overwritten if ``type`` is specified."
 s_nom,MVA,float,"Limit of apparent power which can pass through branch. Overwritten if ``type`` is specified."
-type,--,"A `transformer type in PyPSA <https://pypsa.readthedocs.io/en/latest/components.html#transformer-types>`_.","Specifies transformer types to assume for the transformers of the ENTSO-E grid extraction."
+type,--,"A `transformer type in PyPSA <https://pypsa.readthedocs.io/en/latest/components.html#transformer-types>`_.","Specifies transformer types to assume for the transformers of the ENTSO-E grid extraction."

doc/configuration.rst

@@ -18,7 +18,7 @@ Top-level configuration
 
 .. literalinclude:: ../config.default.yaml
    :language: yaml
-   :lines: 1-8,17,24-30
+   :lines: 5-12,20,27-34
 
 .. csv-table::
    :header-rows: 1
@@ -36,13 +36,13 @@ investment changes as more ambitious greenhouse-gas emission reduction targets a
 
 The ``scenario`` section is an extraordinary section of the config file
 that is strongly connected to the :ref:`wildcards` and is designed to
-facilitate running multiple scenarios through a single command 
+facilitate running multiple scenarios through a single command
 
 .. code:: bash
-    
-    snakemake -j 1 solve_all_elec_networks
 
-For each wildcard, a **list of values** is provided. The rule ``solve_all_elec_networks`` will trigger the rules for creating ``results/networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc`` for **all combinations** of the provided wildcard values as defined by Python's `itertools.product(...) <https://docs.python.org/2/library/itertools.html#itertools.product>`_ function that snakemake's `expand(...) function <https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#targets>`_ uses.
+    snakemake -j 1 solve_all_networks
+
+For each wildcard, a **list of values** is provided. The rule ``solve_all_networks`` will trigger the rules for creating ``results/networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc`` for **all combinations** of the provided wildcard values as defined by Python's `itertools.product(...) <https://docs.python.org/2/library/itertools.html#itertools.product>`_ function that snakemake's `expand(...) function <https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#targets>`_ uses.
 
 An exemplary dependency graph (starting from the simplification rules) then looks like this:
 
@@ -50,7 +50,7 @@ An exemplary dependency graph (starting from the simplification rules) then look
 
 .. literalinclude:: ../config.default.yaml
    :language: yaml
-   :lines: 10-15
+   :lines: 14-18
 
 .. csv-table::
    :header-rows: 1
@@ -66,7 +66,7 @@ Specifies the temporal range to build an energy system model for as arguments to
 
 .. literalinclude:: ../config.default.yaml
    :language: yaml
-   :lines: 19-22
+   :lines: 22-25
 
 .. csv-table::
    :header-rows: 1
@@ -80,7 +80,7 @@ Specifies the temporal range to build an energy system model for as arguments to
 
 .. literalinclude:: ../config.default.yaml
    :language: yaml
-   :lines: 32-50
+   :lines: 36-60
 
 .. csv-table::
    :header-rows: 1
@@ -97,7 +97,7 @@ Specifies the temporal range to build an energy system model for as arguments to
 
 .. literalinclude:: ../config.default.yaml
    :language: yaml
-   :lines: 57-70
+   :lines: 62-75
 
 .. csv-table::
    :header-rows: 1
@@ -114,7 +114,7 @@ Specifies the temporal range to build an energy system model for as arguments to
 
 .. literalinclude:: ../config.default.yaml
    :language: yaml
-   :lines: 72-89
+   :lines: 77-94
 
 .. csv-table::
    :header-rows: 1
@@ -126,7 +126,7 @@ Specifies the temporal range to build an energy system model for as arguments to
 
 .. literalinclude:: ../config.default.yaml
    :language: yaml
-   :lines: 72,90-102
+   :lines: 77,95-107
 
 .. csv-table::
    :header-rows: 1
@@ -138,7 +138,7 @@ Specifies the temporal range to build an energy system model for as arguments to
 
 .. literalinclude:: ../config.default.yaml
    :language: yaml
-   :lines: 72,103-116
+   :lines: 77,108-121
 
 .. csv-table::
    :header-rows: 1
@@ -150,7 +150,7 @@ Specifies the temporal range to build an energy system model for as arguments to
 
 .. literalinclude:: ../config.default.yaml
    :language: yaml
-   :lines: 72,117-136
+   :lines: 77,122-141
 
 .. csv-table::
    :header-rows: 1
@@ -162,7 +162,7 @@ Specifies the temporal range to build an energy system model for as arguments to
 
 .. literalinclude:: ../config.default.yaml
    :language: yaml
-   :lines: 72,137-143
+   :lines: 77,142-147
 
 .. csv-table::
    :header-rows: 1
@@ -176,7 +176,7 @@ Specifies the temporal range to build an energy system model for as arguments to
 
 .. literalinclude:: ../config.default.yaml
    :language: yaml
-   :lines: 145-152
+   :lines: 149-157
 
 .. csv-table::
    :header-rows: 1
@@ -190,7 +190,7 @@ Specifies the temporal range to build an energy system model for as arguments to
 
 .. literalinclude:: ../config.default.yaml
    :language: yaml
-   :lines: 154-157
+   :lines: 159-163
 
 .. csv-table::
    :header-rows: 1
@@ -204,7 +204,7 @@ Specifies the temporal range to build an energy system model for as arguments to
 
 .. literalinclude:: ../config.default.yaml
    :language: yaml
-   :lines: 159-162
+   :lines: 165-168
 
 .. csv-table::
    :header-rows: 1
@@ -218,7 +218,7 @@ Specifies the temporal range to build an energy system model for as arguments to
 
 .. literalinclude:: ../config.default.yaml
    :language: yaml
-   :lines: 164-165
+   :lines: 170-176
 
 .. csv-table::
    :header-rows: 1
@@ -232,7 +232,7 @@ Specifies the temporal range to build an energy system model for as arguments to
 
 .. literalinclude:: ../config.default.yaml
    :language: yaml
-   :lines: 167-179
+   :lines: 178-190
 
 .. csv-table::
    :header-rows: 1
@@ -241,7 +241,6 @@ Specifies the temporal range to build an energy system model for as arguments to
 
 .. note::
     To change cost assumptions in more detail (i.e. other than ``marginal_cost`` and ``capital_cost``), consider modifying cost assumptions directly in ``resources/costs.csv`` as this is not yet supported through the config file.
-
     You can also build multiple different cost databases. Make a renamed copy of ``resources/costs.csv`` (e.g. ``data/costs-optimistic.csv``) and set the variable ``COSTS=data/costs-optimistic.csv`` in the ``Snakefile``.
 
 .. _solving_cf:
@@ -254,7 +253,7 @@ Specifies the temporal range to build an energy system model for as arguments to
 
 .. literalinclude:: ../config.default.yaml
    :language: yaml
-   :lines: 181-189
+   :lines: 192-202
 
 .. csv-table::
    :header-rows: 1
@@ -266,7 +265,7 @@ Specifies the temporal range to build an energy system model for as arguments to
 
 .. literalinclude:: ../config.default.yaml
    :language: yaml
-   :lines: 181,190-206
+   :lines: 192,203-219
 
 .. csv-table::
    :header-rows: 1
@@ -280,7 +279,7 @@ Specifies the temporal range to build an energy system model for as arguments to
 
 .. literalinclude:: ../config.default.yaml
    :language: yaml
-   :lines: 208-342
+   :lines: 221-299
 
 .. csv-table::
    :header-rows: 1

doc/contributing.rst

@@ -12,7 +12,7 @@ be it with new ideas, suggestions, by filing bug reports or contributing code
 to our `GitHub repository <https://github.com/PyPSA/PyPSA-Eur>`_.
 
 * If you already have some code changes, you can submit them directly as a `pull request <https://github.com/PyPSA/pypsa-eur/pulls>`_.
-* If you are wondering where we would greatly appreciate your efforts, check out the ``help wanted`` tag in the `issues list <https://github.com/PyPSA/pypsa-eur/issues`_ and initiate a discussion there..
+* If you are wondering where we would greatly appreciate your efforts, check out the ``help wanted`` tag in the `issues list <https://github.com/PyPSA/pypsa-eur/issues>`_ and initiate a discussion there.
 * If you start working on a feature in the code, let us know by opening an issue or a draft pull request.
   This helps all of us to keep an overview on what is being done and helps to avoid a situation where we
   are doing the same work twice in parallel.

doc/costs.rst

@@ -34,7 +34,7 @@ Based on the parameters above the ``marginal_cost`` and ``capital_cost`` of the
 
 .. note::
 
-    Another great resource for `cost assumptions <https://ens.dk/en/our-services/projections-and-models/technology-data`_ is the cost database from the Danish Energy Agency.
+    Another great resource for cost assumptions is the `cost database from the Danish Energy Agency <https://ens.dk/en/our-services/projections-and-models/technology-data>`_.
 
 Modifying Cost Assumptions
 ==========================
@@ -43,4 +43,11 @@ Some cost assumptions (e.g. marginal cost and capital cost) can be directly over
 
 To change cost assumptions in more detail, modify cost assumptions directly in ``resources/costs.csv`` as this is not yet supported through the config file.
 
+<<<<<<< HEAD
 You can also build multiple different cost databases. Make a renamed copy of ``resources/costs.csv`` (e.g. ``data/costs-optimistic.csv``) and set the variable ``COSTS=data/costs-optimistic.csv`` in the ``Snakefile``.
+=======
+.. csv-table::
+   :header-rows: 1
+   :widths: 10,3,5,4,6,8
+   :file: ../data/costs.csv
+>>>>>>> master

doc/index.rst

@@ -8,7 +8,7 @@ PyPSA-Eur: An Open Optimisation Model of the European Transmission System
 
 .. image:: https://img.shields.io/github/v/release/pypsa/pypsa-eur?include_prereleases
     :alt: GitHub release (latest by date including pre-releases)
-    
+
 .. image:: https://travis-ci.org/PyPSA/pypsa-eur.svg?branch=master
     :target: https://travis-ci.org/PyPSA/pypsa-eur
 
@@ -19,8 +19,8 @@ PyPSA-Eur: An Open Optimisation Model of the European Transmission System
 .. image:: https://img.shields.io/github/repo-size/pypsa/pypsa-eur
     :alt: GitHub repo size
 
-.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3520875.svg
-    :target: https://doi.org/10.5281/zenodo.3520875
+.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3520874.svg
+    :target: https://doi.org/10.5281/zenodo.3520874
 
 .. image:: https://badges.gitter.im/PyPSA/community.svg
     :target: https://gitter.im/PyPSA/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge
@@ -42,6 +42,8 @@ It contains alternating current lines at and above 220 kV voltage level and all
 The model is suitable both for operational studies and generation and transmission expansion planning studies. The continental scope and highly resolved spatial scale enables a proper description of the long-range smoothing effects for renewable power generation and their varying resource availability.
 
 .. image:: img/base.png
+    :width: 50%
+    :align: center
 
 The restriction to freely available and open data encourages the open exchange of model data developments and eases the comparison of model results. It provides a full, automated software pipeline to assemble the load-flow-ready model from the original datasets, which enables easy replacement and improvement of the individual parts.
 
@@ -101,9 +103,9 @@ Documentation
    simplification
    solving
    plotting
-   
+
 **References**
-   
+
 * :doc:`release_notes`
 * :doc:`limitations`
 * :doc:`contributing`
@@ -169,21 +171,21 @@ Please use the following BibTeX: ::
 If you want to cite a specific PyPSA-Eur version, each release of PyPSA-Eur is stored on Zenodo with a release-specific DOI.
 This can be found linked from the overall PyPSA-Eur Zenodo DOI:
 
-.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3520875.svg
-   :target: https://doi.org/10.5281/zenodo.3520875
+.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3520874.svg
+   :target: https://doi.org/10.5281/zenodo.3520874
 
 Pre-Built Networks as a Dataset
 ===============================
 
 There are pre-built networks available as a dataset on Zenodo as well for every release of PyPSA-Eur.
 
-.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3601882.svg
-   :target: https://doi.org/10.5281/zenodo.3601882
+.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3601881.svg
+   :target: https://doi.org/10.5281/zenodo.3601881
 
 The included ``.nc`` files are PyPSA network files which can be imported with PyPSA via:
 
 .. code:: python
-    
+
     import pypsa
 
     filename = "elec_s_1024_ec.nc" # example
@@ -202,7 +204,7 @@ PyPSA-Eur work is released under multiple licenses:
 See the individual files and the `dep5 <.reuse/dep5>`_ file for license details.
 
 Additionally, different licenses and terms of use also apply to the various input data, which are summarised below.
-More details are included in 
+More details are included in
 `the description of the data bundles on zenodo <https://zenodo.org/record/3517935#.XbGeXvzRZGo>`_.
 
 .. csv-table::

doc/installation.rst

@@ -1,6 +1,6 @@
 ..
   SPDX-FileCopyrightText: 2019-2020 The PyPSA-Eur Authors
-  
+
   SPDX-License-Identifier: CC-BY-4.0
 
 .. _installation:
@@ -17,6 +17,7 @@ Clone the Repository
 
 First of all, clone the `PyPSA-Eur repository <https://github.com/PyPSA/pypsa-eur>`_ using the version control system ``git``.
 The path to the directory into which the ``git repository`` is cloned, must **not** have any spaces!
+If you do not have ``git`` installed, follow installation instructions `here <https://git-scm.com/book/en/v2/Getting-Started-Installing-Git>`_.
 
 .. code:: bash
 
@@ -24,8 +25,6 @@ The path to the directory into which the ``git repository`` is cloned, must **no
 
     /some/path/without/spaces % git clone https://github.com/PyPSA/pypsa-eur.git
 
-.. note::
-    If you do not have ``git`` installed, follow installation instructions `here <https://git-scm.com/book/en/v2/Getting-Started-Installing-Git>`_.
 
 .. _deps:
 
@@ -37,32 +36,31 @@ We recommend using the package manager and environment management system ``conda
 Install `miniconda <https://docs.conda.io/en/latest/miniconda.html>`_, which is a mini version of `Anaconda <https://www.anaconda.com/>`_ that includes only ``conda`` and its dependencies or make sure ``conda`` is already installed on your system.
 For instructions for your operating system follow the ``conda`` `installation guide <https://docs.conda.io/projects/conda/en/latest/user-guide/install/>`_.
 
-The python package requirements are curated in the `environment.yaml <https://github.com/PyPSA/pypsa-eur/blob/master/environment.yaml>`_ file.
+The python package requirements are curated in the `envs/environment.yaml <https://github.com/PyPSA/pypsa-eur/blob/master/envs/environment.yaml>`_ file.
 The environment can be installed and activated using
 
 .. code:: bash
 
-    .../pypsa-eur % conda env create -f environment.yaml
+    .../pypsa-eur % conda env create -f envs/environment.yaml
 
     .../pypsa-eur % conda activate pypsa-eur
 
-.. note::
-    Note that activation is local to the currently open shell!
-    After opening a new terminal window, one needs to reissue the second command!
+Note that activation is local to the currently open shell!
+After opening a new terminal window, one needs to reissue the second command!
 
 .. note::
     If you have troubles with a slow ``conda`` installation, we recommend to install
     `mamba <https://github.com/QuantStack/mamba>`_ as a fast drop-in replacement via
 
     .. code:: bash
-        
+
         conda install -c conda-forge mamba
 
     and then install the environment with
 
     .. code:: bash
 
-        mamba env create -f environment.yaml
+        mamba env create -f envs/environment.yaml
 
 Install a Solver
 ================
@@ -74,25 +72,23 @@ PyPSA is known to work with the free software
 - `Cbc <https://projects.coin-or.org/Cbc#DownloadandInstall>`_
 - `GLPK <https://www.gnu.org/software/glpk/>`_ (`WinGLKP <http://winglpk.sourceforge.net/>`_)
 
-and the non-free, commercial software (for which free academic licenses are available)
+and the non-free, commercial software (for some of which free academic licenses are available)
 
 - `Gurobi <https://www.gurobi.com/documentation/quickstart.html>`_
 - `CPLEX <https://www.ibm.com/products/ilog-cplex-optimization-studio>`_
+- `FICO® Xpress Solver <https://www.fico.com/de/products/fico-xpress-solver>`_
 
-and any other solver that works with the underlying modelling framework `Pyomo <http://www.pyomo.org/>`_.
 For installation instructions of these solvers for your operating system, follow the links above.
+Commercial solvers such as Gurobi and CPLEX currently significantly outperform open-source solvers for large-scale problems.
+It might be the case that you can only retrieve solutions by using a commercial solver.
 
 .. seealso::
     `Getting a solver in the PyPSA documentation <https://pypsa.readthedocs.io/en/latest/installation.html#getting-a-solver-for-linear-optimisation>`_
 
-.. note::
-    Commercial solvers such as Gurobi and CPLEX currently significantly outperform open-source solvers for large-scale problems.
-    It might be the case that you can only retrieve solutions by using a commercial solver.
-
 .. note::
     The rules :mod:`cluster_network` and :mod:`simplify_network` solve a quadratic optimisation problem for clustering.
     The open-source solvers Cbc and GlPK cannot handle this. A fallback to Ipopt is implemented in this case, but requires
-    also Ipopt to be installed. For an open-source solver setup install in your `conda` environment on OSX/Linux
+    also Ipopt to be installed. For an open-source solver setup install in your ``conda`` environment on OSX/Linux
 
     .. code:: bash
 
@@ -102,10 +98,10 @@ For installation instructions of these solvers for your operating system, follow
     and on Windows
 
     .. code:: bash
-        
+
         conda activate pypsa-eur
         conda install -c conda-forge ipopt glpk
-        
+
 
 .. _defaultconfig:
 
@@ -113,7 +109,7 @@ Set Up the Default Configuration
 ================================
 
 PyPSA-Eur has several configuration options that must be specified in a ``config.yaml`` file located in the root directory.
-An example configuration ``config.default.yaml`` is maintained in the repository. 
+An example configuration ``config.default.yaml`` is maintained in the repository.
 More details on the configuration options are in :ref:`config`.
 
 Before first use, create a ``config.yaml`` by copying the example.

doc/introduction.rst

@@ -1,6 +1,6 @@
 ..
   SPDX-FileCopyrightText: 2019-2020 The PyPSA-Eur Authors
-  
+
   SPDX-License-Identifier: CC-BY-4.0
 
 .. _intro:
@@ -64,4 +64,6 @@ Folder Structure
 System Requirements
 ===================
 
-Building the model with the scripts in this repository uses up to 20 GB of memory. Computing optimal investment and operation scenarios requires a strong interior-point solver compatible with the modelling library `Pyomo <https://www.pyomo.org>`_ like `Gurobi <http://www.gurobi.com/>`_ or `CPLEX <https://www.ibm.com/analytics/cplex-optimizer>`_ with up to 100 GB of memory.
+Building the model with the scripts in this repository runs on a normal computer.
+But computing optimal investment and operation scenarios requires a strong interior-point solver
+like `Gurobi <http://www.gurobi.com/>`_ or `CPLEX <https://www.ibm.com/analytics/cplex-optimizer>`_ with more memory.

doc/limitations.rst

@@ -37,7 +37,7 @@ improving the approximations.
   not spatially disaggregated; assuming, as we have done, that the load time series
   shape is the same at each node within each country ignores local differences.
 
-- **Currently installed renewable capacities:** 
+- **Currently installed renewable capacities:**
   Information on existing wind, solar and small hydro, geothermal, marine and
   biomass power plants are excluded from the dataset because of a lack of data
   availability in many countries. Approximate distributions of wind and solar
@@ -56,4 +56,3 @@ improving the approximations.
   Belarus, Ukraine, Turkey and Morocco have not been taken into account;
   islands which are not connected to the main European system, such as Malta,
   Crete and Cyprus, are also excluded from the model.
-  

doc/plotting.rst

@@ -173,4 +173,4 @@ Rule ``plot_network``
 .. automodule:: plot_network
 
 .. image:: img/tech-colors.png
-    :align: center
+    :align: center

doc/preparation.rst

@@ -39,6 +39,7 @@ together into a detailed PyPSA network stored in ``networks/elec.nc``.
 
    preparation/retrieve
    preparation/build_shapes
+   preparation/build_load_data
    preparation/build_cutout
    preparation/build_natura_raster
    preparation/prepare_links_p_nom

doc/preparation/base_network.rst

@@ -2,7 +2,7 @@
   SPDX-FileCopyrightText: 2019-2020 The PyPSA-Eur Authors
 
   SPDX-License-Identifier: CC-BY-4.0
-  
+
 .. _base:
 
 Rule ``base_network``
@@ -51,4 +51,4 @@ Rule ``base_network``
 
 |
 
-.. automodule:: base_network
+.. automodule:: base_network

doc/preparation/build_bus_regions.rst

@@ -48,4 +48,4 @@ Rule ``build_bus_regions``
 
 |
 
-.. automodule:: build_bus_regions
+.. automodule:: build_bus_regions

doc/preparation/build_cutout.rst

@@ -39,4 +39,4 @@ Rule ``build_cutout``
 
 |
 
-.. automodule:: build_cutout
+.. automodule:: build_cutout

doc/preparation/build_load_data.rst

@@ -0,0 +1,12 @@
+..
+  SPDX-FileCopyrightText: 2020-2021 The PyPSA-Eur Authors
+
+  SPDX-License-Identifier: CC-BY-4.0
+
+.. _load_data:
+
+Rule ``build_load_data``
+=============================
+
+
+.. automodule:: build_load_data

doc/release_notes.rst

@@ -11,31 +11,123 @@ Release Notes
 Upcoming Release
 ================
 
-* Added an option to alter the capital cost of carriers by a factor via ``carrier+factor`` in the ``{opts}`` wildcard. This can be useful for exploring uncertain cost parameters. Example: ``solar+0.5`` reduces the capital cost of solar to 50% of original values (`#167 <https://github.com/PyPSA/pypsa-eur/pull/167>`_).
+* Fix: Value for ``co2base`` in ``config.yaml`` adjusted to 1.487e9 t CO2-eq (from 3.1e9 t CO2-eq). The new value represents emissions related to the electricity sector for EU+UK. The old value was ~2x too high and used when the emissions wildcard in ``{opts}`` was used.
 
-* Add compatibility for pyomo 5.7.0 in :mod:`cluster_network` and :mod:`simplify_network`.
-
-* Raise a warning if `tech_colors` in the config are not defined for all carriers.
-
-* Corrected HVDC link connections (a) between Norway and Denmark and (b) mainland Italy, Corsica (FR) and Sardinia (IT) (`#181 <https://github.com/PyPSA/pypsa-eur/pull/181>`_)
-
-* Added Google Cloud Platform tutorial (for Windows users).
-
-* Corrected setting of exogenous emission price (in ``cost: emission price:``). This was not weighted by the efficiency and effective emission of the generators (`#171 <https://github.com/PyPSA/pypsa-eur/pull/171>`_).
+* Add option to include marginal costs of links representing fuel cells, electrolysis, and battery inverters 
+  [`#232 <https://github.com/PyPSA/pypsa-eur/pull/232>`_].
 
 * Techno-economic parameters of technologies (e.g. costs and efficiencies) will now be retrieved from a separate repository `PyPSA/technology-data <https://github.com/pypsa/technology-data>`_ 
   that collects assumptions from a variety of sources. It is activated by default with ``enable: retrieve_cost_data: true`` and controlled with ``costs: year:`` and ``costs: version:``. 
-  The location of this data changed from ``data/costs.csv`` to ``resources/costs.csv`` (`#184 <https://github.com/PyPSA/pypsa-eur/pull/184>`_).
+  The location of this data changed from ``data/costs.csv`` to ``resources/costs.csv`` 
+  [`#184 <https://github.com/PyPSA/pypsa-eur/pull/184>`_].
+
+PyPSA-Eur 0.3.0 (7th December 2020)
+==================================
+
+**New Features**
+
+Using the ``{opts}`` wildcard for scenarios:
+
+* An option is introduced which adds constraints such that each country or node produces on average a minimal share of its total consumption itself.
+  For example ``EQ0.5c`` set in the ``{opts}`` wildcard requires each country to produce on average at least 50% of its consumption. Additionally,
+  the option ``ATK`` requires autarky at each node and removes all means of power transmission through lines and links. ``ATKc`` only removes
+  cross-border transfer capacities. 
+  [`#166 <https://github.com/PyPSA/pypsa-eur/pull/166>`_].
+
+* Added an option to alter the capital cost (``c``) or installable potentials (``p``) of carriers by a factor via ``carrier+{c,p}factor`` in the ``{opts}`` wildcard.
+  This can be useful for exploring uncertain cost parameters.
+  Example: ``solar+c0.5`` reduces the capital cost of solar to 50% of original values
+  [`#167 <https://github.com/PyPSA/pypsa-eur/pull/167>`_, `#207 <https://github.com/PyPSA/pypsa-eur/pull/207>`_].
+
+* Added an option to the ``{opts}`` wildcard that applies a time series segmentation algorithm based on renewables, hydro inflow and load time series
+  to produce a given total number of adjacent snapshots of varying lengths.
+  This feature is an alternative to downsampling the temporal resolution by simply averaging and
+  uses the `tsam <https://tsam.readthedocs.io/en/latest/index.html>`_ package
+  [`#186 <https://github.com/PyPSA/pypsa-eur/pull/186>`_].
+
+More OPSD integration:
+
+* Add renewable power plants from `OPSD <https://data.open-power-system-data.org/renewable_power_plants/2020-08-25>`_ to the network for specified technologies.
+  This will overwrite the capacities calculated from the heuristic approach in :func:`estimate_renewable_capacities()`
+  [`#212 <https://github.com/PyPSA/pypsa-eur/pull/212>`_].
+
+* Electricity consumption data is now retrieved directly from the `OPSD website <https://data.open-power-system-data.org/time_series/2019-06-05>`_ using the rule :mod:`build_load_data`.
+  The user can decide whether to take the ENTSO-E power statistics data (default) or the ENTSO-E transparency data
+  [`#211 <https://github.com/PyPSA/pypsa-eur/pull/211>`_].
+
+Other:
+
+* Added an option to use custom busmaps in rule :mod:`cluster_network`. To use this feature set ``enable: custom_busmap: true``.
+  Then, the rule looks for custom busmaps at ``data/custom_busmap_elec_s{simpl}_{clusters}.csv``,
+  which should have the same format as ``resources/busmap_elec_s{simpl}_{clusters}.csv``.
+  i.e. the index should contain the buses of ``networks/elec_s{simpl}.nc``
+  [`#193 <https://github.com/PyPSA/pypsa-eur/pull/193>`_].
+
+* Line and link capacities can be capped in the ``config.yaml`` at ``lines: s_nom_max:`` and ``links: p_nom_max``:
+  [`#166 <https://github.com/PyPSA/pypsa-eur/pull/166>`_].
+
+* Added Google Cloud Platform tutorial (for Windows users)
+  [`#177 <https://github.com/PyPSA/pypsa-eur/pull/177>`_].
+
+**Changes**
+
+* Don't remove capital costs from lines and links, when imposing a line volume limit (``lv``) or a line cost limit (``lc``).
+  Previously, these were removed to move the expansion in direction of the limit
+  [`#183 <https://github.com/PyPSA/pypsa-eur/pull/183>`_].
+
+* The mappings for clustered lines and buses produced by the :mod:`simplify_network` and :mod:`cluster_network` rules
+  changed from Hierarchical Data Format (``.h5``) to Comma-Separated Values format (``.csv``) for ease of use.
+  [`#198 <https://github.com/PyPSA/pypsa-eur/pull/198>`_]
+
+* The N-1 security margin for transmission lines is now fixed to a provided value in ``config.yaml``,
+  removing an undocumented linear interpolation between 0.5 and 0.7 in the range between 37 and 200 nodes.
+  [`#199 <https://github.com/PyPSA/pypsa-eur/pull/199>`_].
+
+* Modelling hydrogen and battery storage with Store and Link components is now the default,
+  rather than using StorageUnit components with fixed power-to-energy ratio
+  [`#205 <https://github.com/PyPSA/pypsa-eur/pull/205>`_].
+
+* Use ``mamba`` (https://github.com/mamba-org/mamba) for faster Travis CI builds
+  [`#196 <https://github.com/PyPSA/pypsa-eur/pull/196>`_].
+
+* Multiple smaller changes: Removed unused ``{network}`` wildcard, moved environment files to dedicated ``envs`` folder,
+  removed sector-coupling components from configuration files, updated documentation colors, minor refactoring and code cleaning
+  [`#190 <https://github.com/PyPSA/pypsa-eur/pull 190>`_].
+
+**Bugs and Compatibility**
+
+* Add compatibility for pyomo 5.7.0 in :mod:`cluster_network` and :mod:`simplify_network`
+  [`#172 <https://github.com/PyPSA/pypsa-eur/pull/172>`_].
+
+* Fixed a bug for storage units such that individual store and dispatch efficiencies are correctly taken account of rather than only their round-trip efficiencies.
+  In the cost database (``data/costs.csv``) the efficiency of battery inverters should be stated as per discharge/charge rather than per roundtrip
+  [`#202 <https://github.com/PyPSA/pypsa-eur/pull/202>`_].
+
+* Corrected exogenous emission price setting (in ``config: cost: emission price:``),
+  which now correctly accounts for the efficiency and effective emission of the generators
+  [`#171 <https://github.com/PyPSA/pypsa-eur/pull/171>`_].
+
+* Corrected HVDC link connections (a) between Norway and Denmark and (b) mainland Italy, Corsica (FR) and Sardinia (IT)
+  as well as for East-Western and Anglo-Scottish interconnectors
+  [`#181 <https://github.com/PyPSA/pypsa-eur/pull/181>`_, `#206 <https://github.com/PyPSA/pypsa-eur/pull/206>`_].
+
+* Fix bug of clustering ``offwind-{ac,dc}`` generators in the option of high-resolution generators for renewables.
+  Now, there are more sites for ``offwind-{ac,dc}`` available than network nodes.
+  Before, they were clustered to the resolution of the network (``elec_s1024_37m.nc``: 37 network nodes, 1024 generators)
+  [`#191 <https://github.com/PyPSA/pypsa-eur/pull/191>`_].
+
+* Raise a warning if ``tech_colors`` in the config are not defined for all carriers
+  [`#178 <https://github.com/PyPSA/pypsa-eur/pull/178>`_]. 
 
 
 PyPSA-Eur 0.2.0 (8th June 2020)
 ==================================
 
-* The optimization is now performed using the ``pyomo=False`` setting in the :func:`pypsa.lopf.network_lopf`. This speeds up the solving process significantly and consumes much less memory. The inclusion of additional constraints were adjusted to the new implementation. They are all passed to the :func:`network_lopf` function via the ``extra_functionality`` argument. The rule ``trace_solve_network`` was integrated into the rule :mod:`solve_network` and can be activated via configuration with ``solving: options: track_iterations: true``. The charging and discharging capacities of batteries modelled as store-link combination are now coupled (`#116 <https://github.com/PyPSA/pypsa-eur/pull/116>`_).
+* The optimization is now performed using the ``pyomo=False`` setting in the :func:`pypsa.lopf.network_lopf`. This speeds up the solving process significantly and consumes much less memory. The inclusion of additional constraints were adjusted to the new implementation. They are all passed to the :func:`network_lopf` function via the ``extra_functionality`` argument. The rule ``trace_solve_network`` was integrated into the rule :mod:`solve_network` and can be activated via configuration with ``solving: options: track_iterations: true``. The charging and discharging capacities of batteries modelled as store-link combination are now coupled [`#116 <https://github.com/PyPSA/pypsa-eur/pull/116>`_].
 
-* An updated extract of the `ENTSO-E Transmission System Map <https://www.entsoe.eu/data/map/>`_ (including Malta) was added to the repository using the `GridKit <https://github.com/PyPSA/GridKit>`_ tool. This tool has been updated to retrieve up-to-date map extracts using a single `script <https://github.com/PyPSA/GridKit/blob/master/entsoe/runall_in_docker.sh>`_. The update extract features 5322 buses, 6574 lines, 46 links. (`#118 <https://github.com/PyPSA/pypsa-eur/pull/118>`_).
+* An updated extract of the `ENTSO-E Transmission System Map <https://www.entsoe.eu/data/map/>`_ (including Malta) was added to the repository using the `GridKit <https://github.com/PyPSA/GridKit>`_ tool. This tool has been updated to retrieve up-to-date map extracts using a single `script <https://github.com/PyPSA/GridKit/blob/master/entsoe/runall_in_docker.sh>`_. The update extract features 5322 buses, 6574 lines, 46 links. [`#118 <https://github.com/PyPSA/pypsa-eur/pull/118>`_].
 
-* Added `FSFE REUSE <https://reuse.software>`_ compliant license information. Documentation now licensed under CC-BY-4.0 (`#160 <https://github.com/PyPSA/pypsa-eur/pull/160>`_).
+* Added `FSFE REUSE <https://reuse.software>`_ compliant license information. Documentation now licensed under CC-BY-4.0 [`#160 <https://github.com/PyPSA/pypsa-eur/pull/160>`_].
 
 * Added a 30 minute `video introduction <https://pypsa-eur.readthedocs.io/en/latest/introduction.html>`_ and a 20 minute `video tutorial <https://pypsa-eur.readthedocs.io/en/latest/tutorial.html>`_
 
@@ -43,55 +135,54 @@ PyPSA-Eur 0.2.0 (8th June 2020)
 
 * Added an option to skip iterative solving usually performed to update the line impedances of expanded lines at ``solving: options: skip_iterations:``.
 
-* ``snakemake`` rules for retrieving cutouts and the natura raster can now be disabled independently from their respective rules to build them; via ``config.*yaml`` (`#136 <https://github.com/PyPSA/pypsa-eur/pull/136>`_).
+* ``snakemake`` rules for retrieving cutouts and the natura raster can now be disabled independently from their respective rules to build them; via ``config.*yaml`` [`#136 <https://github.com/PyPSA/pypsa-eur/pull/136>`_].
 
-* Removed the ``id`` column for custom power plants in ``data/custom_powerplants.csv`` to avoid custom power plants with conflicting ids getting attached to the wrong bus (`#131 <https://github.com/PyPSA/pypsa-eur/pull/131>`_).
+* Removed the ``id`` column for custom power plants in ``data/custom_powerplants.csv`` to avoid custom power plants with conflicting ids getting attached to the wrong bus [`#131 <https://github.com/PyPSA/pypsa-eur/pull/131>`_].
 
-* Add option ``renewables: {carrier}: keep_all_available_areas:`` to use all availabe weather cells for renewable profile and potential generation. The default ignores weather cells where only less than 1 MW can be installed  (`#150 <https://github.com/PyPSA/pypsa-eur/pull/150>`_).
+* Add option ``renewables: {carrier}: keep_all_available_areas:`` to use all availabe weather cells for renewable profile and potential generation. The default ignores weather cells where only less than 1 MW can be installed  [`#150 <https://github.com/PyPSA/pypsa-eur/pull/150>`_].
 
-* Added a function ``_helpers.load_network()`` which loads a network with overridden components specified in ``snakemake.config['override_components']`` (`#128 <https://github.com/PyPSA/pypsa-eur/pull/128>`_).
+* Added a function ``_helpers.load_network()`` which loads a network with overridden components specified in ``snakemake.config['override_components']`` [`#128 <https://github.com/PyPSA/pypsa-eur/pull/128>`_].
 
-* Bugfix in  :mod:`base_network` which now finds all closest links, not only the first entry (`#143 <https://github.com/PyPSA/pypsa-eur/pull/143>`_).
+* Bugfix in  :mod:`base_network` which now finds all closest links, not only the first entry [`#143 <https://github.com/PyPSA/pypsa-eur/pull/143>`_].
 
-* Bugfix in :mod:`cluster_network` which now skips recalculation of link parameters if there are no links  (`#149 <https://github.com/PyPSA/pypsa-eur/pull/149>`_).
+* Bugfix in :mod:`cluster_network` which now skips recalculation of link parameters if there are no links  [`#149 <https://github.com/PyPSA/pypsa-eur/pull/149>`_].
 
-* Added information on pull requests to contribution guidelines (`#151 <https://github.com/PyPSA/pypsa-eur/pull/151>`_).
+* Added information on pull requests to contribution guidelines [`#151 <https://github.com/PyPSA/pypsa-eur/pull/151>`_].
 
 * Improved documentation on open-source solver setup and added usage warnings.
 
 * Updated ``conda`` environment regarding ``pypsa``, ``pyproj``, ``gurobi``, ``lxml``. This release requires PyPSA v0.17.0.
 
-
 PyPSA-Eur 0.1.0 (9th January 2020)
 ==================================
 
 This is the first release of PyPSA-Eur, a model of the European power system at the transmission network level. Recent changes include:
 
-* Documentation on installation, workflows and configuration settings is now available online at `pypsa-eur.readthedocs.io <pypsa-eur.readthedocs.io>`_ (`#65 <https://github.com/PyPSA/pypsa-eur/pull/65>`_).
+* Documentation on installation, workflows and configuration settings is now available online at `pypsa-eur.readthedocs.io <pypsa-eur.readthedocs.io>`_ [`#65 <https://github.com/PyPSA/pypsa-eur/pull/65>`_].
 
-* The ``conda`` environment files were updated and extended (`#81 <https://github.com/PyPSA/pypsa-eur/pull/81>`_).
+* The ``conda`` environment files were updated and extended [`#81 <https://github.com/PyPSA/pypsa-eur/pull/81>`_].
 
-* The power plant database was updated with extensive filtering options via ``pandas.query`` functionality (`#84 <https://github.com/PyPSA/pypsa-eur/pull/84>`_ and `#94 <https://github.com/PyPSA/pypsa-eur/pull/94>`_).
+* The power plant database was updated with extensive filtering options via ``pandas.query`` functionality [`#84 <https://github.com/PyPSA/pypsa-eur/pull/84>`_ and `#94 <https://github.com/PyPSA/pypsa-eur/pull/94>`_].
 
-* Continuous integration testing with `Travis CI <https://travis-ci.org>`_ is now included for Linux, Mac and Windows (`#82 <https://github.com/PyPSA/pypsa-eur/pull/82>`_).
+* Continuous integration testing with `Travis CI <https://travis-ci.org>`_ is now included for Linux, Mac and Windows [`#82 <https://github.com/PyPSA/pypsa-eur/pull/82>`_].
 
-* Data dependencies were moved to `zenodo <https://zenodo.org/>`_ and are now versioned (`#60 <https://github.com/PyPSA/pypsa-eur/issues/60>`_).
+* Data dependencies were moved to `zenodo <https://zenodo.org/>`_ and are now versioned [`#60 <https://github.com/PyPSA/pypsa-eur/issues/60>`_].
 
-* Data dependencies are now retrieved directly from within the snakemake workflow (`#86 <https://github.com/PyPSA/pypsa-eur/pull/86>`_).
+* Data dependencies are now retrieved directly from within the snakemake workflow [`#86 <https://github.com/PyPSA/pypsa-eur/pull/86>`_].
 
-* Emission prices can be added to marginal costs of generators through the keyworks ``Ep`` in the ``{opts}`` wildcard (`#100 <https://github.com/PyPSA/pypsa-eur/pull/100>`_).
+* Emission prices can be added to marginal costs of generators through the keyworks ``Ep`` in the ``{opts}`` wildcard [`#100 <https://github.com/PyPSA/pypsa-eur/pull/100>`_].
 
-* An option is introduced to add extendable nuclear power plants to the network (`#98 <https://github.com/PyPSA/pypsa-eur/pull/98>`_).
+* An option is introduced to add extendable nuclear power plants to the network [`#98 <https://github.com/PyPSA/pypsa-eur/pull/98>`_].
 
-* Focus weights can now be specified for particular countries for the network clustering, which allows to set a proportion of the total number of clusters for particular countries (`#87 <https://github.com/PyPSA/pypsa-eur/pull/87>`_).
+* Focus weights can now be specified for particular countries for the network clustering, which allows to set a proportion of the total number of clusters for particular countries [`#87 <https://github.com/PyPSA/pypsa-eur/pull/87>`_].
 
-* A new rule :mod:`add_extra_components` allows to add additional components to the network only after clustering. It is thereby possible to model storage units (e.g. battery and hydrogen) in more detail via a combination of ``Store``, ``Link`` and ``Bus`` elements (`#97 <https://github.com/PyPSA/pypsa-eur/pull/97>`_).
+* A new rule :mod:`add_extra_components` allows to add additional components to the network only after clustering. It is thereby possible to model storage units (e.g. battery and hydrogen) in more detail via a combination of ``Store``, ``Link`` and ``Bus`` elements [`#97 <https://github.com/PyPSA/pypsa-eur/pull/97>`_].
 
-* Hydrogen pipelines (including cost assumptions) can now be added alongside clustered network connections in the rule :mod:`add_extra_components` . Set ``electricity: extendable_carriers: Link: [H2 pipeline]`` and ensure hydrogen storage is modelled as a ``Store``. This is a first simplified stage (`#108 <https://github.com/PyPSA/pypsa-eur/pull/108>`_).
+* Hydrogen pipelines (including cost assumptions) can now be added alongside clustered network connections in the rule :mod:`add_extra_components` . Set ``electricity: extendable_carriers: Link: [H2 pipeline]`` and ensure hydrogen storage is modelled as a ``Store``. This is a first simplified stage [`#108 <https://github.com/PyPSA/pypsa-eur/pull/108>`_].
 
-* Logfiles for all rules of the ``snakemake`` workflow are now written in the folder ``log/`` (`#102 <https://github.com/PyPSA/pypsa-eur/pull/102>`_). 
+* Logfiles for all rules of the ``snakemake`` workflow are now written in the folder ``log/`` [`#102 <https://github.com/PyPSA/pypsa-eur/pull/102>`_].
 
-* The new function ``_helpers.mock_snakemake`` creates a ``snakemake`` object which mimics the actual ``snakemake`` object produced by workflow by parsing the ``Snakefile`` and setting all paths for inputs, outputs, and logs. This allows running all scripts within a (I)python terminal (or just by calling ``python <script-name>``) and thereby facilitates developing and debugging scripts significantly (`#107 <https://github.com/PyPSA/pypsa-eur/pull/107>`_).
+* The new function ``_helpers.mock_snakemake`` creates a ``snakemake`` object which mimics the actual ``snakemake`` object produced by workflow by parsing the ``Snakefile`` and setting all paths for inputs, outputs, and logs. This allows running all scripts within a (I)python terminal (or just by calling ``python <script-name>``) and thereby facilitates developing and debugging scripts significantly [`#107 <https://github.com/PyPSA/pypsa-eur/pull/107>`_].
 
 Release Process
 ===============
@@ -100,8 +191,8 @@ Release Process
 
 * Finalise release notes at ``doc/release_notes.rst``.
 
-* Update ``environment.fixedversions.yaml`` via
-  ``conda env export -n pypsa-eur -f environment.fixedversions.yaml --no-builds``
+* Update ``envs/environment.fixed.yaml`` via
+  ``conda env export -n pypsa-eur -f envs/environment.fixed.yaml --no-builds``
   from an up-to-date `pypsa-eur` environment.
 
 * Update version number in ``doc/conf.py`` and ``*config.*.yaml``.
@@ -111,10 +202,10 @@ Release Process
 
 * Tag a release on Github via ``git tag v0.x.x``, ``git push``, ``git push --tags``. Include release notes in the tag message.
 
-* Upload code to `zenodo code repository <https://doi.org/10.5281/zenodo.3520875>`_ with `GNU GPL 3.0 <https://www.gnu.org/licenses/gpl-3.0.en.html>`_ license.
+* Upload code to `zenodo code repository <https://doi.org/10.5281/zenodo.3520874>`_ with `GNU GPL 3.0 <https://www.gnu.org/licenses/gpl-3.0.en.html>`_ license.
 
-* Create pre-built networks for ``config.default.yaml`` by running ``snakemake -j 1 extra_components_all_elec_networks``.
+* Create pre-built networks for ``config.default.yaml`` by running ``snakemake -j 1 extra_components_all_networks``.
 
-* Upload pre-built networks to `zenodo data repository <https://doi.org/10.5281/zenodo.3601882>`_ with `CC BY 4.0 <https://creativecommons.org/licenses/by/4.0/>`_ license.
+* Upload pre-built networks to `zenodo data repository <https://doi.org/10.5281/zenodo.3601881>`_ with `CC BY 4.0 <https://creativecommons.org/licenses/by/4.0/>`_ license.
 
 * Send announcement on the `PyPSA and PyPSA-Eur mailing list <https://groups.google.com/forum/#!forum/pypsa>`_.

doc/simplification.rst

@@ -22,7 +22,7 @@ After simplification and clustering of the network, additional components may be
 
 .. toctree::
    :caption: Overview
-   
+
    simplification/simplify_network
    simplification/cluster_network
    simplification/add_extra_components

doc/solving.rst

@@ -7,7 +7,7 @@
 Solving Networks
 ##########################################
 
-After generating and simplifying the networks they can be solved through the rule :mod:`solve_network`  by using the collection rule :mod:`solve_all_elec_networks`. Moreover, networks can be solved for another focus with the derivative rules :mod:`solve_network`  by using the collection rule :mod:`solve_operations_network` for dispatch-only analyses on an already solved network.
+After generating and simplifying the networks they can be solved through the rule :mod:`solve_network`  by using the collection rule :mod:`solve_all_networks`. Moreover, networks can be solved for another focus with the derivative rules :mod:`solve_network`  by using the collection rule :mod:`solve_operations_network` for dispatch-only analyses on an already solved network.
 
 .. toctree::
    :caption: Overview

doc/tutorial.rst

@@ -1,6 +1,6 @@
 ..
   SPDX-FileCopyrightText: 2019-2020 The PyPSA-Eur Authors
-  
+
   SPDX-License-Identifier: CC-BY-4.0
 
 .. _tutorial:
@@ -47,47 +47,47 @@ The model can be adapted to only include selected countries (e.g. Germany) inste
 
 .. literalinclude:: ../config.tutorial.yaml
    :language: yaml
-   :lines: 16
-   
+   :lines: 20
+
 Likewise, the example's temporal scope can be restricted (e.g. to a single month).
 
 .. literalinclude:: ../config.tutorial.yaml
    :language: yaml
-   :lines: 18-21
+   :lines: 22-25
 
 It is also possible to allow less or more carbon-dioxide emissions. Here, we limit the emissions of Germany 100 Megatonnes per year.
 
 .. literalinclude:: ../config.tutorial.yaml
    :language: yaml
-   :lines: 33
+   :lines: 36,38
 
 PyPSA-Eur also includes a database of existing conventional powerplants.
 We can select which types of powerplants we like to be included with fixed capacities:
 
 .. literalinclude:: ../config.tutorial.yaml
    :language: yaml
-   :lines: 47
+   :lines: 36,52
 
 To accurately model the temporal and spatial availability of renewables such as wind and solar energy, we rely on historical weather data.
 It is advisable to adapt the required range of coordinates to the selection of countries.
 
 .. literalinclude:: ../config.tutorial.yaml
    :language: yaml
-   :lines: 49-57
+   :lines: 54-62
 
 We can also decide which weather data source should be used to calculate potentials and capacity factor time-series for each carrier.
 For example, we may want to use the ERA-5 dataset for solar and not the default SARAH-2 dataset.
 
 .. literalinclude:: ../config.tutorial.yaml
    :language: yaml
-   :lines: 59,102-103
+   :lines: 64,107-108
 
 Finally, it is possible to pick a solver. For instance, this tutorial uses the open-source solvers CBC and Ipopt and does not rely
 on the commercial solvers Gurobi or CPLEX (for which free academic licenses are available).
 
 .. literalinclude:: ../config.tutorial.yaml
    :language: yaml
-   :lines: 158,167-168
+   :lines: 170,180-181
 
 .. note::
 
@@ -119,8 +119,8 @@ orders ``snakemake`` to run the script ``solve_network`` that produces the solve
 .. code::
 
     rule solve_network:
-        input: "networks/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc"
-        output: "results/networks/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc"
+        input: "networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc"
+        output: "results/networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc"
         [...]
         script: "scripts/solve_network.py"
 
@@ -129,10 +129,10 @@ orders ``snakemake`` to run the script ``solve_network`` that produces the solve
 .. warning::
     On Windows the previous command may currently cause a ``MissingRuleException`` due to problems with output files in subfolders.
     This is an `open issue <https://github.com/snakemake/snakemake/issues/46>`_ at `snakemake <https://snakemake.readthedocs.io/>`_.
-    Windows users should add the option ``--keep-target-files`` to the command or instead run ``snakemake -j 1 solve_all_elec_networks``.
+    Windows users should add the option ``--keep-target-files`` to the command or instead run ``snakemake -j 1 solve_all_networks``.
 
 This triggers a workflow of multiple preceding jobs that depend on each rule's inputs and outputs:
-    
+
 .. graphviz::
     :align: center
 
@@ -184,7 +184,7 @@ This triggers a workflow of multiple preceding jobs that depend on each rule's i
         7 -> 11
         5 -> 11
         12 -> 11
-    } 
+    }
 
 |
 
@@ -229,8 +229,8 @@ A job (here ``simplify_network``) will display its attributes and normally some
     INFO:__main__:Mapping all network lines onto a single 380kV layer
     INFO:__main__:Simplifying connected link components
     INFO:__main__:Removing stubs
-    INFO:__main__:Displacing offwind-ac generator(s) and adding connection costs to capital_costs: 20128 Eur/MW/a for `5718 offwind-ac` 
-    INFO:__main__:Displacing offwind-dc generator(s) and adding connection costs to capital_costs: 14994 Eur/MW/a for `5718 offwind-dc`, 26939 Eur/MW/a for `5724 offwind-dc`, 29621 Eur/MW/a for `5725 offwind-dc` 
+    INFO:__main__:Displacing offwind-ac generator(s) and adding connection costs to capital_costs: 20128 Eur/MW/a for `5718 offwind-ac`
+    INFO:__main__:Displacing offwind-dc generator(s) and adding connection costs to capital_costs: 14994 Eur/MW/a for `5718 offwind-dc`, 26939 Eur/MW/a for `5724 offwind-dc`, 29621 Eur/MW/a for `5725 offwind-dc`
     INFO:pypsa.io:Exported network elec_s.nc has lines, carriers, links, storage_units, loads, buses, generators
     [<DATETIME>]
     Finished job 3.
@@ -271,7 +271,7 @@ the wildcards given in ``scenario`` in the configuration file ``config.yaml`` ar
 
 .. literalinclude:: ../config.tutorial.yaml
    :language: yaml
-   :lines: 7-12
+   :lines: 14-18
 
 In this example we would not only solve a 6-node model of Germany but also a 2-node model.
 
@@ -286,12 +286,4 @@ The solved networks can be analysed just like any other PyPSA network (e.g. in J
 
     network = pypsa.Network("results/networks/elec_s_6_ec_lcopt_Co2L-24H.nc")
 
-    ...
-
 For inspiration, read the `examples section in the PyPSA documentation <https://pypsa.readthedocs.io/en/latest/examples.html>`_.
-
-.. note::
-
-    There are rules for summaries and plotting available in the repository of PyPSA-Eur.
-    
-    They are currently under revision and therefore not yet documented. 

doc/wildcards.rst

@@ -18,16 +18,6 @@ what data to retrieve and what files to produce.
 Detailed explanations of how wildcards work in ``snakemake`` can be found in the
 `relevant section of the documentation <https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#wildcards>`_.
 
-.. _network:
-
-The ``{network}`` wildcard
-==========================
-
-The ``{network}`` wildcard specifies the considered energy sector(s)
-and, as currently only ``elec`` (for electricity) is included,
-it currently represents rather a placeholder wildcard to facilitate
-future extensions including multiple energy sectors at once.
-
 .. _simpl:
 
 The ``{simpl}`` wildcard
@@ -37,9 +27,6 @@ The ``{simpl}`` wildcard specifies number of buses a detailed
 network model should be pre-clustered to in the rule
 :mod:`simplify_network` (before :mod:`cluster_network`).
 
-.. seealso::
-    :mod:`simplify_network`
-
 .. _clusters:
 
 The ``{clusters}`` wildcard
@@ -55,9 +42,6 @@ If an `m` is placed behind the number of clusters (e.g. ``100m``),
 generators are only moved to the clustered buses but not aggregated
 by carrier; i.e. the clustered bus may have more than one e.g. wind generator.
 
-.. seealso::
-    :mod:`cluster_network`
-
 .. _ll:
 
 The ``{ll}`` wildcard
@@ -75,7 +59,7 @@ The wildcard, in general, consists of two parts:
 
     2. The second part can be
        ``opt`` or a float bigger than one (e.g. 1.25).
-       
+
        (a) If ``opt`` is chosen line expansion is optimised
            according to its capital cost
            (where the choice ``v`` only considers overhead costs for HVDC transmission lines, while
@@ -84,14 +68,11 @@ The wildcard, in general, consists of two parts:
 
        (b) ``v1.25`` will limit the total volume of line expansion
            to 25 % of currently installed capacities weighted by
-           individual line lengths; investment costs are neglected. 
+           individual line lengths; investment costs are neglected.
 
        (c) ``c1.25`` will allow to build a transmission network that
            costs no more than 25 % more than the current system.
 
-.. seealso::
-    :mod:`prepare_network`
-
 .. _opts:
 
 The ``{opts}`` wildcard
@@ -108,21 +89,18 @@ It may hold multiple triggers separated by ``-``, i.e. ``Co2L-3H`` contains the
    :widths: 10,20,10,10
    :file: configtables/opts.csv
 
-.. seealso::
-    :mod:`prepare_network`, :mod:`solve_network`
-
 .. _country:
 
 The ``{country}`` wildcard
 ==========================
 
-The rules ``make_summary`` and ``plot_summary`` (generating summaries of all or a subselection
-of the solved networks) as well as ``plot_p_nom_max`` (for plotting the cumulative
+The rules :mod:`make_summary` and :mod:`plot_summary` (generating summaries of all or a subselection
+of the solved networks) as well as :mod:`plot_p_nom_map` (for plotting the cumulative
 generation potentials for renewable technologies) can be narrowed to
 individual countries using the ``{country}`` wildcard.
 
-If ``country = all``, then the rule acts on the network for all countries
-defined in ``config.yaml``. If otherwise ``country = DE`` or another 2-letter
+If ``country=all``, then the rule acts on the network for all countries
+defined in ``config.yaml``. If otherwise ``country=DE`` or another 2-letter
 country code, then the network is narrowed to buses of this country
 for the rule. For example to get a summary of the energy generated
 in Germany (in the solution for Europe) use:
@@ -131,9 +109,6 @@ in Germany (in the solution for Europe) use:
 
     snakemake -j 1 results/summaries/elec_s_all_lall_Co2L-3H_DE
 
-.. seealso::
-    :mod:`make_summary`, :mod:`plot_summary`, :mod:`plot_p_nom_max`
-
 .. _cutout_wc:
 
 The ``{cutout}`` wildcard
@@ -143,9 +118,6 @@ The ``{cutout}`` wildcard facilitates running the rule :mod:`build_cutout`
 for all cutout configurations specified under ``atlite: cutouts:``.
 These cutouts will be stored in a folder specified by ``{cutout}``.
 
-.. seealso::
-    :mod:`build_cutout`, :ref:`atlite_cf`
-
 .. _technology:
 
 The ``{technology}`` wildcard
@@ -161,22 +133,16 @@ For instance ``{technology}`` can be used to plot regionally disaggregated poten
 with the rule :mod:`plot_p_nom_max` or to summarize a particular technology's
 full load hours in various countries with the rule :mod:`build_country_flh`.
 
-.. seealso::
-    :mod:`build_renewable_profiles`, :mod:`plot_p_nom_max`, :mod:`build_country_flh`
-
 .. _attr:
 
 The ``{attr}`` wildcard
 =======================
 
-The ``{attr}`` wildcard specifies which attribute are used for size
+The ``{attr}`` wildcard specifies which attribute is used for size
 representations of network components on a map plot produced by the rule
-``plot_network``. While it might be extended in the future, ``{attr}``
+:mod:`plot_network`. While it might be extended in the future, ``{attr}``
 currently only supports plotting of ``p_nom``.
 
-.. seealso::
-    :mod:`plot_network`
-
 .. _ext:
 
 The ``{ext}`` wildcard
@@ -191,6 +157,3 @@ formats depends on the used backend. To query the supported file types on your s
 
     import matplotlib.pyplot as plt
     plt.gcf().canvas.get_supported_filetypes()
-
-.. seealso::
-    :mod:`plot_network`, :mod:`plot_summary`, :mod:`plot_p_nom_max`

environment.fixedversions.yaml

@@ -1,241 +0,0 @@
-# SPDX-FileCopyrightText: : 2017-2020 The PyPSA-Eur Authors
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-name: pypsa-eur
-channels:
-  - bioconda
-  - gurobi
-  - conda-forge
-  - defaults
-dependencies:
-  - _libgcc_mutex=0.1
-  - affine=2.3.0
-  - appdirs=1.4.3
-  - atlite=0.0.3
-  - attrs=19.3.0
-  - backcall=0.1.0
-  - beautifulsoup4=4.9.1
-  - blas=1.0
-  - blosc=1.16.3
-  - bokeh=2.0.2
-  - bottleneck=1.3.2
-  - bzip2=1.0.8
-  - ca-certificates=2020.1.1
-  - cairo=1.14.12
-  - cartopy=0.17.0
-  - certifi=2020.4.5.1
-  - cffi=1.14.0
-  - cfitsio=3.470
-  - cftime=1.1.2
-  - chardet=3.0.4
-  - click=7.1.2
-  - click-plugins=1.1.1
-  - cligj=0.5.0
-  - cloudpickle=1.4.1
-  - coincbc=2.10.5
-  - configargparse=1.1
-  - cryptography=2.9.2
-  - curl=7.67.0
-  - cycler=0.10.0
-  - cytoolz=0.10.1
-  - dask=2.17.2
-  - dask-core=2.17.2
-  - datrie=0.8.2
-  - dbus=1.13.14
-  - decorator=4.4.2
-  - distributed=2.17.0
-  - docutils=0.16
-  - entsoe-py=0.2.10
-  - expat=2.2.6
-  - fiona=1.8.11
-  - fontconfig=2.13.0
-  - freetype=2.9.1
-  - freexl=1.0.5
-  - fsspec=0.7.4
-  - gdal=3.0.2
-  - geographiclib=1.50
-  - geopandas=0.6.1
-  - geopy=1.22.0
-  - geos=3.8.0
-  - geotiff=1.5.1
-  - giflib=5.1.4
-  - gitdb=4.0.2
-  - gitpython=3.1.1
-  - glib=2.63.1
-  - gst-plugins-base=1.14.0
-  - gstreamer=1.14.0
-  - gurobi=9.0.2
-  - hdf4=4.2.13
-  - hdf5=1.10.4
-  - heapdict=1.0.1
-  - icu=58.2
-  - idna=2.9
-  - importlib-metadata=1.6.0
-  - importlib_metadata=1.6.0
-  - intel-openmp=2020.1
-  - ipopt=3.13.2
-  - ipython=7.13.0
-  - ipython_genutils=0.2.0
-  - jedi=0.17.0
-  - jinja2=2.11.2
-  - joblib=0.15.1
-  - jpeg=9b
-  - json-c=0.13.1
-  - jsonschema=3.2.0
-  - jupyter_core=4.6.3
-  - kealib=1.4.7
-  - kiwisolver=1.2.0
-  - krb5=1.16.4
-  - ld_impl_linux-64=2.33.1
-  - libblas=3.8.0
-  - libboost=1.67.0
-  - libcblas=3.8.0
-  - libcurl=7.67.0
-  - libdap4=3.19.1
-  - libedit=3.1.20181209
-  - libffi=3.3
-  - libgcc-ng=9.1.0
-  - libgdal=3.0.2
-  - libgfortran-ng=7.3.0
-  - libkml=1.3.0
-  - liblapack=3.8.0
-  - libnetcdf=4.6.1
-  - libpng=1.6.37
-  - libpq=11.5
-  - libspatialindex=1.9.3
-  - libspatialite=4.3.0a
-  - libssh2=1.9.0
-  - libstdcxx-ng=9.1.0
-  - libtiff=4.1.0
-  - libuuid=1.0.3
-  - libxcb=1.13
-  - libxml2=2.9.9
-  - libxslt=1.1.33
-  - locket=0.2.0
-  - lxml=4.5.0
-  - lz4-c=1.8.1.2
-  - lzo=2.10
-  - markupsafe=1.1.1
-  - matplotlib=3.1.3
-  - matplotlib-base=3.1.3
-  - memory_profiler=0.55.0
-  - metis=5.1.0
-  - mkl=2020.1
-  - mkl-service=2.3.0
-  - mkl_fft=1.0.15
-  - mkl_random=1.1.1
-  - mock=4.0.2
-  - more-itertools=8.3.0
-  - msgpack-python=1.0.0
-  - munch=2.5.0
-  - nbformat=5.0.6
-  - ncurses=6.2
-  - netcdf4=1.4.2
-  - networkx=2.4
-  - nose=1.3.7
-  - numexpr=2.7.1
-  - numpy=1.18.1
-  - numpy-base=1.18.1
-  - olefile=0.46
-  - openjpeg=2.3.0
-  - openssl=1.1.1g
-  - owslib=0.19.2
-  - packaging=20.3
-  - pandas=1.0.3
-  - parso=0.7.0
-  - partd=1.1.0
-  - pcre=8.43
-  - pexpect=4.8.0
-  - pickleshare=0.7.5
-  - pillow=7.1.2
-  - pip=20.0.2
-  - pixman=0.38.0
-  - pluggy=0.13.1
-  - ply=3.11
-  - poppler=0.65.0
-  - poppler-data=0.4.9
-  - postgresql=11.5
-  - powerplantmatching=0.4.5
-  - progressbar2=3.37.1
-  - proj=6.2.1
-  - prompt-toolkit=3.0.5
-  - prompt_toolkit=3.0.5
-  - psutil=5.7.0
-  - ptyprocess=0.6.0
-  - py=1.8.1
-  - pycountry=19.8.18
-  - pycparser=2.20
-  - pyepsg=0.4.0
-  - pygments=2.6.1
-  - pykdtree=1.3.1
-  - pyomo=5.6.9
-  - pyopenssl=19.1.0
-  - pyparsing=2.4.7
-  - pyproj=2.6.1.post1
-  - pypsa=0.17.0
-  - pyqt=5.9.2
-  - pyrsistent=0.16.0
-  - pyshp=2.1.0
-  - pysocks=1.7.1
-  - pytables=3.6.1
-  - pytest=5.4.2
-  - pytest-runner=5.2
-  - python=3.7.7
-  - python-dateutil=2.8.1
-  - python-utils=2.3.0
-  - python_abi=3.7
-  - pytz=2020.1
-  - pyutilib=5.8.0
-  - pyyaml=5.3.1
-  - qt=5.9.7
-  - rasterio=1.1.0
-  - ratelimiter=1.2.0
-  - readline=8.0
-  - requests=2.23.0
-  - rtree=0.9.4
-  - scikit-learn=0.22.1
-  - scipy=1.4.1
-  - seaborn=0.10.1
-  - setuptools=47.1.1
-  - shapely=1.7.0
-  - sip=4.19.8
-  - six=1.15.0
-  - smmap=3.0.2
-  - snakemake-minimal=5.19.2
-  - snappy=1.1.7
-  - snuggs=1.4.7
-  - sortedcontainers=2.1.0
-  - soupsieve=2.0.1
-  - sqlite=3.31.1
-  - tbb=2018.0.5
-  - tblib=1.6.0
-  - tiledb=1.6.3
-  - tk=8.6.8
-  - toolz=0.10.0
-  - toposort=1.5
-  - tornado=6.0.4
-  - traitlets=4.3.3
-  - typing_extensions=3.7.4.1
-  - tzcode=2020a
-  - urllib3=1.25.8
-  - wcwidth=0.1.9
-  - wheel=0.34.2
-  - wrapt=1.12.1
-  - xarray=0.15.1
-  - xerces-c=3.2.2
-  - xlrd=1.2.0
-  - xz=5.2.5
-  - yaml=0.1.7
-  - zict=2.0.0
-  - zipp=3.1.0
-  - zlib=1.2.11
-  - zstd=1.3.7
-  - pip:
-    - cdsapi==0.2.7
-    - countrycode==0.2
-    - descartes==1.1.0
-    - geokit==1.1.2
-    - glaes==1.1.2
-    - tqdm==4.46.1
-    - vresutils==0.3.1

envs/environment.docs.yaml

@@ -5,19 +5,17 @@
 name: pypsa-eur-docs
 channels:
   - conda-forge
-  #- bioconda
 dependencies:
-  #- python
+  - python<=3.7
   - pip
   - pypsa>=0.17.1
   - atlite=0.0.3
+  - pre-commit
 
   # Dependencies of the workflow itself
-  #- xlrd
   - scikit-learn
   - pycountry
   - seaborn
-  #- snakemake-minimal
   - memory_profiler
   - yaml
   - pytables
@@ -25,28 +23,19 @@ dependencies:
 
   # Second order dependencies which should really be deps of atlite
   - xarray
-  #- netcdf4
-  #- bottleneck
-  #- toolz
-  #- dask
   - progressbar2
   - pyyaml>=5.1.0
 
-  # Include ipython so that one does not inadvertently drop out of the conda
-  # environment by calling ipython
-  # - ipython
-
   # GIS dependencies have to come all from conda-forge
-  - conda-forge::cartopy
-  - conda-forge::fiona
-  - conda-forge::proj
-  - conda-forge::pyshp
-  - conda-forge::geopandas
-  - conda-forge::rasterio
-  - conda-forge::shapely
-  - conda-forge::libgdal
+  - cartopy
+  - fiona
+  - proj
+  - pyshp
+  - geopandas
+  - rasterio
+  - shapely
+  - libgdal
 
-  # The FRESNA/KIT stuff is not packaged for conda yet
   - pip:
     - vresutils==0.3.1
     - git+https://github.com/PyPSA/glaes.git#egg=glaes

envs/environment.fixed.yaml

@@ -0,0 +1,265 @@
+# SPDX-FileCopyrightText: : 2017-2020 The PyPSA-Eur Authors
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+name: pypsa-eur
+channels:
+  - bioconda
+  - conda-forge
+  - defaults
+dependencies:
+  - _libgcc_mutex=0.1
+  - _openmp_mutex=4.5
+  - affine=2.3.0
+  - amply=0.1.4
+  - appdirs=1.4.4
+  - atlite=0.0.3
+  - attrs=20.3.0
+  - backcall=0.2.0
+  - backports=1.0
+  - backports.functools_lru_cache=1.6.1
+  - beautifulsoup4=4.9.3
+  - blosc=1.20.1
+  - bokeh=2.2.3
+  - boost-cpp=1.72.0
+  - bottleneck=1.3.2
+  - brotlipy=0.7.0
+  - bzip2=1.0.8
+  - c-ares=1.17.1
+  - ca-certificates=2020.11.8
+  - cairo=1.16.0
+  - cartopy=0.17.0
+  - certifi=2020.11.8
+  - cffi=1.14.4
+  - cfitsio=3.470
+  - cftime=1.3.0
+  - chardet=3.0.4
+  - click=7.1.2
+  - click-plugins=1.1.1
+  - cligj=0.7.1
+  - cloudpickle=1.6.0
+  - coincbc=2.10.5
+  - conda=4.9.2
+  - conda-package-handling=1.7.2
+  - configargparse=1.2.3
+  - cryptography=3.2.1
+  - curl=7.71.1
+  - cycler=0.10.0
+  - cytoolz=0.11.0
+  - dask=2.30.0
+  - dask-core=2.30.0
+  - datrie=0.8.2
+  - decorator=4.4.2
+  - descartes=1.1.0
+  - distributed=2.30.1
+  - docutils=0.16
+  - entsoe-py=0.2.10
+  - expat=2.2.9
+  - fiona=1.8.13
+  - fontconfig=2.13.1
+  - freetype=2.10.4
+  - freexl=1.0.5
+  - fsspec=0.8.4
+  - gdal=3.0.4
+  - geographiclib=1.50
+  - geopandas=0.8.1
+  - geopy=2.0.0
+  - geos=3.8.1
+  - geotiff=1.6.0
+  - gettext=0.19.8.1
+  - giflib=5.2.1
+  - gitdb=4.0.5
+  - gitpython=3.1.11
+  - glib=2.66.3
+  - glpk=4.65
+  - gmp=6.2.1
+  - hdf4=4.2.13
+  - hdf5=1.10.6
+  - heapdict=1.0.1
+  - icu=64.2
+  - idna=2.10
+  - importlib-metadata=3.1.1
+  - importlib_metadata=3.1.1
+  - ipopt=3.13.2
+  - ipython=7.19.0
+  - ipython_genutils=0.2.0
+  - jedi=0.17.2
+  - jinja2=2.11.2
+  - joblib=0.17.0
+  - jpeg=9d
+  - json-c=0.13.1
+  - jsonschema=3.2.0
+  - jupyter_core=4.7.0
+  - kealib=1.4.14
+  - kiwisolver=1.3.1
+  - krb5=1.17.2
+  - lcms2=2.11
+  - ld_impl_linux-64=2.35.1
+  - libarchive=3.3.3
+  - libblas=3.9.0
+  - libcblas=3.9.0
+  - libcurl=7.71.1
+  - libdap4=3.20.6
+  - libedit=3.1.20191231
+  - libev=4.33
+  - libffi=3.3
+  - libgcc-ng=9.3.0
+  - libgdal=3.0.4
+  - libgfortran-ng=7.5.0
+  - libgfortran4=7.5.0
+  - libgfortran5=9.3.0
+  - libglib=2.66.3
+  - libgomp=9.3.0
+  - libiconv=1.16
+  - libkml=1.3.0
+  - liblapack=3.9.0
+  - libnetcdf=4.7.4
+  - libnghttp2=1.41.0
+  - libopenblas=0.3.12
+  - libpng=1.6.37
+  - libpq=12.3
+  - libsolv=0.7.16
+  - libspatialindex=1.9.3
+  - libspatialite=4.3.0a
+  - libssh2=1.9.0
+  - libstdcxx-ng=9.3.0
+  - libtiff=4.1.0
+  - libuuid=2.32.1
+  - libwebp-base=1.1.0
+  - libxcb=1.13
+  - libxml2=2.9.10
+  - libxslt=1.1.33
+  - locket=0.2.0
+  - lxml=4.6.2
+  - lz4-c=1.9.2
+  - lzo=2.10
+  - mamba=0.7.3
+  - markupsafe=1.1.1
+  - matplotlib-base=3.3.3
+  - memory_profiler=0.58.0
+  - metis=5.1.0
+  - mock=4.0.2
+  - msgpack-python=1.0.0
+  - munch=2.5.0
+  - nbformat=5.0.8
+  - ncurses=6.2
+  - netcdf4=1.5.4
+  - networkx=2.5
+  - nose=1.3.7
+  - numexpr=2.7.1
+  - numpy=1.19.0
+  - olefile=0.46
+  - openjpeg=2.3.1
+  - openssl=1.1.1h
+  - owslib=0.20.0
+  - packaging=20.7
+  - pandas=1.1.4
+  - parso=0.7.1
+  - partd=1.1.0
+  - patsy=0.5.1
+  - pcre=8.44
+  - pexpect=4.8.0
+  - pickleshare=0.7.5
+  - pillow=8.0.1
+  - pip=20.3.1
+  - pixman=0.38.0
+  - ply=3.11
+  - poppler=0.87.0
+  - poppler-data=0.4.10
+  - postgresql=12.3
+  - powerplantmatching=0.4.8
+  - progressbar2=3.53.1
+  - proj=7.0.0
+  - prompt-toolkit=3.0.8
+  - psutil=5.7.3
+  - pthread-stubs=0.4
+  - ptyprocess=0.6.0
+  - pulp=2.3.1
+  - pycosat=0.6.3
+  - pycountry=20.7.3
+  - pycparser=2.20
+  - pyepsg=0.4.0
+  - pygments=2.7.2
+  - pykdtree=1.3.4
+  - pyomo=5.7.1
+  - pyopenssl=20.0.0
+  - pyparsing=2.4.7
+  - pyproj=2.6.1.post1
+  - pypsa=0.17.1
+  - pyrsistent=0.17.3
+  - pyshp=2.1.2
+  - pysocks=1.7.1
+  - pytables=3.6.1
+  - python=3.8.6
+  - python-dateutil=2.8.1
+  - python-utils=2.4.0
+  - python_abi=3.8
+  - pytz=2020.4
+  - pyutilib=6.0.0
+  - pyyaml=5.3.1
+  - rasterio=1.1.5
+  - ratelimiter=1.2.0
+  - readline=8.0
+  - reproc=14.2.1
+  - reproc-cpp=14.2.1
+  - requests=2.25.0
+  - rtree=0.9.4
+  - ruamel_yaml=0.15.80
+  - scikit-learn=0.23.2
+  - scipy=1.5.3
+  - seaborn=0.11.0
+  - seaborn-base=0.11.0
+  - setuptools=49.6.0
+  - shapely=1.7.1
+  - six=1.15.0
+  - smmap=3.0.4
+  - snakemake-minimal=5.30.1
+  - snuggs=1.4.7
+  - sortedcontainers=2.3.0
+  - soupsieve=2.0.1
+  - sqlite=3.34.0
+  - statsmodels=0.12.1
+  - tbb=2020.2
+  - tblib=1.6.0
+  - threadpoolctl=2.1.0
+  - tiledb=1.7.7
+  - tk=8.6.10
+  - toolz=0.11.1
+  - toposort=1.5
+  - tornado=6.1
+  - tqdm=4.54.1
+  - traitlets=5.0.5
+  - typing_extensions=3.7.4.3
+  - tzcode=2020a
+  - urllib3=1.25.11
+  - wcwidth=0.2.5
+  - wheel=0.36.1
+  - wrapt=1.12.1
+  - xarray=0.16.2
+  - xerces-c=3.2.2
+  - xlrd=1.2.0
+  - xorg-kbproto=1.0.7
+  - xorg-libice=1.0.10
+  - xorg-libsm=1.2.3
+  - xorg-libx11=1.6.12
+  - xorg-libxau=1.0.9
+  - xorg-libxdmcp=1.1.3
+  - xorg-libxext=1.3.4
+  - xorg-libxrender=0.9.10
+  - xorg-renderproto=0.11.1
+  - xorg-xextproto=7.3.0
+  - xorg-xproto=7.0.31
+  - xz=5.2.5
+  - yaml=0.2.5
+  - zict=2.0.0
+  - zipp=3.4.0
+  - zlib=1.2.11
+  - zstd=1.4.5
+  - pip:
+    - cdsapi==0.4.0
+    - countrycode==0.2
+    - geokit==1.1.2
+    - glaes==1.1.2
+    - sklearn==0.0
+    - tsam==1.1.0
+    - vresutils==0.3.1

envs/environment.yaml

@@ -4,19 +4,20 @@
 
 name: pypsa-eur
 channels:
-  - defaults
   - conda-forge
   - bioconda
   - http://conda.anaconda.org/gurobi
 dependencies:
   - python
   - pip
+  - mamba # esp for windows build
 
   - pypsa>=0.17.1
   - atlite=0.0.3
 
   # Dependencies of the workflow itself
   - xlrd
+  - openpyxl
   - scikit-learn
   - pycountry
   - seaborn
@@ -25,7 +26,8 @@ dependencies:
   - yaml
   - pytables
   - lxml
-  - powerplantmatching>=0.4.3
+  - powerplantmatching>=0.4.8
+  - numpy<=1.19.0 # otherwise macos fails
 
   # Second order dependencies which should really be deps of atlite
   - xarray
@@ -36,8 +38,7 @@ dependencies:
   - progressbar2
   - pyyaml>=5.1.0
 
-  # Include ipython so that one does not inadvertently drop out of the conda
-  # environment by calling ipython
+  # Keep in conda environment when calling ipython
   - ipython
 
   # GIS dependencies:
@@ -48,13 +49,12 @@ dependencies:
   - geopandas
   - rasterio
   - shapely
-  - libgdal
-
-  # Solvers
-  - gurobi:gurobi # until https://github.com/conda-forge/pypsa-feedstock/issues/4 closed
+  - libgdal<=3.0.4
+  - descartes
 
   - pip:
     - vresutils==0.3.1
+    - tsam>=1.1.0
     - git+https://github.com/PyPSA/glaes.git#egg=glaes
     - git+https://github.com/PyPSA/geokit.git#egg=geokit
     - cdsapi

scripts/_helpers.py

@@ -44,6 +44,7 @@ def configure_logging(snakemake, skip_handlers=False):
             })
     logging.basicConfig(**kwargs)
 
+
 def load_network(import_name=None, custom_components=None):
     """
     Helper for importing a pypsa.Network with additional custom components.
@@ -70,7 +71,6 @@ def load_network(import_name=None, custom_components=None):
     -------
     pypsa.Network
     """
-
     import pypsa
     from pypsa.descriptors import Dict
 
@@ -90,10 +90,12 @@ def load_network(import_name=None, custom_components=None):
                          override_components=override_components,
                          override_component_attrs=override_component_attrs)
 
+
 def pdbcast(v, h):
     return pd.DataFrame(v.values.reshape((-1, 1)) * h.values,
                         index=v.index, columns=h.index)
 
+
 def load_network_for_plots(fn, tech_costs, config, combine_hydro_ps=True):
     import pypsa
     from add_electricity import update_transmission_costs, load_costs
@@ -113,11 +115,11 @@ def load_network_for_plots(fn, tech_costs, config, combine_hydro_ps=True):
     if combine_hydro_ps:
         n.storage_units.loc[n.storage_units.carrier.isin({'PHS', 'hydro'}), 'carrier'] = 'hydro+PHS'
 
-    # #if the carrier was not set on the heat storage units
+    # if the carrier was not set on the heat storage units
     # bus_carrier = n.storage_units.bus.map(n.buses.carrier)
     # n.storage_units.loc[bus_carrier == "heat","carrier"] = "water tanks"
 
-    Nyears = n.snapshot_weightings.sum()/8760.
+    Nyears = n.snapshot_weightings.sum() / 8760.
     costs = load_costs(Nyears, tech_costs, config['costs'], config['electricity'])
     update_transmission_costs(n, costs)
 
@@ -168,6 +170,7 @@ def aggregate_costs(n, flatten=False, opts=None, existing_only=False):
         n.iterate_components(iterkeys(components), skip_empty=False),
         itervalues(components)
     ):
+        if c.df.empty: continue
         if not existing_only: p_nom += "_opt"
         costs[(c.list_name, 'capital')] = (c.df[p_nom] * c.df.capital_cost).groupby(c.df.carrier).sum()
         if p_attr is not None:

scripts/add_electricity.py

@@ -24,13 +24,13 @@ Relevant Settings
         conventional_carriers:
         co2limit:
         extendable_carriers:
-            Generator:
+        include_renewable_capacities_from_OPSD:
         estimate_renewable_capacities_from_capacity_stats:
 
     load:
         scaling_factor:
 
-    renewable: (keys)
+    renewable:
         hydro:
             carriers:
             hydro_max_hours:
@@ -52,15 +52,8 @@ Inputs
     .. image:: ../img/hydrocapacities.png
         :scale: 34 %
 
-- ``data/geth2015_hydro_capacities.csv``: alternative to capacities above; NOT CURRENTLY USED!
-- ``data/bundle/time_series_60min_singleindex_filtered.csv``: Hourly per-country load profiles since 2010 from the `ENTSO-E statistical database <https://www.entsoe.eu/data/power-stats/hourly_load/>`_
-
-    .. image:: ../img/load-box.png
-        :scale: 33 %
-
-    .. image:: ../img/load-ts.png
-        :scale: 33 %
-
+- ``data/geth2015_hydro_capacities.csv``: alternative to capacities above; not currently used!
+- ``resources/opsd_load.csv`` Hourly per-country load profiles.
 - ``resources/regions_onshore.geojson``: confer :ref:`busregions`
 - ``resources/nuts3_shapes.geojson``: confer :ref:`shapes`
 - ``resources/powerplants.csv``: confer :ref:`powerplants`
@@ -90,25 +83,28 @@ It further adds extendable ``generators`` with **zero** capacity for
 - additional open- and combined-cycle gas turbines (if ``OCGT`` and/or ``CCGT`` is listed in the config setting ``electricity: extendable_carriers``)
 """
 
-from vresutils.load import timeseries_opsd
-from vresutils import transfer as vtransfer
-
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import configure_logging
 
+import pypsa
 import pandas as pd
 import numpy as np
 import xarray as xr
 import geopandas as gpd
-import pypsa
-import powerplantmatching as ppm
+import powerplantmatching as pm
+from powerplantmatching.export import map_country_bus
+
+from vresutils.load import timeseries_opsd
+from vresutils import transfer as vtransfer
 
 idx = pd.IndexSlice
 
+logger = logging.getLogger(__name__)
+
 
 def normed(s): return s/s.sum()
 
+
 def _add_missing_carriers_from_costs(n, costs, carriers):
     missing_carriers = pd.Index(carriers).difference(n.carriers.index)
     if missing_carriers.empty: return
@@ -169,13 +165,10 @@ def load_costs(Nyears=1., tech_costs=None, config=None, elec_config=None):
 
     def costs_for_storage(store, link1, link2=None, max_hours=1.):
         capital_cost = link1['capital_cost'] + max_hours * store['capital_cost']
-        efficiency = link1['efficiency']**0.5
         if link2 is not None:
             capital_cost += link2['capital_cost']
-            efficiency *= link2['efficiency']**0.5
         return pd.Series(dict(capital_cost=capital_cost,
                               marginal_cost=0.,
-                              efficiency=efficiency,
                               co2_emissions=0.))
 
     if elec_config is None:
@@ -196,10 +189,11 @@ def load_costs(Nyears=1., tech_costs=None, config=None, elec_config=None):
 
     return costs
 
+
 def load_powerplants(ppl_fn=None):
     if ppl_fn is None:
         ppl_fn = snakemake.input.powerplants
-    carrier_dict = {'ocgt': 'OCGT', 'ccgt': 'CCGT', 'bioenergy':'biomass',
+    carrier_dict = {'ocgt': 'OCGT', 'ccgt': 'CCGT', 'bioenergy': 'biomass',
                     'ccgt, thermal': 'CCGT', 'hard coal': 'coal'}
     return (pd.read_csv(ppl_fn, index_col=0, dtype={'bus': 'str'})
             .powerplant.to_pypsa_names()
@@ -207,27 +201,19 @@ def load_powerplants(ppl_fn=None):
             .replace({'carrier': carrier_dict}))
 
 
-# =============================================================================
-# Attach components
-# =============================================================================
-
-# ### Load
-
 def attach_load(n):
     substation_lv_i = n.buses.index[n.buses['substation_lv']]
     regions = (gpd.read_file(snakemake.input.regions).set_index('name')
                .reindex(substation_lv_i))
-    opsd_load = (timeseries_opsd(slice(*n.snapshots[[0,-1]].year.astype(str)),
-                                 snakemake.input.opsd_load) *
-                 snakemake.config.get('load', {}).get('scaling_factor', 1.0))
+    opsd_load = (pd.read_csv(snakemake.input.load, index_col=0, parse_dates=True)
+                .filter(items=snakemake.config['countries']))
 
-    # Convert to naive UTC (has to be explicit since pandas 0.24)
-    opsd_load.index = opsd_load.index.tz_localize(None)
+    scaling = snakemake.config.get('load', {}).get('scaling_factor', 1.0)
+    logger.info(f"Load data scaled with scalling factor {scaling}.")
+    opsd_load *= scaling
 
     nuts3 = gpd.read_file(snakemake.input.nuts3_shapes).set_index('index')
 
-    def normed(x): return x.divide(x.sum())
-
     def upsample(cntry, group):
         l = opsd_load[cntry]
         if len(group) == 1:
@@ -242,7 +228,8 @@ def attach_load(n):
                               index=group.index)
 
             # relative factors 0.6 and 0.4 have been determined from a linear
-            # regression on the country to continent load data (refer to vresutils.load._upsampling_weights)
+            # regression on the country to continent load data
+            # (refer to vresutils.load._upsampling_weights)
             factors = normed(0.6 * normed(gdp_n) + 0.4 * normed(pop_n))
             return pd.DataFrame(factors.values * l.values[:,np.newaxis],
                                 index=l.index, columns=factors.index)
@@ -252,7 +239,6 @@ def attach_load(n):
 
     n.madd("Load", substation_lv_i, bus=substation_lv_i, p_set=load)
 
-### Set line costs
 
 def update_transmission_costs(n, costs, length_factor=1.0, simple_hvdc_costs=False):
     n.lines['capital_cost'] = (n.lines['length'] * length_factor *
@@ -261,6 +247,11 @@ def update_transmission_costs(n, costs, length_factor=1.0, simple_hvdc_costs=Fal
     if n.links.empty: return
 
     dc_b = n.links.carrier == 'DC'
+
+    # If there are no dc links, then the 'underwater_fraction' column
+    # may be missing. Therefore we have to return here.
+    if n.links.loc[dc_b].empty: return
+
     if simple_hvdc_costs:
         costs = (n.links.loc[dc_b, 'length'] * length_factor *
                  costs.at['HVDC overhead', 'capital_cost'])
@@ -273,7 +264,6 @@ def update_transmission_costs(n, costs, length_factor=1.0, simple_hvdc_costs=Fal
                 costs.at['HVDC inverter pair', 'capital_cost'])
     n.links.loc[dc_b, 'capital_cost'] = costs
 
-### Generators
 
 def attach_wind_and_solar(n, costs):
     for tech in snakemake.config['renewable']:
@@ -312,15 +302,17 @@ def attach_wind_and_solar(n, costs):
                    p_max_pu=ds['profile'].transpose('time', 'bus').to_pandas())
 
 
-
 def attach_conventional_generators(n, costs, ppl):
     carriers = snakemake.config['electricity']['conventional_carriers']
+
     _add_missing_carriers_from_costs(n, costs, carriers)
+
     ppl = (ppl.query('carrier in @carriers').join(costs, on='carrier')
            .rename(index=lambda s: 'C' + str(s)))
 
-    logger.info('Adding {} generators with capacities\n{}'
+    logger.info('Adding {} generators with capacities [MW] \n{}'
                 .format(len(ppl), ppl.groupby('carrier').p_nom.sum()))
+
     n.madd("Generator", ppl.index,
            carrier=ppl.carrier,
            bus=ppl.bus,
@@ -328,6 +320,7 @@ def attach_conventional_generators(n, costs, ppl):
            efficiency=ppl.efficiency,
            marginal_cost=ppl.marginal_cost,
            capital_cost=0)
+
     logger.warning(f'Capital costs for conventional generators put to 0 EUR/MW.')
 
 
@@ -346,7 +339,7 @@ def attach_hydro(n, costs, ppl):
 
     country = ppl['bus'].map(n.buses.country).rename("country")
 
-    inflow_idx = ror.index | hydro.index
+    inflow_idx = ror.index.union(hydro.index)
     if not inflow_idx.empty:
         dist_key = ppl.loc[inflow_idx, 'p_nom'].groupby(country).transform(normed)
 
@@ -377,8 +370,8 @@ def attach_hydro(n, costs, ppl):
                          .where(lambda df: df<=1., other=1.)))
 
     if 'PHS' in carriers and not phs.empty:
-        # fill missing max hours to config value and assume no natural inflow
-        # due to lack of data
+        # fill missing max hours to config value and
+        # assume no natural inflow due to lack of data
         phs = phs.replace({'max_hours': {0: c['PHS_max_hours']}})
         n.madd('StorageUnit', phs.index,
                carrier='PHS',
@@ -416,7 +409,6 @@ def attach_hydro(n, costs, ppl):
         hydro_max_hours = hydro.max_hours.where(hydro.max_hours > 0,
                                 hydro.country.map(max_hours_country)).fillna(6)
 
-
         n.madd('StorageUnit', hydro.index, carrier='hydro',
                bus=hydro['bus'],
                p_nom=hydro['p_nom'],
@@ -435,6 +427,7 @@ def attach_hydro(n, costs, ppl):
 def attach_extendable_generators(n, costs, ppl):
     elec_opts = snakemake.config['electricity']
     carriers = pd.Index(elec_opts['extendable_carriers']['Generator'])
+
     _add_missing_carriers_from_costs(n, costs, carriers)
 
     for tech in carriers:
@@ -480,6 +473,39 @@ def attach_extendable_generators(n, costs, ppl):
                                       "Only OCGT, CCGT and nuclear are allowed at the moment.")
 
 
+
+def attach_OPSD_renewables(n):
+
+    available = ['DE', 'FR', 'PL', 'CH', 'DK', 'CZ', 'SE', 'GB']
+    tech_map = {'Onshore': 'onwind', 'Offshore': 'offwind', 'Solar': 'solar'}
+    countries = set(available) & set(n.buses.country)
+    techs = snakemake.config['electricity'].get('renewable_capacities_from_OPSD', [])
+    tech_map = {k: v for k, v in tech_map.items() if v in techs}
+
+    if not tech_map:
+        return
+
+    logger.info(f'Using OPSD renewable capacities in {", ".join(countries)} '
+                f'for technologies {", ".join(tech_map.values())}.')
+
+    df = pd.concat([pm.data.OPSD_VRE_country(c) for c in countries])
+    technology_b = ~df.Technology.isin(['Onshore', 'Offshore'])
+    df['Fueltype'] = df.Fueltype.where(technology_b, df.Technology)
+    df = df.query('Fueltype in @tech_map').powerplant.convert_country_to_alpha2()
+
+    for fueltype, carrier_like in tech_map.items():
+        gens = n.generators[lambda df: df.carrier.str.contains(carrier_like)]
+        buses = n.buses.loc[gens.bus.unique()]
+        gens_per_bus = gens.groupby('bus').p_nom.count()
+
+        caps = map_country_bus(df.query('Fueltype == @fueltype'), buses)
+        caps = caps.groupby(['bus']).Capacity.sum()
+        caps = caps / gens_per_bus.reindex(caps.index, fill_value=1)
+
+        n.generators.p_nom.update(gens.bus.map(caps).dropna())
+
+
+
 def estimate_renewable_capacities(n, tech_map=None):
     if tech_map is None:
         tech_map = (snakemake.config['electricity']
@@ -487,23 +513,33 @@ def estimate_renewable_capacities(n, tech_map=None):
 
     if len(tech_map) == 0: return
 
-    capacities = (ppm.data.Capacity_stats().powerplant.convert_country_to_alpha2()
+    capacities = (pm.data.Capacity_stats().powerplant.convert_country_to_alpha2()
                   [lambda df: df.Energy_Source_Level_2]
                   .set_index(['Fueltype', 'Country']).sort_index())
 
     countries = n.buses.country.unique()
 
+    if len(countries) == 0: return
+
+    logger.info('heuristics applied to distribute renewable capacities [MW] \n{}'
+                .format(capacities.query('Fueltype in @tech_map.keys() and Capacity >= 0.1')
+                        .groupby('Country').agg({'Capacity': 'sum'})))
+
     for ppm_fueltype, techs in tech_map.items():
         tech_capacities = capacities.loc[ppm_fueltype, 'Capacity']\
                                     .reindex(countries, fill_value=0.)
-        tech_i = n.generators.query('carrier in @techs').index
+        #tech_i = n.generators.query('carrier in @techs').index
+        tech_i = (n.generators.query('carrier in @techs')
+                  [n.generators.query('carrier in @techs')
+                   .bus.map(n.buses.country).isin(countries)].index)
         n.generators.loc[tech_i, 'p_nom'] = (
             (n.generators_t.p_max_pu[tech_i].mean() *
              n.generators.loc[tech_i, 'p_nom_max']) # maximal yearly generation
-             .groupby(n.generators.bus.map(n.buses.country)) # for each country
+             .groupby(n.generators.bus.map(n.buses.country))
              .transform(lambda s: normed(s) * tech_capacities.at[s.name])
              .where(lambda s: s>0.1, 0.))  # only capacities above 100kW
 
+
 def add_nice_carrier_names(n, config=None):
     if config is None: config = snakemake.config
     carrier_i = n.carriers.index
@@ -525,7 +561,7 @@ if __name__ == "__main__":
     configure_logging(snakemake)
 
     n = pypsa.Network(snakemake.input.base_network)
-    Nyears = n.snapshot_weightings.sum()/8760.
+    Nyears = n.snapshot_weightings.sum() / 8760.
 
     costs = load_costs(Nyears)
     ppl = load_powerplants()
@@ -540,6 +576,8 @@ if __name__ == "__main__":
     attach_extendable_generators(n, costs, ppl)
 
     estimate_renewable_capacities(n)
+    attach_OPSD_renewables(n)
+
     add_nice_carrier_names(n)
 
     n.export_to_netcdf(snakemake.output[0])

scripts/add_extra_components.py

@@ -37,30 +37,33 @@ Inputs
 Outputs
 -------
 
-- ``networks/{network}_s{simpl}_{clusters}_ec.nc``:
+- ``networks/elec_s{simpl}_{clusters}_ec.nc``:
 
 
 Description
 -----------
 
-The rule :mod:`add_extra_components` attaches additional extendable components to the clustered and simplified network. These can be configured in the ``config.yaml`` at ``electricity: extendable_carriers: ``. It processes ``networks/{network}_s{simpl}_{clusters}.nc`` to build ``networks/{network}_s{simpl}_{clusters}_ec.nc``, which in contrast to the former (depending on the configuration) contain with **zero** initial capacity
+The rule :mod:`add_extra_components` attaches additional extendable components to the clustered and simplified network. These can be configured in the ``config.yaml`` at ``electricity: extendable_carriers:``. It processes ``networks/elec_s{simpl}_{clusters}.nc`` to build ``networks/elec_s{simpl}_{clusters}_ec.nc``, which in contrast to the former (depending on the configuration) contain with **zero** initial capacity
 
 - ``StorageUnits`` of carrier 'H2' and/or 'battery'. If this option is chosen, every bus is given an extendable ``StorageUnit`` of the corresponding carrier. The energy and power capacities are linked through a parameter that specifies the energy capacity as maximum hours at full dispatch power and is configured in ``electricity: max_hours:``. This linkage leads to one investment variable per storage unit. The default ``max_hours`` lead to long-term hydrogen and short-term battery storage units.
 
 - ``Stores`` of carrier 'H2' and/or 'battery' in combination with ``Links``. If this option is chosen, the script adds extra buses with corresponding carrier where energy ``Stores`` are attached and which are connected to the corresponding power buses via two links, one each for charging and discharging. This leads to three investment variables for the energy capacity, charging and discharging capacity of the storage unit.
 """
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import configure_logging
 
+import pypsa
 import pandas as pd
 import numpy as np
-import pypsa
+
 from add_electricity import (load_costs, add_nice_carrier_names,
                              _add_missing_carriers_from_costs)
 
 idx = pd.IndexSlice
 
+logger = logging.getLogger(__name__)
+
+
 def attach_storageunits(n, costs):
     elec_opts = snakemake.config['electricity']
     carriers = elec_opts['extendable_carriers']['StorageUnit']
@@ -70,6 +73,9 @@ def attach_storageunits(n, costs):
 
     buses_i = n.buses.index
 
+    lookup_store = {"H2": "electrolysis", "battery": "battery inverter"}
+    lookup_dispatch = {"H2": "fuel cell", "battery": "battery inverter"}
+
     for carrier in carriers:
         n.madd("StorageUnit", buses_i, ' ' + carrier,
                bus=buses_i,
@@ -77,11 +83,12 @@ def attach_storageunits(n, costs):
                p_nom_extendable=True,
                capital_cost=costs.at[carrier, 'capital_cost'],
                marginal_cost=costs.at[carrier, 'marginal_cost'],
-               efficiency_store=costs.at[carrier, 'efficiency'],
-               efficiency_dispatch=costs.at[carrier, 'efficiency'],
+               efficiency_store=costs.at[lookup_store[carrier], 'efficiency'],
+               efficiency_dispatch=costs.at[lookup_dispatch[carrier], 'efficiency'],
                max_hours=max_hours[carrier],
                cyclic_state_of_charge=True)
 
+
 def attach_stores(n, costs):
     elec_opts = snakemake.config['electricity']
     carriers = elec_opts['extendable_carriers']['Store']
@@ -107,7 +114,8 @@ def attach_stores(n, costs):
                carrier='H2 electrolysis',
                p_nom_extendable=True,
                efficiency=costs.at["electrolysis", "efficiency"],
-               capital_cost=costs.at["electrolysis", "capital_cost"])
+               capital_cost=costs.at["electrolysis", "capital_cost"],
+               marginal_cost=costs.at["electrolysis", "marginal_cost"])
 
         n.madd("Link", h2_buses_i + " Fuel Cell",
                bus0=h2_buses_i,
@@ -116,7 +124,8 @@ def attach_stores(n, costs):
                p_nom_extendable=True,
                efficiency=costs.at["fuel cell", "efficiency"],
                #NB: fixed cost is per MWel
-               capital_cost=costs.at["fuel cell", "capital_cost"] * costs.at["fuel cell", "efficiency"])
+               capital_cost=costs.at["fuel cell", "capital_cost"] * costs.at["fuel cell", "efficiency"],
+               marginal_cost=costs.at["fuel cell", "marginal_cost"])
 
     if 'battery' in carriers:
         b_buses_i = n.madd("Bus", buses_i + " battery", carrier="battery", **bus_sub_dict)
@@ -126,23 +135,27 @@ def attach_stores(n, costs):
                carrier='battery',
                e_cyclic=True,
                e_nom_extendable=True,
-               capital_cost=costs.at['battery storage', 'capital_cost'])
+               capital_cost=costs.at['battery storage', 'capital_cost'],
+               marginal_cost=costs.at["battery", "marginal_cost"])
 
         n.madd("Link", b_buses_i + " charger",
                bus0=buses_i,
                bus1=b_buses_i,
                carrier='battery charger',
-               efficiency=costs.at['battery inverter', 'efficiency']**0.5,
+               efficiency=costs.at['battery inverter', 'efficiency'],
                capital_cost=costs.at['battery inverter', 'capital_cost'],
-               p_nom_extendable=True)
+               p_nom_extendable=True,
+               marginal_cost=costs.at["battery inverter", "marginal_cost"])
 
         n.madd("Link", b_buses_i + " discharger",
                bus0=b_buses_i,
                bus1=buses_i,
                carrier='battery discharger',
-               efficiency=costs.at['battery inverter','efficiency']**0.5,
+               efficiency=costs.at['battery inverter','efficiency'],
                capital_cost=costs.at['battery inverter', 'capital_cost'],
-               p_nom_extendable=True)
+               p_nom_extendable=True,
+               marginal_cost=costs.at["battery inverter", "marginal_cost"])
+
 
 def attach_hydrogen_pipelines(n, costs):
     elec_opts = snakemake.config['electricity']
@@ -176,6 +189,7 @@ def attach_hydrogen_pipelines(n, costs):
            efficiency=costs.at['H2 pipeline','efficiency'],
            carrier="H2 pipeline")
 
+
 if __name__ == "__main__":
     if 'snakemake' not in globals():
         from _helpers import mock_snakemake
@@ -184,7 +198,7 @@ if __name__ == "__main__":
     configure_logging(snakemake)
 
     n = pypsa.Network(snakemake.input.network)
-    Nyears = n.snapshot_weightings.sum()/8760.
+    Nyears = n.snapshot_weightings.sum() / 8760.
     costs = load_costs(Nyears, tech_costs=snakemake.input.tech_costs,
                        config=snakemake.config['costs'],
                        elec_config=snakemake.config['electricity'])

scripts/base_network.py

@@ -63,14 +63,16 @@ Description
 """
 
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import configure_logging
 
+import pypsa
 import yaml
 import pandas as pd
 import geopandas as gpd
 import numpy as np
 import scipy as sp
+import networkx as nx
+
 from scipy.sparse import csgraph
 from six import iteritems
 from itertools import product
@@ -78,9 +80,8 @@ from itertools import product
 from shapely.geometry import Point, LineString
 import shapely, shapely.prepared, shapely.wkt
 
-import networkx as nx
+logger = logging.getLogger(__name__)
 
-import pypsa
 
 def _get_oid(df):
     if "tags" in df.columns:
@@ -88,12 +89,14 @@ def _get_oid(df):
     else:
         return pd.Series(np.nan, df.index)
 
+
 def _get_country(df):
     if "tags" in df.columns:
         return df.tags.str.extract('"country"=>"([A-Z]{2})"', expand=False)
     else:
         return pd.Series(np.nan, df.index)
 
+
 def _find_closest_links(links, new_links, distance_upper_bound=1.5):
     treecoords = np.asarray([np.asarray(shapely.wkt.loads(s))[[0, -1]].flatten()
                               for s in links.geometry])
@@ -109,6 +112,7 @@ def _find_closest_links(links, new_links, distance_upper_bound=1.5):
                         [lambda ds: ~ds.index.duplicated(keep='first')]\
                          .sort_index()['i']
 
+
 def _load_buses_from_eg():
     buses = (pd.read_csv(snakemake.input.eg_buses, quotechar="'",
                          true_values='t', false_values='f',
@@ -130,6 +134,7 @@ def _load_buses_from_eg():
 
     return pd.DataFrame(buses.loc[buses_in_europe_b & buses_with_v_nom_to_keep_b])
 
+
 def _load_transformers_from_eg(buses):
     transformers = (pd.read_csv(snakemake.input.eg_transformers, quotechar="'",
                                 true_values='t', false_values='f',
@@ -140,6 +145,7 @@ def _load_transformers_from_eg(buses):
 
     return transformers
 
+
 def _load_converters_from_eg(buses):
     converters = (pd.read_csv(snakemake.input.eg_converters, quotechar="'",
                               true_values='t', false_values='f',
@@ -201,8 +207,8 @@ def _add_links_from_tyndp(buses, links):
     buses = buses.loc[keep_b['Bus']]
     links = links.loc[keep_b['Link']]
 
-    links_tyndp["j"] = _find_closest_links(links, links_tyndp, distance_upper_bound=0.15)
-    # Corresponds approximately to 15km tolerances
+    links_tyndp["j"] = _find_closest_links(links, links_tyndp, distance_upper_bound=0.20)
+    # Corresponds approximately to 20km tolerances
 
     if links_tyndp["j"].notnull().any():
         logger.info("TYNDP links already in the dataset (skipping): " + ", ".join(links_tyndp.loc[links_tyndp["j"].notnull(), "Name"]))
@@ -241,6 +247,7 @@ def _add_links_from_tyndp(buses, links):
 
     return buses, links.append(links_tyndp, sort=True)
 
+
 def _load_lines_from_eg(buses):
     lines = (pd.read_csv(snakemake.input.eg_lines, quotechar="'", true_values='t', false_values='f',
                          dtype=dict(line_id='str', bus0='str', bus1='str',
@@ -254,11 +261,13 @@ def _load_lines_from_eg(buses):
 
     return lines
 
+
 def _apply_parameter_corrections(n):
     with open(snakemake.input.parameter_corrections) as f:
         corrections = yaml.safe_load(f)
 
     if corrections is None: return
+
     for component, attrs in iteritems(corrections):
         df = n.df(component)
         oid = _get_oid(df)
@@ -275,6 +284,7 @@ def _apply_parameter_corrections(n):
                 inds = r.index.intersection(df.index)
                 df.loc[inds, attr] = r[inds].astype(df[attr].dtype)
 
+
 def _set_electrical_parameters_lines(lines):
     v_noms = snakemake.config['electricity']['voltages']
     linetypes = snakemake.config['lines']['types']
@@ -286,12 +296,14 @@ def _set_electrical_parameters_lines(lines):
 
     return lines
 
+
 def _set_lines_s_nom_from_linetypes(n):
     n.lines['s_nom'] = (
         np.sqrt(3) * n.lines['type'].map(n.line_types.i_nom) *
         n.lines['v_nom'] * n.lines.num_parallel
     )
 
+
 def _set_electrical_parameters_links(links):
     if links.empty: return links
 
@@ -300,24 +312,25 @@ def _set_electrical_parameters_links(links):
     links['p_min_pu'] = -p_max_pu
 
     links_p_nom = pd.read_csv(snakemake.input.links_p_nom)
-    
-    #Filter links that are not in operation anymore    
+
+    # filter links that are not in operation anymore
     removed_b = links_p_nom.Remarks.str.contains('Shut down|Replaced', na=False)
     links_p_nom = links_p_nom[~removed_b]
-    
-    #find closest link for all links in links_p_nom        
+
+    # find closest link for all links in links_p_nom
     links_p_nom['j'] = _find_closest_links(links, links_p_nom)
-        
-    links_p_nom = links_p_nom.groupby(['j'],as_index=False).agg({'Power (MW)': 'sum'})    
-        
+
+    links_p_nom = links_p_nom.groupby(['j'],as_index=False).agg({'Power (MW)': 'sum'})
+
     p_nom = links_p_nom.dropna(subset=["j"]).set_index("j")["Power (MW)"]
-   
+
     # Don't update p_nom if it's already set
     p_nom_unset = p_nom.drop(links.index[links.p_nom.notnull()], errors='ignore') if "p_nom" in links else p_nom
     links.loc[p_nom_unset.index, "p_nom"] = p_nom_unset
 
     return links
 
+
 def _set_electrical_parameters_converters(converters):
     p_max_pu = snakemake.config['links'].get('p_max_pu', 1.)
     converters['p_max_pu'] = p_max_pu
@@ -331,6 +344,7 @@ def _set_electrical_parameters_converters(converters):
 
     return converters
 
+
 def _set_electrical_parameters_transformers(transformers):
     config = snakemake.config['transformers']
 
@@ -341,9 +355,11 @@ def _set_electrical_parameters_transformers(transformers):
 
     return transformers
 
+
 def _remove_dangling_branches(branches, buses):
     return pd.DataFrame(branches.loc[branches.bus0.isin(buses.index) & branches.bus1.isin(buses.index)])
 
+
 def _remove_unconnected_components(network):
     _, labels = csgraph.connected_components(network.adjacency_matrix(), directed=False)
     component = pd.Series(labels, index=network.buses.index)
@@ -356,6 +372,7 @@ def _remove_unconnected_components(network):
 
     return network[component == component_sizes.index[0]]
 
+
 def _set_countries_and_substations(n):
 
     buses = n.buses
@@ -442,6 +459,7 @@ def _set_countries_and_substations(n):
 
     return buses
 
+
 def _replace_b2b_converter_at_country_border_by_link(n):
     # Affects only the B2B converter in Lithuania at the Polish border at the moment
     buscntry = n.buses.country
@@ -479,6 +497,7 @@ def _replace_b2b_converter_at_country_border_by_link(n):
             logger.info("Replacing B2B converter `{}` together with bus `{}` and line `{}` by an HVDC tie-line {}-{}"
                         .format(i, b0, line, linkcntry.at[i], buscntry.at[b1]))
 
+
 def _set_links_underwater_fraction(n):
     if n.links.empty: return
 
@@ -489,6 +508,7 @@ def _set_links_underwater_fraction(n):
         links = gpd.GeoSeries(n.links.geometry.dropna().map(shapely.wkt.loads))
         n.links['underwater_fraction'] = links.intersection(offshore_shape).length / links.length
 
+
 def _adjust_capacities_of_under_construction_branches(n):
     lines_mode = snakemake.config['lines'].get('under_construction', 'undef')
     if lines_mode == 'zero':
@@ -513,6 +533,7 @@ def _adjust_capacities_of_under_construction_branches(n):
 
     return n
 
+
 def base_network():
     buses = _load_buses_from_eg()
 
@@ -534,7 +555,7 @@ def base_network():
     n.name = 'PyPSA-Eur'
 
     n.set_snapshots(pd.date_range(freq='h', **snakemake.config['snapshots']))
-    n.snapshot_weightings[:] *= 8760./n.snapshot_weightings.sum()
+    n.snapshot_weightings[:] *= 8760. / n.snapshot_weightings.sum()
 
     n.import_components_from_dataframe(buses, "Bus")
     n.import_components_from_dataframe(lines, "Line")
@@ -565,4 +586,5 @@ if __name__ == "__main__":
     configure_logging(snakemake)
 
     n = base_network()
+
     n.export_to_netcdf(snakemake.output[0])

scripts/build_bus_regions.py

@@ -42,17 +42,24 @@ Description
 """
 
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import configure_logging
 
-from vresutils.graph import voronoi_partition_pts
-
+import pypsa
 import os
-
 import pandas as pd
 import geopandas as gpd
 
-import pypsa
+from vresutils.graph import voronoi_partition_pts
+
+logger = logging.getLogger(__name__)
+
+
+def save_to_geojson(s, fn):
+    if os.path.exists(fn):
+        os.unlink(fn)
+    schema = {**gpd.io.file.infer_schema(s), 'geometry': 'Unknown'}
+    s.to_file(fn, driver='GeoJSON', schema=schema)
+
 
 if __name__ == "__main__":
     if 'snakemake' not in globals():
@@ -96,12 +103,6 @@ if __name__ == "__main__":
         offshore_regions_c = offshore_regions_c.loc[offshore_regions_c.area > 1e-2]
         offshore_regions.append(offshore_regions_c)
 
-    def save_to_geojson(s, fn):
-        if os.path.exists(fn):
-            os.unlink(fn)
-        schema = {**gpd.io.file.infer_schema(s), 'geometry': 'Unknown'}
-        s.to_file(fn, driver='GeoJSON', schema=schema)
-
     save_to_geojson(pd.concat(onshore_regions, ignore_index=True), snakemake.output.regions_onshore)
 
     save_to_geojson(pd.concat(offshore_regions, ignore_index=True), snakemake.output.regions_offshore)

scripts/build_country_flh.py

@@ -63,7 +63,6 @@ Description
 """
 
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import configure_logging
 
 import os
@@ -84,6 +83,9 @@ import progressbar as pgb
 
 from build_renewable_profiles import init_globals, calculate_potential
 
+logger = logging.getLogger(__name__)
+
+
 def build_area(flh, countries, areamatrix, breaks, fn):
     area_unbinned = xr.DataArray(areamatrix.todense(), [countries, capacity_factor.coords['spatial']])
     bins = xr.DataArray(pd.cut(flh.to_series(), bins=breaks), flh.coords, name="bins")
@@ -92,6 +94,7 @@ def build_area(flh, countries, areamatrix, breaks, fn):
     area.columns = area.columns.map(lambda s: s.left)
     return area
 
+
 def plot_area_not_solar(area, countries):
     # onshore wind/offshore wind
     a = area.T

scripts/build_cutout.py

@@ -92,12 +92,13 @@ Description
 """
 
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import configure_logging
 
 import os
 import atlite
 
+logger = logging.getLogger(__name__)
+
 if __name__ == "__main__":
     if 'snakemake' not in globals():
         from _helpers import mock_snakemake
@@ -113,4 +114,6 @@ if __name__ == "__main__":
                         cutout_dir=os.path.dirname(snakemake.output[0]),
                         **cutout_params)
 
-    cutout.prepare(nprocesses=snakemake.config['atlite'].get('nprocesses', 4))
+    nprocesses = snakemake.config['atlite'].get('nprocesses', 4)
+
+    cutout.prepare(nprocesses=nprocesses)

scripts/build_hydro_profile.py

@@ -60,7 +60,6 @@ Description
 """
 
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import configure_logging
 
 import os
@@ -68,6 +67,8 @@ import atlite
 import geopandas as gpd
 from vresutils import hydro as vhydro
 
+logger = logging.getLogger(__name__)
+
 if __name__ == "__main__":
     if 'snakemake' not in globals():
         from _helpers import mock_snakemake
@@ -75,8 +76,8 @@ if __name__ == "__main__":
     configure_logging(snakemake)
 
     config = snakemake.config['renewable']['hydro']
-    cutout = atlite.Cutout(config['cutout'],
-                        cutout_dir=os.path.dirname(snakemake.input.cutout))
+    cutout_dir = os.path.dirname(snakemake.input.cutout)
+    cutout = atlite.Cutout(config['cutout'], cutout_dir=cutout_dir)
 
     countries = snakemake.config['countries']
     country_shapes = gpd.read_file(snakemake.input.country_shapes).set_index('name')['geometry'].reindex(countries)
@@ -84,9 +85,9 @@ if __name__ == "__main__":
 
     eia_stats = vhydro.get_eia_annual_hydro_generation(snakemake.input.eia_hydro_generation).reindex(columns=countries)
     inflow = cutout.runoff(shapes=country_shapes,
-                        smooth=True,
-                        lower_threshold_quantile=True,
-                        normalize_using_yearly=eia_stats)
+                           smooth=True,
+                           lower_threshold_quantile=True,
+                           normalize_using_yearly=eia_stats)
 
     if 'clip_min_inflow' in config:
         inflow.values[inflow.values < config['clip_min_inflow']] = 0.

scripts/build_load_data.py

@@ -0,0 +1,227 @@
+# SPDX-FileCopyrightText: : 2020 @JanFrederickUnnewehr, The PyPSA-Eur Authors
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+"""
+
+This rule downloads the load data from `Open Power System Data Time series <https://data.open-power-system-data.org/time_series/>`_. For all countries in the network, the per country load timeseries with suffix ``_load_actual_entsoe_transparency`` are extracted from the dataset. After filling small gaps linearly and large gaps by copying time-slice of a given period, the load data is exported to a ``.csv`` file.
+
+Relevant Settings
+-----------------
+
+.. code:: yaml
+
+    snapshots:
+
+    load:
+        url:
+        interpolate_limit:
+        time_shift_for_large_gaps:
+        manual_adjustments:
+
+
+.. seealso::
+    Documentation of the configuration file ``config.yaml`` at
+    :ref:`load_cf`
+
+Inputs
+------
+
+
+Outputs
+-------
+
+- ``resource/time_series_60min_singleindex_filtered.csv``:
+
+
+"""
+
+import logging
+logger = logging.getLogger(__name__)
+from _helpers import configure_logging
+
+import pandas as pd
+import numpy as np
+import dateutil
+from pandas import Timedelta as Delta
+
+
+def load_timeseries(fn, years, countries, powerstatistics=True):
+    """
+    Read load data from OPSD time-series package version 2020-10-06.
+
+    Parameters
+    ----------
+    years : None or slice()
+        Years for which to read load data (defaults to
+        slice("2018","2019"))
+    fn : str
+        File name or url location (file format .csv)
+    countries : listlike
+        Countries for which to read load data.
+    powerstatistics: bool
+        Whether the electricity consumption data of the ENTSOE power
+        statistics (if true) or of the ENTSOE transparency map (if false)
+        should be parsed.
+
+    Returns
+    -------
+    load : pd.DataFrame
+        Load time-series with UTC timestamps x ISO-2 countries
+    """
+    logger.info(f"Retrieving load data from '{fn}'.")
+
+    pattern = 'power_statistics' if powerstatistics else '_transparency'
+    pattern = f'_load_actual_entsoe_{pattern}'
+    rename = lambda s: s[:-len(pattern)]
+    date_parser = lambda x: dateutil.parser.parse(x, ignoretz=True)
+    return (pd.read_csv(fn, index_col=0, parse_dates=[0], date_parser=date_parser)
+            .filter(like=pattern)
+            .rename(columns=rename)
+            .dropna(how="all", axis=0)
+            .rename(columns={'GB_UKM' : 'GB'})
+            .filter(items=countries)
+            .loc[years])
+
+
+def consecutive_nans(ds):
+    return (ds.isnull().astype(int)
+            .groupby(ds.notnull().astype(int).cumsum()[ds.isnull()])
+            .transform('sum').fillna(0))
+
+
+def fill_large_gaps(ds, shift):
+    """
+    Fill up large gaps with load data from the previous week.
+
+    This function fills gaps ragning from 3 to 168 hours (one week).
+    """
+    shift = Delta(shift)
+    nhours = shift / np.timedelta64(1, 'h')
+    if (consecutive_nans(ds) > nhours).any():
+        logger.warning('There exist gaps larger then the time shift used for '
+                       'copying time slices.')
+    time_shift = pd.Series(ds.values, ds.index + shift)
+    return ds.where(ds.notnull(), time_shift.reindex_like(ds))
+
+
+def nan_statistics(df):
+    def max_consecutive_nans(ds):
+        return (ds.isnull().astype(int)
+                  .groupby(ds.notnull().astype(int).cumsum())
+                  .sum().max())
+    consecutive = df.apply(max_consecutive_nans)
+    total = df.isnull().sum()
+    max_total_per_month = df.isnull().resample('m').sum().max()
+    return pd.concat([total, consecutive, max_total_per_month],
+                 keys=['total', 'consecutive', 'max_total_per_month'], axis=1)
+
+
+def copy_timeslice(load, cntry, start, stop, delta):
+    start = pd.Timestamp(start)
+    stop = pd.Timestamp(stop)
+    if start-delta in load.index and stop in load.index and cntry in load:
+        load.loc[start:stop, cntry] = load.loc[start-delta:stop-delta, cntry].values
+
+
+def manual_adjustment(load, powerstatistics):
+    """
+    Adjust gaps manual for load data from OPSD time-series package.
+
+    1. For the ENTSOE power statistics load data (if powerstatistics is True)
+
+    Kosovo (KV) and Albania (AL) do not exist in the data set. Kosovo gets the
+    same load curve as Serbia and Albania the same as Macdedonia, both scaled
+    by the corresponding ratio of total energy consumptions reported by
+    IEA Data browser [0] for the year 2013.
+
+    2. For the ENTSOE transparency load data (if powerstatistics is False)
+
+    Albania (AL) and Macedonia (MK) do not exist in the data set. Both get the
+    same load curve as Montenegro,  scaled by the corresponding ratio of total energy
+    consumptions reported by  IEA Data browser [0] for the year 2016.
+
+    [0] https://www.iea.org/data-and-statistics?country=WORLD&fuel=Electricity%20and%20heat&indicator=TotElecCons
+
+
+    Parameters
+    ----------
+    load : pd.DataFrame
+        Load time-series with UTC timestamps x ISO-2 countries
+    powerstatistics: bool
+        Whether argument load comprises the electricity consumption data of
+        the ENTSOE power statistics or of the ENTSOE transparency map
+
+    Returns
+    -------
+    load : pd.DataFrame
+        Manual adjusted and interpolated load time-series with UTC
+        timestamps x ISO-2 countries
+    """
+
+    if powerstatistics:
+        if 'MK' in load.columns:
+            if 'AL' not in load.columns or load.AL.isnull().values.all():
+                load['AL'] = load['MK'] * (4.1 / 7.4)
+        if 'RS' in load.columns:
+            if 'KV' not in load.columns or load.KV.isnull().values.all():
+                load['KV'] = load['RS'] * (4.8 / 27.)
+
+        copy_timeslice(load, 'GR', '2015-08-11 21:00', '2015-08-15 20:00', Delta(weeks=1))
+        copy_timeslice(load, 'AT', '2018-12-31 22:00', '2019-01-01 22:00', Delta(days=2))
+        copy_timeslice(load, 'CH', '2010-01-19 07:00', '2010-01-19 22:00', Delta(days=1))
+        copy_timeslice(load, 'CH', '2010-03-28 00:00', '2010-03-28 21:00', Delta(days=1))
+        # is a WE, so take WE before
+        copy_timeslice(load, 'CH', '2010-10-08 13:00', '2010-10-10 21:00', Delta(weeks=1))
+        copy_timeslice(load, 'CH', '2010-11-04 04:00', '2010-11-04 22:00', Delta(days=1))
+        copy_timeslice(load, 'NO', '2010-12-09 11:00', '2010-12-09 18:00', Delta(days=1))
+        # whole january missing
+        copy_timeslice(load, 'GB', '2009-12-31 23:00', '2010-01-31 23:00', Delta(days=-364))
+
+    else:
+        if 'ME' in load:
+            if 'AL' not in load and 'AL' in countries:
+                load['AL'] = load.ME * (5.7/2.9)
+            if 'MK' not in load and 'MK' in countries:
+                load['MK'] = load.ME * (6.7/2.9)
+        copy_timeslice(load, 'BG', '2018-10-27 21:00', '2018-10-28 22:00', Delta(weeks=1))
+
+    return load
+
+
+if __name__ == "__main__":
+
+    if 'snakemake' not in globals():
+        from _helpers import mock_snakemake
+        snakemake = mock_snakemake('build_load_data')
+
+    configure_logging(snakemake)
+
+    config = snakemake.config
+    powerstatistics = config['load']['power_statistics']
+    url = config['load']['url']
+    interpolate_limit = config['load']['interpolate_limit']
+    countries = config['countries']
+    snapshots = pd.date_range(freq='h', **config['snapshots'])
+    years = slice(snapshots[0], snapshots[-1])
+    time_shift = config['load']['time_shift_for_large_gaps']
+
+    load = load_timeseries(url, years, countries, powerstatistics)
+
+    if config['load']['manual_adjustments']:
+        load = manual_adjustment(load, powerstatistics)
+
+    logger.info(f"Linearly interpolate gaps of size {interpolate_limit} and less.")
+    load = load.interpolate(method='linear', limit=interpolate_limit)
+
+    logger.info("Filling larger gaps by copying time-slices of period "
+                f"'{time_shift}'.")
+    load = load.apply(fill_large_gaps, shift=time_shift)
+
+    assert not load.isna().any().any(), (
+        'Load data contains nans. Adjust the parameters '
+        '`time_shift_for_large_gaps` or modify the `manual_adjustment` function '
+        'for implementing the needed load data modifications.')
+
+    load.to_csv(snakemake.output[0])
+

scripts/build_natura_raster.py

@@ -41,6 +41,7 @@ Description
 
 import logging
 from _helpers import configure_logging
+
 import atlite
 import geokit as gk
 from pathlib import Path
@@ -58,7 +59,7 @@ def determine_cutout_xXyY(cutout_name):
 if __name__ == "__main__":
     if 'snakemake' not in globals():
         from _helpers import mock_snakemake
-        snakemake = mock_snakemake('build_natura_raster') #has to be enabled
+        snakemake = mock_snakemake('build_natura_raster')
     configure_logging(snakemake)
 
     cutout_dir = Path(snakemake.input.cutouts[0]).parent.resolve()

scripts/build_powerplants.py

@@ -72,16 +72,18 @@ The configuration options ``electricity: powerplants_filter`` and ``electricity:
 """
 
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import configure_logging
 
-from scipy.spatial import cKDTree as KDTree
-
 import pypsa
 import powerplantmatching as pm
 import pandas as pd
 import numpy as np
 
+from scipy.spatial import cKDTree as KDTree
+
+logger = logging.getLogger(__name__)
+
+
 def add_custom_powerplants(ppl):
     custom_ppl_query = snakemake.config['electricity']['custom_powerplants']
     if not custom_ppl_query:
@@ -94,7 +96,6 @@ def add_custom_powerplants(ppl):
 
 
 if __name__ == "__main__":
-
     if 'snakemake' not in globals():
         from _helpers import mock_snakemake
         snakemake = mock_snakemake('build_powerplants')

scripts/build_renewable_profiles.py

@@ -181,27 +181,28 @@ node (`p_nom_max`): ``simple`` and ``conservative``:
 
 """
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import configure_logging
 
-import matplotlib.pyplot as plt
-
 import os
 import atlite
+
 import numpy as np
 import xarray as xr
 import pandas as pd
 import multiprocessing as mp
+import matplotlib.pyplot as plt
+import progressbar as pgb
 
 from scipy.sparse import csr_matrix, vstack
-
 from pypsa.geo import haversine
 from vresutils import landuse as vlanduse
 from vresutils.array import spdiag
 
-import progressbar as pgb
+logger = logging.getLogger(__name__)
 
 bounds = dx = dy = config = paths = gebco = clc = natura = None
+
+
 def init_globals(bounds_xXyY, n_dx, n_dy, n_config, n_paths):
     # Late import so that the GDAL Context is only created in the new processes
     global gl, gk, gdal
@@ -227,6 +228,7 @@ def init_globals(bounds_xXyY, n_dx, n_dy, n_config, n_paths):
 
     natura = gk.raster.loadRaster(paths["natura"])
 
+
 def downsample_to_coarse_grid(bounds, dx, dy, mask, data):
     # The GDAL warp function with the 'average' resample algorithm needs a band of zero values of at least
     # the size of one coarse cell around the original raster or it produces erroneous results
@@ -238,6 +240,7 @@ def downsample_to_coarse_grid(bounds, dx, dy, mask, data):
     assert gdal.Warp(average, padded, resampleAlg='average') == 1, "gdal warp failed: %s" % gdal.GetLastErrorMsg()
     return average
 
+
 def calculate_potential(gid, save_map=None):
     feature = gk.vector.extractFeature(paths["regions"], where=gid)
     ec = gl.ExclusionCalculator(feature.geom)

scripts/build_shapes.py

@@ -92,6 +92,7 @@ def _get_country(target, **keys):
     except (KeyError, AttributeError):
         return np.nan
 
+
 def _simplify_polys(polys, minarea=0.1, tolerance=0.01, filterremote=True):
     if isinstance(polys, MultiPolygon):
         polys = sorted(polys, key=attrgetter('area'), reverse=True)
@@ -105,6 +106,7 @@ def _simplify_polys(polys, minarea=0.1, tolerance=0.01, filterremote=True):
             polys = mainpoly
     return polys.simplify(tolerance=tolerance)
 
+
 def countries():
     cntries = snakemake.config['countries']
     if 'RS' in cntries: cntries.append('KV')
@@ -121,6 +123,7 @@ def countries():
 
     return s
 
+
 def eez(country_shapes):
     df = gpd.read_file(snakemake.input.eez)
     df = df.loc[df['ISO_3digit'].isin([_get_country('alpha_3', alpha_2=c) for c in snakemake.config['countries']])]
@@ -130,6 +133,7 @@ def eez(country_shapes):
     s.index.name = "name"
     return s
 
+
 def country_cover(country_shapes, eez_shapes=None):
     shapes = list(country_shapes)
     if eez_shapes is not None:
@@ -140,6 +144,7 @@ def country_cover(country_shapes, eez_shapes=None):
         europe_shape = max(europe_shape, key=attrgetter('area'))
     return Polygon(shell=europe_shape.exterior)
 
+
 def nuts3(country_shapes):
     df = gpd.read_file(snakemake.input.nuts3)
     df = df.loc[df['STAT_LEVL_'] == 3]
@@ -158,7 +163,6 @@ def nuts3(country_shapes):
            .applymap(lambda x: pd.to_numeric(x, errors='coerce'))
            .fillna(method='bfill', axis=1))['2014']
 
-    # Swiss data
     cantons = pd.read_csv(snakemake.input.ch_cantons)
     cantons = cantons.set_index(cantons['HASC'].str[3:])['NUTS']
     cantons = cantons.str.pad(5, side='right', fillchar='0')
@@ -197,6 +201,7 @@ def nuts3(country_shapes):
 
     return df
 
+
 def save_to_geojson(df, fn):
     if os.path.exists(fn):
         os.unlink(fn)
@@ -206,20 +211,23 @@ def save_to_geojson(df, fn):
     schema = {**gpd.io.file.infer_schema(df), 'geometry': 'Unknown'}
     df.to_file(fn, driver='GeoJSON', schema=schema)
 
+
 if __name__ == "__main__":
     if 'snakemake' not in globals():
         from _helpers import mock_snakemake
         snakemake = mock_snakemake('build_shapes')
     configure_logging(snakemake)
 
+    out = snakemake.output
+
     country_shapes = countries()
-    save_to_geojson(country_shapes, snakemake.output.country_shapes)
+    save_to_geojson(country_shapes, out.country_shapes)
 
     offshore_shapes = eez(country_shapes)
-    save_to_geojson(offshore_shapes, snakemake.output.offshore_shapes)
+    save_to_geojson(offshore_shapes, out.offshore_shapes)
 
     europe_shape = country_cover(country_shapes, offshore_shapes)
-    save_to_geojson(gpd.GeoSeries(europe_shape), snakemake.output.europe_shape)
+    save_to_geojson(gpd.GeoSeries(europe_shape), out.europe_shape)
 
     nuts3_shapes = nuts3(country_shapes)
-    save_to_geojson(nuts3_shapes, snakemake.output.nuts3_shapes)
+    save_to_geojson(nuts3_shapes, out.nuts3_shapes)

scripts/cluster_network.py

@@ -31,26 +31,28 @@ Relevant Settings
 Inputs
 ------
 
-- ``resources/regions_onshore_{network}_s{simpl}.geojson``: confer :ref:`simplify`
-- ``resources/regions_offshore_{network}_s{simpl}.geojson``: confer :ref:`simplify`
-- ``resources/clustermaps_{network}_s{simpl}.h5``: confer :ref:`simplify`
-- ``networks/{network}_s{simpl}.nc``: confer :ref:`simplify`
+- ``resources/regions_onshore_elec_s{simpl}.geojson``: confer :ref:`simplify`
+- ``resources/regions_offshore_elec_s{simpl}.geojson``: confer :ref:`simplify`
+- ``resources/busmap_elec_s{simpl}.csv``: confer :ref:`simplify`
+- ``networks/elec_s{simpl}.nc``: confer :ref:`simplify`
+- ``data/custom_busmap_elec_s{simpl}_{clusters}.csv``: optional input
 
 Outputs
 -------
 
-- ``resources/regions_onshore_{network}_s{simpl}_{clusters}.geojson``:
+- ``resources/regions_onshore_elec_s{simpl}_{clusters}.geojson``:
 
     .. image:: ../img/regions_onshore_elec_s_X.png
         :scale: 33 %
 
-- ``resources/regions_offshore_{network}_s{simpl}_{clusters}.geojson``:
+- ``resources/regions_offshore_elec_s{simpl}_{clusters}.geojson``:
 
     .. image:: ../img/regions_offshore_elec_s_X.png
         :scale: 33 %
 
-- ``resources/clustermaps_{network}_s{simpl}_{clusters}.h5``: Mapping of buses and lines from ``networks/elec_s{simpl}.nc`` to ``networks/elec_s{simpl}_{clusters}.nc``; has keys ['/busmap', '/busmap_s', '/linemap', '/linemap_negative', '/linemap_positive']
-- ``networks/{network}_s{simpl}_{clusters}.nc``:
+- ``resources/busmap_elec_s{simpl}_{clusters}.csv``: Mapping of buses from ``networks/elec_s{simpl}.nc`` to ``networks/elec_s{simpl}_{clusters}.nc``;
+- ``resources/linemap_elec_s{simpl}_{clusters}.csv``: Mapping of lines from ``networks/elec_s{simpl}.nc`` to ``networks/elec_s{simpl}_{clusters}.nc``;
+- ``networks/elec_s{simpl}_{clusters}.nc``:
 
     .. image:: ../img/elec_s_X.png
         :scale: 40  %
@@ -115,36 +117,38 @@ Exemplary unsolved network clustered to 37 nodes:
 
 .. image:: ../img/elec_s_37.png
     :scale: 40  %
-    :align: center  
+    :align: center
 
 """
 
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import configure_logging
 
-import pandas as pd
-idx = pd.IndexSlice
-
+import pypsa
 import os
+import shapely
+
+import pandas as pd
 import numpy as np
 import geopandas as gpd
-import shapely
+import pyomo.environ as po
 import matplotlib.pyplot as plt
 import seaborn as sns
 
 from six.moves import reduce
 
-import pyomo.environ as po
-
-import pypsa
 from pypsa.networkclustering import (busmap_by_kmeans, busmap_by_spectral_clustering,
                                      _make_consense, get_clustering_from_busmap)
 
 from add_electricity import load_costs
 
-def normed(x):
-    return (x/x.sum()).fillna(0.)
+idx = pd.IndexSlice
+
+logger = logging.getLogger(__name__)
+
+
+def normed(x): return (x/x.sum()).fillna(0.)
+
 
 def weighting_for_country(n, x):
     conv_carriers = {'OCGT','CCGT','PHS', 'hydro'}
@@ -162,22 +166,13 @@ def weighting_for_country(n, x):
     g = normed(gen.reindex(b_i, fill_value=0))
     l = normed(load.reindex(b_i, fill_value=0))
 
-    w= g + l
+    w = g + l
     return (w * (100. / w.max())).clip(lower=1.).astype(int)
 
 
-## Plot weighting for Germany
-
-def plot_weighting(n, country, country_shape=None):
-    n.plot(bus_sizes=(2*weighting_for_country(n.buses.loc[n.buses.country == country])).reindex(n.buses.index, fill_value=1))
-    if country_shape is not None:
-        plt.xlim(country_shape.bounds[0], country_shape.bounds[2])
-        plt.ylim(country_shape.bounds[1], country_shape.bounds[3])
-
-
-# # Determining the number of clusters per country
-
 def distribute_clusters(n, n_clusters, focus_weights=None, solver_name=None):
+    """Determine the number of clusters per country"""
+
     if solver_name is None:
         solver_name = snakemake.config['solving']['solver']['name']
 
@@ -189,7 +184,7 @@ def distribute_clusters(n, n_clusters, focus_weights=None, solver_name=None):
     N = n.buses.groupby(['country', 'sub_network']).size()
 
     assert n_clusters >= len(N) and n_clusters <= N.sum(), \
-        "Number of clusters must be {} <= n_clusters <= {} for this selection of countries.".format(len(N), N.sum())
+        f"Number of clusters must be {len(N)} <= n_clusters <= {N.sum()} for this selection of countries."
 
     if focus_weights is not None:
 
@@ -205,7 +200,7 @@ def distribute_clusters(n, n_clusters, focus_weights=None, solver_name=None):
 
         logger.warning('Using custom focus weights for determining number of clusters.')
 
-    assert np.isclose(L.sum(), 1.0, rtol=1e-3), "Country weights L must sum up to 1.0 when distributing clusters. Is {}.".format(L.sum())
+    assert np.isclose(L.sum(), 1.0, rtol=1e-3), f"Country weights L must sum up to 1.0 when distributing clusters. Is {L.sum()}."
 
     m = po.ConcreteModel()
     def n_bounds(model, *n_id):
@@ -221,10 +216,11 @@ def distribute_clusters(n, n_clusters, focus_weights=None, solver_name=None):
         opt = po.SolverFactory('ipopt')
 
     results = opt.solve(m)
-    assert results['Solver'][0]['Status'] == 'ok', "Solver returned non-optimally: {}".format(results)
+    assert results['Solver'][0]['Status'] == 'ok', f"Solver returned non-optimally: {results}"
 
     return pd.Series(m.n.get_values(), index=L.index).astype(int)
 
+
 def busmap_for_n_clusters(n, n_clusters, solver_name, focus_weights=None, algorithm="kmeans", **algorithm_kwds):
     if algorithm == "kmeans":
         algorithm_kwds.setdefault('n_init', 1000)
@@ -243,7 +239,7 @@ def busmap_for_n_clusters(n, n_clusters, solver_name, focus_weights=None, algori
 
     def busmap_for_country(x):
         prefix = x.name[0] + x.name[1] + ' '
-        logger.debug("Determining busmap for country {}".format(prefix[:-1]))
+        logger.debug(f"Determining busmap for country {prefix[:-1]}")
         if len(x) == 1:
             return pd.Series(prefix + '0', index=x.index)
         weight = weighting_for_country(n, x)
@@ -257,31 +253,30 @@ def busmap_for_n_clusters(n, n_clusters, solver_name, focus_weights=None, algori
         else:
             raise ValueError(f"`algorithm` must be one of 'kmeans', 'spectral' or 'louvain'. Is {algorithm}.")
 
-    return (n.buses.groupby(['country', 'sub_network'], group_keys=False, squeeze=True)
-            .apply(busmap_for_country).rename('busmap'))
+    return (n.buses.groupby(['country', 'sub_network'], group_keys=False)
+            .apply(busmap_for_country).squeeze().rename('busmap'))
 
-def plot_busmap_for_n_clusters(n, n_clusters=50):
-    busmap = busmap_for_n_clusters(n, n_clusters)
-    cs = busmap.unique()
-    cr = sns.color_palette("hls", len(cs))
-    n.plot(bus_colors=busmap.map(dict(zip(cs, cr))))
-    del cs, cr
 
-def clustering_for_n_clusters(n, n_clusters, aggregate_carriers=None,
-                              line_length_factor=1.25, potential_mode='simple',
-                              solver_name="cbc", algorithm="kmeans",
-                              extended_link_costs=0, focus_weights=None):
+def clustering_for_n_clusters(n, n_clusters, custom_busmap=False, aggregate_carriers=None,
+                              line_length_factor=1.25, potential_mode='simple', solver_name="cbc",
+                              algorithm="kmeans", extended_link_costs=0, focus_weights=None):
 
     if potential_mode == 'simple':
         p_nom_max_strategy = np.sum
     elif potential_mode == 'conservative':
         p_nom_max_strategy = np.min
     else:
-        raise AttributeError("potential_mode should be one of 'simple' or 'conservative', "
-                             "but is '{}'".format(potential_mode))
+        raise AttributeError(f"potential_mode should be one of 'simple' or 'conservative' but is '{potential_mode}'")
+
+    if custom_busmap:
+        busmap = pd.read_csv(snakemake.input.custom_busmap, index_col=0, squeeze=True)
+        busmap.index = busmap.index.astype(str)
+        logger.info(f"Imported custom busmap from {snakemake.input.custom_busmap}")
+    else:
+        busmap = busmap_for_n_clusters(n, n_clusters, solver_name, focus_weights, algorithm)
 
     clustering = get_clustering_from_busmap(
-        n, busmap_for_n_clusters(n, n_clusters, solver_name, focus_weights, algorithm),
+        n, busmap,
         bus_strategies=dict(country=_make_consense("Bus", "country")),
         aggregate_generators_weighted=True,
         aggregate_generators_carriers=aggregate_carriers,
@@ -301,6 +296,7 @@ def clustering_for_n_clusters(n, n_clusters, aggregate_carriers=None,
 
     return clustering
 
+
 def save_to_geojson(s, fn):
     if os.path.exists(fn):
         os.unlink(fn)
@@ -308,6 +304,7 @@ def save_to_geojson(s, fn):
     schema = {**gpd.io.file.infer_schema(df), 'geometry': 'Unknown'}
     df.to_file(fn, driver='GeoJSON', schema=schema)
 
+
 def cluster_regions(busmaps, input=None, output=None):
     if input is None: input = snakemake.input
     if output is None: output = snakemake.output
@@ -321,6 +318,17 @@ def cluster_regions(busmaps, input=None, output=None):
         regions_c.index.name = 'name'
         save_to_geojson(regions_c, getattr(output, which))
 
+
+def plot_busmap_for_n_clusters(n, n_clusters, fn=None):
+    busmap = busmap_for_n_clusters(n, n_clusters)
+    cs = busmap.unique()
+    cr = sns.color_palette("hls", len(cs))
+    n.plot(bus_colors=busmap.map(dict(zip(cs, cr))))
+    if fn is not None:
+        plt.savefig(fn, bbox_inches='tight')
+    del cs, cr
+
+
 if __name__ == "__main__":
     if 'snakemake' not in globals():
         from _helpers import mock_snakemake
@@ -333,7 +341,7 @@ if __name__ == "__main__":
 
     renewable_carriers = pd.Index([tech
                                    for tech in n.generators.carrier.unique()
-                                   if tech.split('-', 2)[0] in snakemake.config['renewable']])
+                                   if tech in snakemake.config['renewable']])
 
     if snakemake.wildcards.clusters.endswith('m'):
         n_clusters = int(snakemake.wildcards.clusters[:-1])
@@ -363,7 +371,8 @@ if __name__ == "__main__":
             return v
         potential_mode = consense(pd.Series([snakemake.config['renewable'][tech]['potential']
                                              for tech in renewable_carriers]))
-        clustering = clustering_for_n_clusters(n, n_clusters, aggregate_carriers,
+        custom_busmap = snakemake.config["enable"].get("custom_busmap", False)
+        clustering = clustering_for_n_clusters(n, n_clusters, custom_busmap, aggregate_carriers,
                                                line_length_factor=line_length_factor,
                                                potential_mode=potential_mode,
                                                solver_name=snakemake.config['solving']['solver']['name'],
@@ -371,11 +380,7 @@ if __name__ == "__main__":
                                                focus_weights=focus_weights)
 
     clustering.network.export_to_netcdf(snakemake.output.network)
-    with pd.HDFStore(snakemake.output.clustermaps, mode='w') as store:
-        with pd.HDFStore(snakemake.input.clustermaps, mode='r') as clustermaps:
-            for attr in clustermaps.keys():
-                store.put(attr, clustermaps[attr], format="table", index=False)
-        for attr in ('busmap', 'linemap', 'linemap_positive', 'linemap_negative'):
-            store.put(attr, getattr(clustering, attr), format="table", index=False)
+    for attr in ('busmap', 'linemap'): #also available: linemap_positive, linemap_negative
+        getattr(clustering, attr).to_csv(snakemake.output[attr])
 
     cluster_regions((clustering.busmap,))

scripts/make_summary.py

@@ -55,29 +55,30 @@ Replacing '/summaries/' with '/plots/' creates nice colored maps of the results.
 """
 
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import configure_logging
 
 import os
-
-from six import iteritems
+import pypsa
 import pandas as pd
 
-import pypsa
-
+from six import iteritems
 from add_electricity import load_costs, update_transmission_costs
 
 idx = pd.IndexSlice
 
+logger = logging.getLogger(__name__)
+
 opt_name = {"Store": "e", "Line" : "s", "Transformer" : "s"}
 
+
 def _add_indexed_rows(df, raw_index):
-    new_index = df.index|pd.MultiIndex.from_product(raw_index)
+    new_index = df.index.union(pd.MultiIndex.from_product(raw_index))
     if isinstance(new_index, pd.Index):
         new_index = pd.MultiIndex.from_tuples(new_index)
 
     return df.reindex(new_index)
 
+
 def assign_carriers(n):
 
     if "carrier" not in n.loads:
@@ -98,7 +99,8 @@ def assign_carriers(n):
     if "EU gas store" in n.stores.index and n.stores.loc["EU gas Store","carrier"] == "":
         n.stores.loc["EU gas Store","carrier"] = "gas Store"
 
-def calculate_costs(n,label,costs):
+
+def calculate_costs(n, label, costs):
 
     for c in n.iterate_components(n.branch_components|n.controllable_one_port_components^{"Load"}):
         capital_costs = c.df.capital_cost*c.df[opt_name.get(c.name,"p") + "_nom_opt"]
@@ -125,13 +127,13 @@ def calculate_costs(n,label,costs):
 
         marginal_costs_grouped = marginal_costs.groupby(c.df.carrier).sum()
 
-        costs = costs.reindex(costs.index|pd.MultiIndex.from_product([[c.list_name],["marginal"],marginal_costs_grouped.index]))
+        costs = costs.reindex(costs.index.union(pd.MultiIndex.from_product([[c.list_name],["marginal"],marginal_costs_grouped.index])))
 
         costs.loc[idx[c.list_name,"marginal",list(marginal_costs_grouped.index)],label] = marginal_costs_grouped.values
 
     return costs
 
-def calculate_curtailment(n,label,curtailment):
+def calculate_curtailment(n, label, curtailment):
 
     avail = n.generators_t.p_max_pu.multiply(n.generators.p_nom_opt).sum().groupby(n.generators.carrier).sum()
     used = n.generators_t.p.sum().groupby(n.generators.carrier).sum()
@@ -140,7 +142,7 @@ def calculate_curtailment(n,label,curtailment):
 
     return curtailment
 
-def calculate_energy(n,label,energy):
+def calculate_energy(n, label, energy):
 
     for c in n.iterate_components(n.one_port_components|n.branch_components):
 
@@ -160,6 +162,7 @@ def include_in_summary(summary, multiindexprefix, label, item):
     summary = _add_indexed_rows(summary, raw_index)
 
     summary.loc[idx[raw_index], label] = item.values
+
     return summary
 
 def calculate_capacity(n,label,capacity):
@@ -179,7 +182,7 @@ def calculate_capacity(n,label,capacity):
 
     return capacity
 
-def calculate_supply(n,label,supply):
+def calculate_supply(n, label, supply):
     """calculate the max dispatch of each component at the buses where the loads are attached"""
 
     load_types = n.loads.carrier.value_counts().index
@@ -220,12 +223,13 @@ def calculate_supply(n,label,supply):
                 #lots of sign compensation for direction and to do maximums
                 s = (-1)**(1-int(end))*((-1)**int(end)*c.pnl["p"+end][items]).max().groupby(c.df.loc[items,'carrier']).sum()
 
-                supply = supply.reindex(supply.index|pd.MultiIndex.from_product([[i],[c.list_name],s.index]))
+                supply = supply.reindex(supply.index.union(pd.MultiIndex.from_product([[i],[c.list_name],s.index])))
                 supply.loc[idx[i,c.list_name,list(s.index)],label] = s.values
 
     return supply
 
-def calculate_supply_energy(n,label,supply_energy):
+
+def calculate_supply_energy(n, label, supply_energy):
     """calculate the total dispatch of each component at the buses where the loads are attached"""
 
     load_types = n.loads.carrier.value_counts().index
@@ -265,14 +269,15 @@ def calculate_supply_energy(n,label,supply_energy):
 
                 s = (-1)*c.pnl["p"+end][items].sum().groupby(c.df.loc[items,'carrier']).sum()
 
-                supply_energy = supply_energy.reindex(supply_energy.index|pd.MultiIndex.from_product([[i],[c.list_name],s.index]))
+                supply_energy = supply_energy.reindex(supply_energy.index.union(pd.MultiIndex.from_product([[i],[c.list_name],s.index])))
                 supply_energy.loc[idx[i,c.list_name,list(s.index)],label] = s.values
 
     return supply_energy
 
+
 def calculate_metrics(n,label,metrics):
 
-    metrics = metrics.reindex(metrics.index|pd.Index(["line_volume","line_volume_limit","line_volume_AC","line_volume_DC","line_volume_shadow","co2_shadow"]))
+    metrics = metrics.reindex(metrics.index.union(pd.Index(["line_volume","line_volume_limit","line_volume_AC","line_volume_DC","line_volume_shadow","co2_shadow"])))
 
     metrics.at["line_volume_DC",label] = (n.links.length*n.links.p_nom_opt)[n.links.carrier == "DC"].sum()
     metrics.at["line_volume_AC",label] = (n.lines.length*n.lines.s_nom_opt).sum()
@@ -294,18 +299,17 @@ def calculate_prices(n,label,prices):
 
     bus_type = pd.Series(n.buses.index.str[3:],n.buses.index).replace("","electricity")
 
-    prices = prices.reindex(prices.index|bus_type.value_counts().index)
+    prices = prices.reindex(prices.index.union(bus_type.value_counts().index))
 
-    #WARNING: this is time-averaged, should really be load-weighted average
+    logger.warning("Prices are time-averaged, not load-weighted")
     prices[label] = n.buses_t.marginal_price.mean().groupby(bus_type).mean()
 
     return prices
 
 
-
 def calculate_weighted_prices(n,label,weighted_prices):
-    # Warning: doesn't include storage units as loads
 
+    logger.warning("Weighted prices don't include storage units as loads")
 
     weighted_prices = weighted_prices.reindex(pd.Index(["electricity","heat","space heat","urban heat","space urban heat","gas","H2"]))
 
@@ -348,7 +352,7 @@ def calculate_weighted_prices(n,label,weighted_prices):
 
             load += n.links_t.p0[names].groupby(n.links.loc[names,"bus0"],axis=1).sum(axis=1)
 
-        #Add H2 Store when charging
+        # Add H2 Store when charging
         if carrier == "H2":
             stores = n.stores_t.p[buses+ " Store"].groupby(n.stores.loc[buses+ " Store","bus"],axis=1).sum(axis=1)
             stores[stores > 0.] = 0.
@@ -362,62 +366,6 @@ def calculate_weighted_prices(n,label,weighted_prices):
     return weighted_prices
 
 
-
-# BROKEN don't use
-#
-# def calculate_market_values(n, label, market_values):
-#     # Warning: doesn't include storage units
-
-#     n.buses["suffix"] = n.buses.index.str[2:]
-#     suffix = ""
-#     buses = n.buses.index[n.buses.suffix == suffix]
-
-#     ## First do market value of generators ##
-#     generators = n.generators.index[n.buses.loc[n.generators.bus,"suffix"] == suffix]
-#     techs = n.generators.loc[generators,"carrier"].value_counts().index
-#     market_values = market_values.reindex(market_values.index | techs)
-
-#     for tech in techs:
-#         gens = generators[n.generators.loc[generators,"carrier"] == tech]
-#         dispatch = n.generators_t.p[gens].groupby(n.generators.loc[gens,"bus"],axis=1).sum().reindex(columns=buses,fill_value=0.)
-#         revenue = dispatch*n.buses_t.marginal_price[buses]
-#         market_values.at[tech,label] = revenue.sum().sum()/dispatch.sum().sum()
-
-#     ## Now do market value of links ##
-
-#     for i in ["0","1"]:
-#         all_links = n.links.index[n.buses.loc[n.links["bus"+i],"suffix"] == suffix]
-#         techs = n.links.loc[all_links,"carrier"].value_counts().index
-#         market_values = market_values.reindex(market_values.index | techs)
-
-#         for tech in techs:
-#             links = all_links[n.links.loc[all_links,"carrier"] == tech]
-#             dispatch = n.links_t["p"+i][links].groupby(n.links.loc[links,"bus"+i],axis=1).sum().reindex(columns=buses,fill_value=0.)
-#             revenue = dispatch*n.buses_t.marginal_price[buses]
-#             market_values.at[tech,label] = revenue.sum().sum()/dispatch.sum().sum()
-
-#     return market_values
-
-
-# OLD CODE must be adapted
-
-# def calculate_price_statistics(n, label, price_statistics):
-
-
-#     price_statistics = price_statistics.reindex(price_statistics.index|pd.Index(["zero_hours","mean","standard_deviation"]))
-#     n.buses["suffix"] = n.buses.index.str[2:]
-#     suffix = ""
-#     buses = n.buses.index[n.buses.suffix == suffix]
-
-#     threshold = 0.1 #higher than phoney marginal_cost of wind/solar
-#     df = pd.DataFrame(data=0.,columns=buses,index=n.snapshots)
-#     df[n.buses_t.marginal_price[buses] < threshold] = 1.
-#     price_statistics.at["zero_hours", label] = df.sum().sum()/(df.shape[0]*df.shape[1])
-#     price_statistics.at["mean", label] = n.buses_t.marginal_price[buses].unstack().mean()
-#     price_statistics.at["standard_deviation", label] = n.buses_t.marginal_price[buses].unstack().std()
-#     return price_statistics
-
-
 outputs = ["costs",
            "curtailment",
            "energy",
@@ -426,11 +374,10 @@ outputs = ["costs",
            "supply_energy",
            "prices",
            "weighted_prices",
-           # "price_statistics",
-           # "market_values",
            "metrics",
            ]
 
+
 def make_summaries(networks_dict, country='all'):
 
     columns = pd.MultiIndex.from_tuples(networks_dict.keys(),names=["simpl","clusters","ll","opts"])
@@ -455,7 +402,7 @@ def make_summaries(networks_dict, country='all'):
         if country != 'all':
             n = n[n.buses.country == country]
 
-        Nyears = n.snapshot_weightings.sum()/8760.
+        Nyears = n.snapshot_weightings.sum() / 8760.
         costs = load_costs(Nyears, snakemake.input[0],
                            snakemake.config['costs'], snakemake.config['electricity'])
         update_transmission_costs(n, costs, simple_hvdc_costs=False)
@@ -485,7 +432,6 @@ if __name__ == "__main__":
         network_dir = os.path.join('results', 'networks')
     configure_logging(snakemake)
 
-
     def expand_from_wildcard(key):
         w = getattr(snakemake.wildcards, key)
         return snakemake.config["scenario"][key] if w == "all" else [w]
@@ -505,8 +451,6 @@ if __name__ == "__main__":
                      for l in ll
                      for opts in expand_from_wildcard("opts")}
 
-    print(networks_dict)
-
     dfs = make_summaries(networks_dict, country=snakemake.wildcards.country)
 
     to_csv(dfs)

scripts/plot_network.py

@@ -20,7 +20,6 @@ Description
 """
 
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import (load_network_for_plots, aggregate_p, aggregate_costs,
                       configure_logging)
 
@@ -35,6 +34,9 @@ from matplotlib.patches import Circle, Ellipse
 from matplotlib.legend_handler import HandlerPatch
 to_rgba = mpl.colors.colorConverter.to_rgba
 
+logger = logging.getLogger(__name__)
+
+
 def make_handler_map_to_scale_circles_as_in(ax, dont_resize_actively=False):
     fig = ax.get_figure()
     def axes2pt():
@@ -57,9 +59,11 @@ def make_handler_map_to_scale_circles_as_in(ax, dont_resize_actively=False):
         return e
     return {Circle: HandlerPatch(patch_func=legend_circle_handler)}
 
+
 def make_legend_circles_for(sizes, scale=1.0, **kw):
     return [Circle((0,0), radius=(s/scale)**0.5, **kw) for s in sizes]
 
+
 def set_plot_style():
     plt.style.use(['classic', 'seaborn-white',
                 {'axes.grid': False, 'grid.linestyle': '--', 'grid.color': u'0.6',
@@ -69,9 +73,9 @@ def set_plot_style():
                     'legend.fontsize': 'medium',
                     'lines.linewidth': 1.5,
                     'pdf.fonttype': 42,
-                    # 'font.family': 'Times New Roman'
                 }])
 
+
 def plot_map(n, ax=None, attribute='p_nom', opts={}):
     if ax is None:
         ax = plt.gca()
@@ -114,16 +118,11 @@ def plot_map(n, ax=None, attribute='p_nom', opts={}):
            bus_sizes=0,
            bus_colors=tech_colors,
            boundaries=map_boundaries,
-           geomap=True,   # TODO : Turn to False, after the release of PyPSA 0.14.2 (refer to https://github.com/PyPSA/PyPSA/issues/75)
+           geomap=False,
            ax=ax)
     ax.set_aspect('equal')
     ax.axis('off')
 
-    # x1, y1, x2, y2 = map_boundaries
-    # ax.set_xlim(x1, x2)
-    # ax.set_ylim(y1, y2)
-
-
     # Rasterize basemap
     # TODO : Check if this also works with cartopy
     for c in ax.collections[:2]: c.set_rasterized(True)
@@ -165,7 +164,7 @@ def plot_map(n, ax=None, attribute='p_nom', opts={}):
                 handler_map=make_handler_map_to_scale_circles_as_in(ax))
     ax.add_artist(l2)
 
-    techs =  (bus_sizes.index.levels[1]) & pd.Index(opts['vre_techs'] + opts['conv_techs'] + opts['storage_techs'])
+    techs =  (bus_sizes.index.levels[1]).intersection(pd.Index(opts['vre_techs'] + opts['conv_techs'] + opts['storage_techs']))
     handles = []
     labels = []
     for t in techs:
@@ -176,13 +175,9 @@ def plot_map(n, ax=None, attribute='p_nom', opts={}):
 
     return fig
 
-#n = load_network_for_plots(snakemake.input.network, opts, combine_hydro_ps=False)
-
 
 def plot_total_energy_pie(n, ax=None):
-    """Add total energy pie plot"""
-    if ax is None:
-        ax = plt.gca()
+    if ax is None: ax = plt.gca()
 
     ax.set_title('Energy per technology', fontdict=dict(fontsize="medium"))
 
@@ -190,7 +185,7 @@ def plot_total_energy_pie(n, ax=None):
 
     patches, texts, autotexts = ax.pie(e_primary,
         startangle=90,
-        labels = e_primary.rename(opts['nice_names_n']).index,
+        labels = e_primary.rename(opts['nice_names']).index,
         autopct='%.0f%%',
         shadow=False,
         colors = [opts['tech_colors'][tech] for tech in e_primary.index])
@@ -200,9 +195,7 @@ def plot_total_energy_pie(n, ax=None):
             t2.remove()
 
 def plot_total_cost_bar(n, ax=None):
-    """Add average system cost bar plot"""
-    if ax is None:
-        ax = plt.gca()
+    if ax is None: ax = plt.gca()
 
     total_load = (n.snapshot_weightings * n.loads_t.p.sum(axis=1)).sum()
     tech_colors = opts['tech_colors']
@@ -240,14 +233,13 @@ def plot_total_cost_bar(n, ax=None):
         if abs(data[-1]) < 5:
             continue
 
-        text = ax.text(1.1,(bottom-0.5*data)[-1]-3,opts['nice_names_n'].get(ind,ind))
+        text = ax.text(1.1,(bottom-0.5*data)[-1]-3,opts['nice_names'].get(ind,ind))
         texts.append(text)
 
     ax.set_ylabel("Average system cost [Eur/MWh]")
-    ax.set_ylim([0, 80]) # opts['costs_max']])
+    ax.set_ylim([0, opts.get('costs_max', 80)])
     ax.set_xlim([0, 1])
-    #ax.set_xticks([0.5])
-    ax.set_xticklabels([]) #["w/o\nEp", "w/\nEp"])
+    ax.set_xticklabels([])
     ax.grid(True, axis="y", color='k', linestyle='dotted')
 
 
@@ -280,8 +272,6 @@ if __name__ == "__main__":
     ax2 = fig.add_axes([-0.075, 0.1, 0.1, 0.45])
     plot_total_cost_bar(n, ax2)
 
-    #fig.tight_layout()
-
     ll = snakemake.wildcards.ll
     ll_type = ll[0]
     ll_factor = ll[1:]

scripts/plot_p_nom_max.py

@@ -19,19 +19,19 @@ Description
 
 """
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import configure_logging
 
 import pypsa
-
 import pandas as pd
 import matplotlib.pyplot as plt
 
+logger = logging.getLogger(__name__)
+
+
 def cum_p_nom_max(net, tech, country=None):
     carrier_b = net.generators.carrier == tech
 
-    generators = \
-    pd.DataFrame(dict(
+    generators = pd.DataFrame(dict(
         p_nom_max=net.generators.loc[carrier_b, 'p_nom_max'],
         p_max_pu=net.generators_t.p_max_pu.loc[:,carrier_b].mean(),
         country=net.generators.loc[carrier_b, 'bus'].map(net.buses.country)

scripts/plot_summary.py

@@ -21,41 +21,19 @@ Description
 
 import os
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import configure_logging
 
 import pandas as pd
 import matplotlib.pyplot as plt
 
-#consolidate and rename
-def rename_techs(label):
-    if label.startswith("central "):
-        label = label[len("central "):]
-    elif label.startswith("urban "):
-        label = label[len("urban "):]
+logger = logging.getLogger(__name__)
 
-    if "retrofitting" in label:
-        label = "building retrofitting"
-    elif "H2" in label:
+
+def rename_techs(label):
+    if "H2" in label:
         label = "hydrogen storage"
-    elif "CHP" in label:
-        label = "CHP"
-    elif "water tank" in label:
-        label = "water tanks"
-    elif label == "water tanks":
-        label = "hot water storage"
-    elif "gas" in label and label != "gas boiler":
-        label = "natural gas"
-    elif "solar thermal" in label:
-        label = "solar thermal"
     elif label == "solar":
         label = "solar PV"
-    elif label == "heat pump":
-        label = "air heat pump"
-    elif label == "Sabatier":
-        label = "methanation"
-    elif label == "offwind":
-        label = "offshore wind"
     elif label == "offwind-ac":
         label = "offshore wind ac"
     elif label == "offwind-dc":
@@ -68,15 +46,14 @@ def rename_techs(label):
         label = "hydroelectricity"
     elif label == "PHS":
         label = "hydroelectricity"
-    elif label == "co2 Store":
-        label = "DAC"
     elif "battery" in label:
         label = "battery storage"
 
     return label
 
 
-preferred_order = pd.Index(["transmission lines","hydroelectricity","hydro reservoir","run of river","pumped hydro storage","onshore wind","offshore wind ac", "offshore wind dc","solar PV","solar thermal","building retrofitting","ground heat pump","air heat pump","resistive heater","CHP","OCGT","gas boiler","gas","natural gas","methanation","hydrogen storage","battery storage","hot water storage"])
+preferred_order = pd.Index(["transmission lines","hydroelectricity","hydro reservoir","run of river","pumped hydro storage","onshore wind","offshore wind ac", "offshore wind dc","solar PV","solar thermal","OCGT","hydrogen storage","battery storage"])
+
 
 def plot_costs(infn, fn=None):
 

scripts/prepare_links_p_nom.py

@@ -37,11 +37,26 @@ Description
 """
 
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import configure_logging
 
 import pandas as pd
 
+logger = logging.getLogger(__name__)
+
+
+def multiply(s):
+    return s.str[0].astype(float) * s.str[1].astype(float)
+
+
+def extract_coordinates(s):
+    regex = (r"(\d{1,2})°(\d{1,2})′(\d{1,2})″(N|S) "
+             r"(\d{1,2})°(\d{1,2})′(\d{1,2})″(E|W)")
+    e = s.str.extract(regex, expand=True)
+    lat = (e[0].astype(float) + (e[1].astype(float) + e[2].astype(float)/60.)/60.)*e[3].map({'N': +1., 'S': -1.})
+    lon = (e[4].astype(float) + (e[5].astype(float) + e[6].astype(float)/60.)/60.)*e[7].map({'E': +1., 'W': -1.})
+    return lon, lat
+
+
 if __name__ == "__main__":
     if 'snakemake' not in globals():
         from _helpers import mock_snakemake #rule must be enabled in config
@@ -50,19 +65,11 @@ if __name__ == "__main__":
 
     links_p_nom = pd.read_html('https://en.wikipedia.org/wiki/List_of_HVDC_projects', header=0, match="SwePol")[0]
 
-    def extract_coordinates(s):
-        regex = (r"(\d{1,2})°(\d{1,2})′(\d{1,2})″(N|S) "
-                r"(\d{1,2})°(\d{1,2})′(\d{1,2})″(E|W)")
-        e = s.str.extract(regex, expand=True)
-        lat = (e[0].astype(float) + (e[1].astype(float) + e[2].astype(float)/60.)/60.)*e[3].map({'N': +1., 'S': -1.})
-        lon = (e[4].astype(float) + (e[5].astype(float) + e[6].astype(float)/60.)/60.)*e[7].map({'E': +1., 'W': -1.})
-        return lon, lat
+    mw = "Power (MW)"
+    m_b = links_p_nom[mw].str.contains('x').fillna(False)
 
-    m_b = links_p_nom["Power (MW)"].str.contains('x').fillna(False)
-    def multiply(s): return s.str[0].astype(float) * s.str[1].astype(float)
-
-    links_p_nom.loc[m_b, "Power (MW)"] = links_p_nom.loc[m_b, "Power (MW)"].str.split('x').pipe(multiply)
-    links_p_nom["Power (MW)"] = links_p_nom["Power (MW)"].str.extract("[-/]?([\d.]+)", expand=False).astype(float)
+    links_p_nom.loc[m_b, mw] = links_p_nom.loc[m_b, mw].str.split('x').pipe(multiply)
+    links_p_nom[mw] = links_p_nom[mw].str.extract("[-/]?([\d.]+)", expand=False).astype(float)
 
     links_p_nom['x1'], links_p_nom['y1'] = extract_coordinates(links_p_nom['Converterstation 1'])
     links_p_nom['x2'], links_p_nom['y2'] = extract_coordinates(links_p_nom['Converterstation 2'])

scripts/prepare_network.py

@@ -9,9 +9,10 @@ Prepare PyPSA network for solving according to :ref:`opts` and :ref:`ll`, such a
 - adding an annual **limit** of carbon-dioxide emissions,
 - adding an exogenous **price** per tonne emissions of carbon-dioxide (or other kinds),
 - setting an **N-1 security margin** factor for transmission line capacities,
-- specifying a limit on the **cost** of transmission expansion,
-- specifying a limit on the **volume** of transmission expansion, and
-- reducing the **temporal** resolution by averaging over multiple hours.
+- specifying an expansion limit on the **cost** of transmission expansion,
+- specifying an expansion limit on the **volume** of transmission expansion, and
+- reducing the **temporal** resolution by averaging over multiple hours
+  or segmenting time series into chunks of varying lengths using ``tsam``.
 
 Relevant Settings
 -----------------
@@ -38,12 +39,12 @@ Inputs
 ------
 
 - ``resources/costs.csv``: The database of cost assumptions for all included technologies for specific years from various sources; e.g. discount rate, lifetime, investment (CAPEX), fixed operation and maintenance (FOM), variable operation and maintenance (VOM), fuel costs, efficiency, carbon-dioxide intensity.
-- ``networks/{network}_s{simpl}_{clusters}.nc``: confer :ref:`cluster`
+- ``networks/elec_s{simpl}_{clusters}.nc``: confer :ref:`cluster`
 
 Outputs
 -------
 
-- ``networks/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc``: Complete PyPSA network that will be handed to the ``solve_network`` rule.
+- ``networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc``: Complete PyPSA network that will be handed to the ``solve_network`` rule.
 
 Description
 -----------
@@ -56,19 +57,21 @@ Description
 """
 
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import configure_logging
 
-from add_electricity import load_costs, update_transmission_costs
-from six import iteritems
-
-import numpy as np
 import re
 import pypsa
+import numpy as np
 import pandas as pd
+from six import iteritems
+
+from add_electricity import load_costs, update_transmission_costs
 
 idx = pd.IndexSlice
 
+logger = logging.getLogger(__name__)
+
+
 def add_co2limit(n, Nyears=1., factor=None):
 
     if factor is not None:
@@ -80,6 +83,7 @@ def add_co2limit(n, Nyears=1., factor=None):
           carrier_attribute="co2_emissions", sense="<=",
           constant=annual_emissions * Nyears)
 
+
 def add_emission_prices(n, emission_prices=None, exclude_co2=False):
     if emission_prices is None:
         emission_prices = snakemake.config['costs']['emission_prices']
@@ -91,88 +95,49 @@ def add_emission_prices(n, emission_prices=None, exclude_co2=False):
     su_ep = n.storage_units.carrier.map(ep) / n.storage_units.efficiency_dispatch
     n.storage_units['marginal_cost'] += su_ep
 
+
 def set_line_s_max_pu(n):
-    # set n-1 security margin to 0.5 for 37 clusters and to 0.7 from 200 clusters
-    n_clusters = len(n.buses)
-    s_max_pu = np.clip(0.5 + 0.2 * (n_clusters - 37) / (200 - 37), 0.5, 0.7)
+    s_max_pu = snakemake.config['lines']['s_max_pu']
     n.lines['s_max_pu'] = s_max_pu
+    logger.info(f"N-1 security margin of lines set to {s_max_pu}")
 
-def set_line_cost_limit(n, lc, Nyears=1.):
+
+def set_transmission_limit(n, ll_type, factor, Nyears=1):
     links_dc_b = n.links.carrier == 'DC' if not n.links.empty else pd.Series()
 
-    lines_s_nom = n.lines.s_nom.where(
-        n.lines.type == '',
-        np.sqrt(3) * n.lines.num_parallel *
-        n.lines.type.map(n.line_types.i_nom) *
-        n.lines.bus0.map(n.buses.v_nom)
-    )
+    _lines_s_nom = (np.sqrt(3) * n.lines.type.map(n.line_types.i_nom) *
+                   n.lines.num_parallel *  n.lines.bus0.map(n.buses.v_nom))
+    lines_s_nom = n.lines.s_nom.where(n.lines.type == '', _lines_s_nom)
 
-    n.lines['capital_cost_lc'] = n.lines['capital_cost']
-    n.links['capital_cost_lc'] = n.links['capital_cost']
-    total_line_cost = ((lines_s_nom * n.lines['capital_cost_lc']).sum() +
-                       n.links.loc[links_dc_b].eval('p_nom * capital_cost_lc').sum())
 
-    if lc == 'opt':
-        costs = load_costs(Nyears, snakemake.input.tech_costs,
-                           snakemake.config['costs'], snakemake.config['electricity'])
-        update_transmission_costs(n, costs, simple_hvdc_costs=False)
-    else:
-        # Either line_volume cap or cost
-        n.lines['capital_cost'] = 0.
-        n.links.loc[links_dc_b, 'capital_cost'] = 0.
+    col = 'capital_cost' if ll_type == 'c' else 'length'
+    ref = (lines_s_nom @ n.lines[col] +
+           n.links.loc[links_dc_b, "p_nom"] @ n.links.loc[links_dc_b, col])
 
-    if lc == 'opt' or float(lc) > 1.0:
+    costs = load_costs(Nyears, snakemake.input.tech_costs,
+                       snakemake.config['costs'],
+                       snakemake.config['electricity'])
+    update_transmission_costs(n, costs, simple_hvdc_costs=False)
+
+    if factor == 'opt' or float(factor) > 1.0:
         n.lines['s_nom_min'] = lines_s_nom
         n.lines['s_nom_extendable'] = True
 
         n.links.loc[links_dc_b, 'p_nom_min'] = n.links.loc[links_dc_b, 'p_nom']
         n.links.loc[links_dc_b, 'p_nom_extendable'] = True
 
-        if lc != 'opt':
-            line_cost = float(lc) * total_line_cost
-            n.add('GlobalConstraint', 'lc_limit',
-                  type='transmission_expansion_cost_limit',
-                  sense='<=', constant=line_cost, carrier_attribute='AC, DC')
+    if factor != 'opt':
+        con_type = 'expansion_cost' if ll_type == 'c' else 'volume_expansion'
+        rhs = float(factor) * ref
+        n.add('GlobalConstraint', f'l{ll_type}_limit',
+              type=f'transmission_{con_type}_limit',
+              sense='<=', constant=rhs, carrier_attribute='AC, DC')
+
     return n
 
-def set_line_volume_limit(n, lv, Nyears=1.):
-    links_dc_b = n.links.carrier == 'DC' if not n.links.empty else pd.Series()
-
-    lines_s_nom = n.lines.s_nom.where(
-        n.lines.type == '',
-        np.sqrt(3) * n.lines.num_parallel *
-        n.lines.type.map(n.line_types.i_nom) *
-        n.lines.bus0.map(n.buses.v_nom)
-    )
-
-    total_line_volume = ((lines_s_nom * n.lines['length']).sum() +
-                         n.links.loc[links_dc_b].eval('p_nom * length').sum())
-
-    if lv == 'opt':
-        costs = load_costs(Nyears, snakemake.input.tech_costs,
-                           snakemake.config['costs'], snakemake.config['electricity'])
-        update_transmission_costs(n, costs, simple_hvdc_costs=True)
-    else:
-        # Either line_volume cap or cost
-        n.lines['capital_cost'] = 0.
-        n.links.loc[links_dc_b, 'capital_cost'] = 0.
-
-    if lv == 'opt' or float(lv) > 1.0:
-        n.lines['s_nom_min'] = lines_s_nom
-        n.lines['s_nom_extendable'] = True
-
-        n.links.loc[links_dc_b, 'p_nom_min'] = n.links.loc[links_dc_b, 'p_nom']
-        n.links.loc[links_dc_b, 'p_nom_extendable'] = True
-
-        if lv != 'opt':
-            line_volume = float(lv) * total_line_volume
-            n.add('GlobalConstraint', 'lv_limit',
-                  type='transmission_volume_expansion_limit',
-                  sense='<=', constant=line_volume, carrier_attribute='AC, DC')
-    return n
 
 def average_every_nhours(n, offset):
-    logger.info('Resampling the network to {}'.format(offset))
+    logger.info(f"Resampling the network to {offset}")
     m = n.copy(with_time=False)
 
     snapshot_weightings = n.snapshot_weightings.resample(offset).sum()
@@ -187,18 +152,80 @@ def average_every_nhours(n, offset):
 
     return m
 
+def apply_time_segmentation(n, segments):
+    logger.info(f"Aggregating time series to {segments} segments.")
+    try:
+        import tsam.timeseriesaggregation as tsam
+    except:
+        raise ModuleNotFoundError("Optional dependency 'tsam' not found."
+                                  "Install via 'pip install tsam'")
+
+    p_max_pu_norm = n.generators_t.p_max_pu.max()
+    p_max_pu = n.generators_t.p_max_pu / p_max_pu_norm
+
+    load_norm = n.loads_t.p_set.max()
+    load = n.loads_t.p_set / load_norm
+    
+    inflow_norm = n.storage_units_t.inflow.max()
+    inflow = n.storage_units_t.inflow / inflow_norm
+
+    raw = pd.concat([p_max_pu, load, inflow], axis=1, sort=False)
+
+    solver_name = snakemake.config["solving"]["solver"]["name"]
+
+    agg = tsam.TimeSeriesAggregation(raw, hoursPerPeriod=len(raw),
+                                     noTypicalPeriods=1, noSegments=int(segments),
+                                     segmentation=True, solver=solver_name)
+
+    segmented = agg.createTypicalPeriods()
+
+    weightings = segmented.index.get_level_values("Segment Duration")
+    offsets = np.insert(np.cumsum(weightings[:-1]), 0, 0)
+    snapshots = [n.snapshots[0] + pd.Timedelta(f"{offset}h") for offset in offsets]
+
+    n.set_snapshots(pd.DatetimeIndex(snapshots, name='name'))
+    n.snapshot_weightings = pd.Series(weightings, index=snapshots, name="weightings", dtype="float64")
+    
+    segmented.index = snapshots
+    n.generators_t.p_max_pu = segmented[n.generators_t.p_max_pu.columns] * p_max_pu_norm
+    n.loads_t.p_set = segmented[n.loads_t.p_set.columns] * load_norm
+    n.storage_units_t.inflow = segmented[n.storage_units_t.inflow.columns] * inflow_norm
+
+    return n
+
+def enforce_autarky(n, only_crossborder=False):
+    if only_crossborder:
+        lines_rm = n.lines.loc[
+                        n.lines.bus0.map(n.buses.country) !=
+                        n.lines.bus1.map(n.buses.country)
+                    ].index
+        links_rm = n.links.loc[
+                        n.links.bus0.map(n.buses.country) !=
+                        n.links.bus1.map(n.buses.country)
+                    ].index
+    else:
+        lines_rm = n.lines.index
+        links_rm = n.links.loc[n.links.carrier=="DC"].index
+    n.mremove("Line", lines_rm)
+    n.mremove("Link", links_rm)
+
+def set_line_nom_max(n):
+    s_nom_max_set = snakemake.config["lines"].get("s_nom_max,", np.inf)
+    p_nom_max_set = snakemake.config["links"].get("p_nom_max", np.inf)
+    n.lines.s_nom_max.clip(upper=s_nom_max_set, inplace=True)
+    n.links.p_nom_max.clip(upper=p_nom_max_set, inplace=True)
 
 if __name__ == "__main__":
     if 'snakemake' not in globals():
         from _helpers import mock_snakemake
         snakemake = mock_snakemake('prepare_network', network='elec', simpl='',
-                                  clusters='5', ll='copt', opts='Co2L-24H')
+                                  clusters='40', ll='v0.3', opts='Co2L-24H')
     configure_logging(snakemake)
 
     opts = snakemake.wildcards.opts.split('-')
 
     n = pypsa.Network(snakemake.input[0])
-    Nyears = n.snapshot_weightings.sum()/8760.
+    Nyears = n.snapshot_weightings.sum() / 8760.
 
     set_line_s_max_pu(n)
 
@@ -207,8 +234,12 @@ if __name__ == "__main__":
         if m is not None:
             n = average_every_nhours(n, m.group(0))
             break
-    else:
-        logger.info("No resampling")
+
+    for o in opts:
+        m = re.match(r'^\d+seg$', o, re.IGNORECASE)
+        if m is not None:
+            n = apply_time_segmentation(n, m.group(0)[:-3])
+            break
 
     for o in opts:
         if "Co2L" in o:
@@ -217,27 +248,36 @@ if __name__ == "__main__":
                 add_co2limit(n, Nyears, float(m[0]))
             else:
                 add_co2limit(n, Nyears)
+            break
 
     for o in opts:
         oo = o.split("+")
-        if oo[0].startswith(tuple(n.carriers.index)):
+        suptechs = map(lambda c: c.split("-", 2)[0], n.carriers.index)
+        if oo[0].startswith(tuple(suptechs)):
             carrier = oo[0]
-            cost_factor = float(oo[1])
+            # handles only p_nom_max as stores and lines have no potentials
+            attr_lookup = {"p": "p_nom_max", "c": "capital_cost"}
+            attr = attr_lookup[oo[1][0]]
+            factor = float(oo[1][1:])
             if carrier == "AC":  # lines do not have carrier
-                n.lines.capital_cost *= cost_factor
+                n.lines[attr] *= factor
             else:
-                comps = {"Generator", "Link", "StorageUnit"}
+                comps = {"Generator", "Link", "StorageUnit", "Store"}
                 for c in n.iterate_components(comps):
                     sel = c.df.carrier.str.contains(carrier)
-                    c.df.loc[sel,"capital_cost"] *= cost_factor
+                    c.df.loc[sel,attr] *= factor
 
     if 'Ep' in opts:
         add_emission_prices(n)
 
     ll_type, factor = snakemake.wildcards.ll[0], snakemake.wildcards.ll[1:]
-    if ll_type == 'v':
-        set_line_volume_limit(n, factor, Nyears)
-    elif ll_type == 'c':
-        set_line_cost_limit(n, factor, Nyears)
+    set_transmission_limit(n, ll_type, factor, Nyears)
+
+    set_line_nom_max(n)
+
+    if "ATK" in opts:
+        enforce_autarky(n)
+    elif "ATKc" in opts:
+        enforce_autarky(n, only_crossborder=True)
 
     n.export_to_netcdf(snakemake.output[0])

scripts/retrieve_databundle.py

@@ -33,14 +33,15 @@ The :ref:`tutorial` uses a smaller `data bundle <https://zenodo.org/record/35179
 """
 
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import progress_retrieve, configure_logging
 
-from pathlib import Path
 import tarfile
+from pathlib import Path
+
+logger = logging.getLogger(__name__)
+
 
 if __name__ == "__main__":
-    # Detect running outside of snakemake and mock snakemake for testing
     if 'snakemake' not in globals():
         from _helpers import mock_snakemake
         snakemake = mock_snakemake('retrieve_databundle')

scripts/retrieve_natura_raster.py

@@ -30,10 +30,11 @@ This rule, as a substitute for :mod:`build_natura_raster`, downloads an already
 """
 
 import logging
-logger = logging.getLogger(__name__)
 
 from _helpers import progress_retrieve, configure_logging
 
+logger = logging.getLogger(__name__)
+
 if __name__ == "__main__":
     if 'snakemake' not in globals():
         from _helpers import mock_snakemake

scripts/simplify_network.py

@@ -48,23 +48,23 @@ Inputs
 - ``resources/costs.csv``: The database of cost assumptions for all included technologies for specific years from various sources; e.g. discount rate, lifetime, investment (CAPEX), fixed operation and maintenance (FOM), variable operation and maintenance (VOM), fuel costs, efficiency, carbon-dioxide intensity.
 - ``resources/regions_onshore.geojson``: confer :ref:`busregions`
 - ``resources/regions_offshore.geojson``: confer :ref:`busregions`
-- ``networks/{network}.nc``: confer :ref:`electricity`
+- ``networks/elec.nc``: confer :ref:`electricity`
 
 Outputs
 -------
 
-- ``resources/regions_onshore_{network}_s{simpl}.geojson``:
+- ``resources/regions_onshore_elec_s{simpl}.geojson``:
 
     .. image:: ../img/regions_onshore_elec_s.png
             :scale: 33 %
 
-- ``resources/regions_offshore_{network}_s{simpl}.geojson``:
+- ``resources/regions_offshore_elec_s{simpl}.geojson``:
 
     .. image:: ../img/regions_offshore_elec_s  .png
             :scale: 33 %
 
-- ``resources/clustermaps_{network}_s{simpl}.h5``: Mapping of buses from ``networks/elec.nc`` to ``networks/elec_s{simpl}.nc``; has keys ['/busmap_s']
-- ``networks/{network}_s{simpl}.nc``:
+- ``resources/busmap_elec_s{simpl}.csv``: Mapping of buses from ``networks/elec.nc`` to ``networks/elec_s{simpl}.nc``;
+- ``networks/elec_s{simpl}.nc``:
 
     .. image:: ../img/elec_s.png
         :scale: 33 %
@@ -84,7 +84,6 @@ The rule :mod:`simplify_network` does up to four things:
 """
 
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import configure_logging
 
 from cluster_network import clustering_for_n_clusters, cluster_regions
@@ -102,7 +101,8 @@ import pypsa
 from pypsa.io import import_components_from_dataframe, import_series_from_dataframe
 from pypsa.networkclustering import busmap_by_stubs, aggregategenerators, aggregateoneport
 
-idx = pd.IndexSlice
+logger = logging.getLogger(__name__)
+
 
 def simplify_network_to_380(n):
     ## All goes to v_nom == 380
@@ -139,6 +139,7 @@ def simplify_network_to_380(n):
 
     return n, trafo_map
 
+
 def _prepare_connection_costs_per_link(n):
     if n.links.empty: return {}
 
@@ -157,6 +158,7 @@ def _prepare_connection_costs_per_link(n):
 
     return connection_costs_per_link
 
+
 def _compute_connection_costs_to_bus(n, busmap, connection_costs_per_link=None, buses=None):
     if connection_costs_per_link is None:
         connection_costs_per_link = _prepare_connection_costs_per_link(n)
@@ -176,6 +178,7 @@ def _compute_connection_costs_to_bus(n, busmap, connection_costs_per_link=None,
 
     return connection_costs_to_bus
 
+
 def _adjust_capital_costs_using_connection_costs(n, connection_costs_to_bus):
     for tech in connection_costs_to_bus:
         tech_b = n.generators.carrier == tech
@@ -185,6 +188,7 @@ def _adjust_capital_costs_using_connection_costs(n, connection_costs_to_bus):
             logger.info("Displacing {} generator(s) and adding connection costs to capital_costs: {} "
                         .format(tech, ", ".join("{:.0f} Eur/MW/a for `{}`".format(d, b) for b, d in costs.iteritems())))
 
+
 def _aggregate_and_move_components(n, busmap, connection_costs_to_bus, aggregate_one_ports={"Load", "StorageUnit"}):
     def replace_components(n, c, df, pnl):
         n.mremove(c, n.df(c).index)
@@ -209,6 +213,7 @@ def _aggregate_and_move_components(n, busmap, connection_costs_to_bus, aggregate
         df = n.df(c)
         n.mremove(c, df.index[df.bus0.isin(buses_to_del) | df.bus1.isin(buses_to_del)])
 
+
 def simplify_links(n):
     ## Complex multi-node links are folded into end-points
     logger.info("Simplifying connected link components")
@@ -304,6 +309,7 @@ def simplify_links(n):
     _aggregate_and_move_components(n, busmap, connection_costs_to_bus)
     return n, busmap
 
+
 def remove_stubs(n):
     logger.info("Removing stubs")
 
@@ -315,8 +321,9 @@ def remove_stubs(n):
 
     return n, busmap
 
+
 def cluster(n, n_clusters):
-    logger.info("Clustering to {} buses".format(n_clusters))
+    logger.info(f"Clustering to {n_clusters} buses")
 
     renewable_carriers = pd.Index([tech
                                     for tech in n.generators.carrier.unique()
@@ -330,11 +337,12 @@ def cluster(n, n_clusters):
     potential_mode = (consense(pd.Series([snakemake.config['renewable'][tech]['potential']
                                             for tech in renewable_carriers]))
                         if len(renewable_carriers) > 0 else 'conservative')
-    clustering = clustering_for_n_clusters(n, n_clusters, potential_mode=potential_mode,
+    clustering = clustering_for_n_clusters(n, n_clusters, custom_busmap=False, potential_mode=potential_mode,
                                            solver_name=snakemake.config['solving']['solver']['name'])
 
     return clustering.network, clustering.busmap
 
+
 if __name__ == "__main__":
     if 'snakemake' not in globals():
         from _helpers import mock_snakemake
@@ -357,8 +365,7 @@ if __name__ == "__main__":
 
     n.export_to_netcdf(snakemake.output.network)
 
-    busemap_s = reduce(lambda x, y: x.map(y), busmaps[1:], busmaps[0])
-    with pd.HDFStore(snakemake.output.clustermaps, mode='w') as store:
-        store.put('busmap_s', busemap_s, format="table", index=False)
+    busmap_s = reduce(lambda x, y: x.map(y), busmaps[1:], busmaps[0])
+    busmap_s.to_csv(snakemake.output.busmap)
 
     cluster_regions(busmaps, snakemake.input, snakemake.output)

scripts/solve_network.py

@@ -10,10 +10,6 @@ Relevant Settings
 
 .. code:: yaml
 
-    (electricity:)
-        (BAU_mincapacities:)
-        (SAFE_reservemargin:)
-
     solving:
         tmpdir:
         options:
@@ -28,10 +24,6 @@ Relevant Settings
             track_iterations:
         solver:
             name:
-            (solveroptions):
-
-    (plotting:)
-        (conv_techs:)
 
 .. seealso::
     Documentation of the configuration file ``config.yaml`` at
@@ -40,12 +32,12 @@ Relevant Settings
 Inputs
 ------
 
-- ``networks/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc``: confer :ref:`prepare`
+- ``networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc``: confer :ref:`prepare`
 
 Outputs
 -------
 
-- ``results/networks/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc``: Solved PyPSA network including optimisation results
+- ``results/networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc``: Solved PyPSA network including optimisation results
 
     .. image:: ../img/results.png
         :scale: 40 %
@@ -85,18 +77,22 @@ Details (and errors made through this heuristic) are discussed in the paper
 """
 
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import configure_logging
 
 import numpy as np
 import pandas as pd
+import re
 
 import pypsa
 from pypsa.linopf import (get_var, define_constraints, linexpr, join_exprs,
                           network_lopf, ilopf)
+
 from pathlib import Path
 from vresutils.benchmark import memory_logger
 
+logger = logging.getLogger(__name__)
+
+
 def prepare_network(n, solve_opts):
 
     if 'clip_p_max_pu' in solve_opts:
@@ -167,6 +163,34 @@ def add_CCL_constraints(n, config):
                                            '<=', maximum, 'agg_p_nom', 'max')
 
 
+def add_EQ_constraints(n, o, scaling=1e-1):
+    float_regex = "[0-9]*\.?[0-9]+"
+    level = float(re.findall(float_regex, o)[0])
+    if o[-1] == 'c':
+        ggrouper = n.generators.bus.map(n.buses.country)
+        lgrouper = n.loads.bus.map(n.buses.country)
+        sgrouper = n.storage_units.bus.map(n.buses.country)
+    else:
+        ggrouper = n.generators.bus
+        lgrouper = n.loads.bus
+        sgrouper = n.storage_units.bus
+    load = n.snapshot_weightings @ \
+           n.loads_t.p_set.groupby(lgrouper, axis=1).sum()
+    inflow = n.snapshot_weightings @ \
+             n.storage_units_t.inflow.groupby(sgrouper, axis=1).sum()
+    inflow = inflow.reindex(load.index).fillna(0.)
+    rhs = scaling * ( level * load - inflow )
+    lhs_gen = linexpr((n.snapshot_weightings * scaling,
+                       get_var(n, "Generator", "p").T)
+              ).T.groupby(ggrouper, axis=1).apply(join_exprs)
+    lhs_spill = linexpr((-n.snapshot_weightings * scaling,
+                         get_var(n, "StorageUnit", "spill").T)
+                ).T.groupby(sgrouper, axis=1).apply(join_exprs)
+    lhs_spill = lhs_spill.reindex(lhs_gen.index).fillna("")
+    lhs = lhs_gen + lhs_spill
+    define_constraints(n, lhs, ">=", rhs, "equity", "min")
+
+
 def add_BAU_constraints(n, config):
     mincaps = pd.Series(config['electricity']['BAU_mincapacities'])
     lhs = (linexpr((1, get_var(n, 'Generator', 'p_nom')))
@@ -211,21 +235,25 @@ def extra_functionality(n, snapshots):
         add_SAFE_constraints(n, config)
     if 'CCL' in opts and n.generators.p_nom_extendable.any():
         add_CCL_constraints(n, config)
+    for o in opts:
+        if "EQ" in o:
+            add_EQ_constraints(n, o)
     add_battery_constraints(n)
 
 
 def solve_network(n, config, solver_log=None, opts='', **kwargs):
     solver_options = config['solving']['solver'].copy()
     solver_name = solver_options.pop('name')
-    track_iterations = config['solving']['options'].get('track_iterations', False)
-    min_iterations = config['solving']['options'].get('min_iterations', 4)
-    max_iterations = config['solving']['options'].get('max_iterations', 6)
+    cf_solving = config['solving']['options']
+    track_iterations = cf_solving.get('track_iterations', False)
+    min_iterations = cf_solving.get('min_iterations', 4)
+    max_iterations = cf_solving.get('max_iterations', 6)
 
     # add to network for extra_functionality
     n.config = config
     n.opts = opts
 
-    if config['solving']['options'].get('skip_iterations', False):
+    if cf_solving.get('skip_iterations', False):
         network_lopf(n, solver_name=solver_name, solver_options=solver_options,
                      extra_functionality=extra_functionality, **kwargs)
     else:
@@ -250,8 +278,8 @@ if __name__ == "__main__":
     opts = snakemake.wildcards.opts.split('-')
     solve_opts = snakemake.config['solving']['options']
 
-    with memory_logger(filename=getattr(snakemake.log, 'memory', None),
-                       interval=30.) as mem:
+    fn = getattr(snakemake.log, 'memory', None)
+    with memory_logger(filename=fn, interval=30.) as mem:
         n = pypsa.Network(snakemake.input[0])
         n = prepare_network(n, solve_opts)
         n = solve_network(n, config=snakemake.config, solver_dir=tmpdir,

scripts/solve_operations_network.py

@@ -32,13 +32,13 @@ Relevant Settings
 Inputs
 ------
 
-- ``networks/{network}_s{simpl}_{clusters}.nc``: confer :ref:`cluster`
-- ``results/networks/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc``: confer :ref:`solve`
+- ``networks/elec_s{simpl}_{clusters}.nc``: confer :ref:`cluster`
+- ``results/networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc``: confer :ref:`solve`
 
 Outputs
 -------
 
-- ``results/networks/{network}_s{simpl}_{clusters}_ec_l{ll}_{opts}_op.nc``: Solved PyPSA network for optimal dispatch including optimisation results
+- ``results/networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_op.nc``: Solved PyPSA network for optimal dispatch including optimisation results
 
 Description
 -----------
@@ -46,7 +46,6 @@ Description
 """
 
 import logging
-logger = logging.getLogger(__name__)
 from _helpers import configure_logging
 
 import pypsa
@@ -56,6 +55,8 @@ from pathlib import Path
 from vresutils.benchmark import memory_logger
 from solve_network import solve_network, prepare_network
 
+logger = logging.getLogger(__name__)
+
 def set_parameters_from_optimized(n, n_optim):
     lines_typed_i = n.lines.index[n.lines.type != '']
     n.lines.loc[lines_typed_i, 'num_parallel'] = \
@@ -107,7 +108,8 @@ if __name__ == "__main__":
     opts = snakemake.wildcards.opts.split('-')
     config['solving']['options']['skip_iterations'] = False
 
-    with memory_logger(filename=getattr(snakemake.log, 'memory', None), interval=30.) as mem:
+    fn = getattr(snakemake.log, 'memory', None)
+    with memory_logger(filename=fn, interval=30.) as mem:
         n = prepare_network(n, solve_opts=snakemake.config['solving']['options'])
         n = solve_network(n, config, solver_dir=tmpdir,
                           solver_log=snakemake.log.solver, opts=opts)

test/config.test1.yaml

@@ -2,7 +2,7 @@
 #
 # SPDX-License-Identifier: CC0-1.0
 
-version: 0.2.0
+version: 0.3.0
 tutorial: true
 logging:
   level: INFO
@@ -11,7 +11,6 @@ logging:
 summary_dir: results
 
 scenario:
-  sectors: [E]
   simpl: ['']
   ll: ['copt']
   clusters: [5]
@@ -32,6 +31,7 @@ enable:
   retrieve_cutout: true
   build_natura_raster: false
   retrieve_natura_raster: true
+  custom_busmap: false
 
 electricity:
   voltages: [220., 300., 380.]
@@ -131,11 +131,13 @@ lines:
     300.: "Al/St 240/40 3-bundle 300.0"
     380.: "Al/St 240/40 4-bundle 380.0"
   s_max_pu: 0.7
+  s_nom_max: .inf
   length_factor: 1.25
   under_construction: 'zero' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity
 
 links:
   p_max_pu: 1.0
+  p_nom_max: .inf
   include_tyndp: true
   under_construction: 'zero' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity
 
@@ -145,6 +147,11 @@ transformers:
   type: ''
 
 load:
+  url: https://data.open-power-system-data.org/time_series/2019-06-05/time_series_60min_singleindex.csv
+  power_statistics: True # only for files from <2019; set false in order to get ENTSOE transparency data 
+  interpolate_limit: 3 # data gaps up until this size are interpolated linearly
+  time_shift_for_large_gaps: 1w # data gaps up until this size are copied by copying from 
+  manual_adjustments: true # false
   scaling_factor: 1.0
 
 costs:
@@ -244,67 +251,18 @@ plotting:
     'waste' : '#68896b'
     'geothermal' : '#ba91b1'
     "OCGT" : "#d35050"
-    "OCGT marginal" : "#d35050"
-    "OCGT-heat" : "#d35050"
-    "gas boiler" : "#d35050"
-    "gas boilers" : "#d35050"
-    "gas boiler marginal" : "#d35050"
-    "gas-to-power/heat" : "#d35050"
     "gas" : "#d35050"
     "natural gas" : "#d35050"
     "CCGT" : "#b20101"
-    "CCGT marginal" : "#b20101"
-    "Nuclear" : "#ff9000"
-    "Nuclear marginal" : "#ff9000"
     "nuclear" : "#ff9000"
     "coal" : "#707070"
-    "Coal" : "#707070"
-    "Coal marginal" : "#707070"
     "lignite" : "#9e5a01"
-    "Lignite" : "#9e5a01"
-    "Lignite marginal" : "#9e5a01"
-    "Oil" : "#262626"
     "oil" : "#262626"
     "H2" : "#ea048a"
     "hydrogen storage" : "#ea048a"
-    "Sabatier" : "#a31597"
-    "methanation" : "#a31597"
-    "helmeth" : "#a31597"
-    "DAC" : "#d284ff"
-    "co2 stored" : "#e5e5e5"
-    "CO2 sequestration" : "#e5e5e5"
     "battery" : "#b8ea04"
-    "battery storage" : "#b8ea04"
-    "Li ion" : "#b8ea04"
-    "BEV charger" : "#e2ff7c"
-    "V2G" : "#7a9618"
-    "transport fuel cell" : "#e884be"
-    "retrofitting" : "#e0d6a8"
-    "building retrofitting" : "#e0d6a8"
-    "heat pumps" : "#ff9768"
-    "heat pump" : "#ff9768"
-    "air heat pump" : "#ffbea0"
-    "ground heat pump" : "#ff7a3d"
-    "power-to-heat" : "#a59e7c"
-    "power-to-gas" : "#db8585"
-    "power-to-liquid" : "#a9acd1"
-    "Fischer-Tropsch" : "#a9acd1"
-    "resistive heater" : "#aa4925"
-    "water tanks" : "#401f75"
-    "hot water storage" : "#401f75"
-    "hot water charging" : "#351c5e"
-    "hot water discharging" : "#683ab2"
-    "CHP" : "#d80a56"
-    "CHP heat" : "#d80a56"
-    "CHP electric" : "#d80a56"
-    "district heating" : "#93864b"
-    "Ambient" : "#262626"
     "Electric load" : "#f9d002"
     "electricity" : "#f9d002"
-    "Heat load" : "#d35050"
-    "heat" : "#d35050"
-    "Transport load" : "#235ebc"
-    "transport" : "#235ebc"
     "lines" : "#70af1d"
     "transmission lines" : "#70af1d"
     "AC-AC" : "#70af1d"
@@ -324,17 +282,5 @@ plotting:
     hydro: "Reservoir & Dam"
     battery: "Battery Storage"
     H2: "Hydrogen Storage"
-    lines: "Transmission lines"
-    ror: "Run of river"
-  nice_names_n:
-    OCGT: "Open-Cycle\nGas"
-    CCGT: "Combined-Cycle\nGas"
-    offwind-ac: "Offshore\nWind (AC)"
-    offwind-dc: "Offshore\nWind (DC)"
-    onwind: "Onshore\nWind"
-    battery: "Battery\nStorage"
-    H2: "Hydrogen\nStorage"
-    lines: "Transmission\nlines"
-    ror: "Run of\nriver"
-    PHS: "Pumped Hydro\nStorage"
-    hydro: "Reservoir\n& Dam"
+    lines: "Transmission Lines"
+    ror: "Run of River"