Merge branch 'master' into transport

.github/workflows/ci.yaml

@@ -0,0 +1,109 @@
+# SPDX-FileCopyrightText: : 2021 The PyPSA-Eur Authors
+#
+# SPDX-License-Identifier: CC0-1.0
+
+name: CI
+
+# Caching method based on and described by:
+# epassaro (2021): https://dev.to/epassaro/caching-anaconda-environments-in-github-actions-5hde
+# and code in GitHub repo: https://github.com/epassaro/cache-conda-envs
+
+on:
+  push:
+    branches:
+    - master
+  pull_request:
+    branches:
+    - master
+  schedule:
+    - cron: "0 5 * * TUE"
+
+env:
+  CONDA_CACHE_NUMBER: 1 # Change this value to manually reset the environment cache
+  DATA_CACHE_NUMBER: 1
+
+jobs:
+  build:
+
+    strategy:
+      matrix:
+        include:
+          # Matrix required to handle caching with Mambaforge
+          - os: ubuntu-latest
+            label: ubuntu-latest
+            prefix: /usr/share/miniconda3/envs/pypsa-eur
+
+          # - os: macos-latest
+          #   label: macos-latest
+          #   prefix: /Users/runner/miniconda3/envs/pypsa-eur
+
+          # - os: windows-latest
+          #   label: windows-latest
+          #   prefix: C:\Miniconda3\envs\pypsa-eur
+
+    name: ${{ matrix.label }}
+
+    runs-on: ${{ matrix.os }}
+    
+    defaults:
+      run:
+        shell: bash -l {0}
+        
+    steps:
+      - uses: actions/checkout@v2
+
+      - name: Clone pypsa-eur and technology-data repositories
+        run: |
+          git clone https://github.com/pypsa/pypsa-eur ../pypsa-eur
+          git clone https://github.com/pypsa/technology-data ../technology-data
+          cp ../pypsa-eur/test/config.test1.yaml ../pypsa-eur/config.yaml
+      
+      - name: Setup secrets
+        run: |
+          echo -ne "url: ${CDSAPI_URL}\nkey: ${CDSAPI_TOKEN}\n" > ~/.cdsapirc
+
+      - name: Add solver to environment
+        run: |
+          echo -e "  - coincbc\n  - ipopt<3.13.3" >> ../pypsa-eur/envs/environment.yaml
+
+      - name: Setup Mambaforge
+        uses: conda-incubator/setup-miniconda@v2
+        with:
+            miniforge-variant: Mambaforge
+            miniforge-version: latest
+            activate-environment: pypsa-eur
+            use-mamba: true
+            
+      - name: Set cache dates
+        run: |
+          echo "DATE=$(date +'%Y%m%d')" >> $GITHUB_ENV
+          echo "WEEK=$(date +'%Y%U')" >> $GITHUB_ENV
+
+      - name: Cache data and cutouts folders
+        uses: actions/cache@v3
+        with:
+          path: |
+            data
+            ../pypsa-eur/cutouts
+            ../pypsa-eur/data
+          key: data-cutouts-${{ env.WEEK }}-${{ env.DATA_CACHE_NUMBER }}
+
+      - name: Create environment cache
+        uses: actions/cache@v2
+        id: cache
+        with:
+          path: ${{ matrix.prefix }}
+          key: ${{ matrix.label }}-conda-${{ env.DATE }}-${{ env.CONDA_CACHE_NUMBER }}
+
+      - name: Update environment due to outdated or unavailable cache
+        run: mamba env update -n pypsa-eur -f ../pypsa-eur/envs/environment.yaml
+        if: steps.cache.outputs.cache-hit != 'true'
+
+      - name: Test snakemake workflow
+        run: |
+          conda activate pypsa-eur
+          conda list
+          cp test/config.overnight.yaml config.yaml
+          snakemake -call solve_all_networks
+          cp test/config.myopic.yaml config.yaml
+          snakemake -call solve_all_networks

Snakefile

@@ -45,18 +45,22 @@ rule prepare_sector_networks:
                **config['scenario'])
 
 datafiles = [
-    "eea/UNFCCC_v23.csv",
+    "data/eea/UNFCCC_v23.csv",
-    "switzerland-sfoe/switzerland-new_format.csv",
+    "data/switzerland-sfoe/switzerland-new_format.csv",
-    "nuts/NUTS_RG_10M_2013_4326_LEVL_2.geojson",
+    "data/nuts/NUTS_RG_10M_2013_4326_LEVL_2.geojson",
-    "myb1-2017-nitro.xls",
+    "data/myb1-2017-nitro.xls",
-    "Industrial_Database.csv",
+    "data/Industrial_Database.csv",
-    "emobility/KFZ__count",
+    "data/emobility/KFZ__count",
-    "emobility/Pkw__count",
+    "data/emobility/Pkw__count",
+    "data/h2_salt_caverns_GWh_per_sqkm.geojson",
+    directory("data/eurostat-energy_balances-june_2016_edition"),
+    directory("data/eurostat-energy_balances-may_2018_edition"),
+    directory("data/jrc-idees-2015"),
 ]
 
 if config.get('retrieve_sector_databundle', True):
     rule retrieve_sector_databundle:
-        output:  expand('data/{file}', file=datafiles)
+        output: *datafiles
         log: "logs/retrieve_sector_databundle.log"
         script: 'scripts/retrieve_sector_databundle.py'
 
@@ -252,9 +256,9 @@ rule build_biomass_potentials:
         enspreso_biomass=HTTP.remote("https://cidportal.jrc.ec.europa.eu/ftp/jrc-opendata/ENSPRESO/ENSPRESO_BIOMASS.xlsx", keep_local=True),
         nuts2="data/nuts/NUTS_RG_10M_2013_4326_LEVL_2.geojson", # https://gisco-services.ec.europa.eu/distribution/v2/nuts/download/#nuts21
         regions_onshore=pypsaeur("resources/regions_onshore_elec_s{simpl}_{clusters}.geojson"),
-        nuts3_population="../pypsa-eur/data/bundle/nama_10r_3popgdp.tsv.gz",
+        nuts3_population=pypsaeur("data/bundle/nama_10r_3popgdp.tsv.gz"),
-        swiss_cantons="../pypsa-eur/data/bundle/ch_cantons.csv",
+        swiss_cantons=pypsaeur("data/bundle/ch_cantons.csv"),
-        swiss_population="../pypsa-eur/data/bundle/je-e-21.03.02.xls",
+        swiss_population=pypsaeur("data/bundle/je-e-21.03.02.xls"),
         country_shapes=pypsaeur('resources/country_shapes.geojson')
     output:
         biomass_potentials_all='resources/biomass_potentials_all_s{simpl}_{clusters}.csv',

data/override_component_attrs/generators.csv

@@ -1,3 +1,4 @@
 attribute,type,unit,default,description,status
-build_year,integer,year,n/a,build year,Input (optional)
+carrier,string,n/a,n/a,carrier,Input (optional)
-lifetime,float,years,n/a,lifetime,Input (optional) 
+lifetime,float,years,inf,lifetime,Input (optional)
+build_year,int,year ,0,build year,Input (optional)

data/override_component_attrs/links.csv

@@ -2,12 +2,12 @@ attribute,type,unit,default,description,status
 bus2,string,n/a,n/a,2nd bus,Input (optional)
 bus3,string,n/a,n/a,3rd bus,Input (optional)
 bus4,string,n/a,n/a,4th bus,Input (optional)
-efficiency2,static or series,per unit,1.,2nd bus efficiency,Input (optional)
+efficiency2,static or series,per unit,1,2nd bus efficiency,Input (optional)
-efficiency3,static or series,per unit,1.,3rd bus efficiency,Input (optional)
+efficiency3,static or series,per unit,1,3rd bus efficiency,Input (optional)
-efficiency4,static or series,per unit,1.,4th bus efficiency,Input (optional)
+efficiency4,static or series,per unit,1,4th bus efficiency,Input (optional)
-p2,series,MW,0.,2nd bus output,Output
+p2,series,MW,0,2nd bus output,Output
-p3,series,MW,0.,3rd bus output,Output
+p3,series,MW,0,3rd bus output,Output
-p4,series,MW,0.,4th bus output,Output
+p4,series,MW,0,4th bus output,Output
-build_year,integer,year,n/a,build year,Input (optional)
-lifetime,float,years,n/a,lifetime,Input (optional)
 carrier,string,n/a,n/a,carrier,Input (optional)
+lifetime,float,years,inf,lifetime,Input (optional)
+build_year,int,year ,0,build year,Input (optional)

data/override_component_attrs/stores.csv

@@ -1,4 +1,4 @@
 attribute,type,unit,default,description,status
-build_year,integer,year,n/a,build year,Input (optional)
-lifetime,float,years,n/a,lifetime,Input (optional)
 carrier,string,n/a,n/a,carrier,Input (optional)
+lifetime,float,years,inf,lifetime,Input (optional)
+build_year,int,year ,0,build year,Input (optional)

scripts/add_brownfield.py

@@ -8,15 +8,22 @@ idx = pd.IndexSlice
 
 import pypsa
 import yaml
+import numpy as np
 
 from add_existing_baseyear import add_build_year_to_new_assets
 from helper import override_component_attrs
+from solve_network import basename
 
 
 def add_brownfield(n, n_p, year):
 
     print("adding brownfield")
 
+    # electric transmission grid set optimised capacities of previous as minimum
+    n.lines.s_nom_min = n_p.lines.s_nom_opt
+    dc_i = n.links[n.links.carrier=="DC"].index
+    n.links.loc[dc_i, "p_nom_min"] = n_p.links.loc[dc_i, "p_nom_opt"]
+
     for c in n_p.iterate_components(["Link", "Generator", "Store"]):
 
         attr = "e" if c.name == "Store" else "p"
@@ -25,7 +32,7 @@ def add_brownfield(n, n_p, year):
         # CO2 or global EU values since these are already in n
         n_p.mremove(
             c.name,
-            c.df.index[c.df.lifetime.isna()]
+            c.df.index[c.df.lifetime==np.inf]
         )
 
         # remove assets whose build_year + lifetime < year
@@ -44,7 +51,7 @@ def add_brownfield(n, n_p, year):
         )]
 
         threshold = snakemake.config['existing_capacities']['threshold_capacity']
-        
+
         if not chp_heat.empty:
             threshold_chp_heat = (threshold
                 * c.df.efficiency[chp_heat.str.replace("heat", "electric")].values
@@ -55,7 +62,7 @@ def add_brownfield(n, n_p, year):
                 c.name,
                 chp_heat[c.df.loc[chp_heat, attr + "_nom_opt"] < threshold_chp_heat]
             )
-        
+
         n_p.mremove(
             c.name,
             c.df.index[c.df[attr + "_nom_extendable"] & ~c.df.index.isin(chp_heat) & (c.df[attr + "_nom_opt"] < threshold)]
@@ -75,16 +82,44 @@ def add_brownfield(n, n_p, year):
         for tattr in n.component_attrs[c.name].index[selection]:
             n.import_series_from_dataframe(c.pnl[tattr], c.name, tattr)
 
+        # deal with gas network
+        pipe_carrier = ['gas pipeline']
+        if snakemake.config["sector"]['H2_retrofit']:
+            # drop capacities of previous year to avoid duplicating
+            to_drop = n.links.carrier.isin(pipe_carrier) & (n.links.build_year!=year)
+            n.mremove("Link", n.links.loc[to_drop].index)
 
+            # subtract the already retrofitted from today's gas grid capacity
+            h2_retrofitted_fixed_i = n.links[(n.links.carrier=='H2 pipeline retrofitted') & (n.links.build_year!=year)].index
+            gas_pipes_i =  n.links[n.links.carrier.isin(pipe_carrier)].index
+            CH4_per_H2 = 1 / snakemake.config["sector"]["H2_retrofit_capacity_per_CH4"]
+            fr = "H2 pipeline retrofitted"
+            to = "gas pipeline"
+            # today's pipe capacity
+            pipe_capacity = n.links.loc[gas_pipes_i, 'p_nom']
+            # already retrofitted capacity from gas -> H2
+            already_retrofitted = (n.links.loc[h2_retrofitted_fixed_i, 'p_nom']
+                                   .rename(lambda x: basename(x).replace(fr, to)).groupby(level=0).sum())
+            remaining_capacity = pipe_capacity - CH4_per_H2 * already_retrofitted.reindex(index=pipe_capacity.index).fillna(0)
+            n.links.loc[gas_pipes_i, "p_nom"] = remaining_capacity
+        else:
+            new_pipes = n.links.carrier.isin(pipe_carrier) & (n.links.build_year==year)
+            n.links.loc[new_pipes, "p_nom"] = 0.
+            n.links.loc[new_pipes, "p_nom_min"] = 0.
+
+
+
+#%%
 if __name__ == "__main__":
     if 'snakemake' not in globals():
         from helper import mock_snakemake
         snakemake = mock_snakemake(
             'add_brownfield',
             simpl='',
-            clusters=48,
+            clusters="37",
+            opts="",
             lv=1.0,
-            sector_opts='Co2L0-168H-T-H-B-I-solar3-dist1',
+            sector_opts='168H-T-H-B-I-solar+p3-dist1',
             planning_horizons=2030,
         )
 

scripts/add_existing_baseyear.py

@@ -12,9 +12,11 @@ import xarray as xr
 import pypsa
 import yaml
 
-from prepare_sector_network import prepare_costs
+from prepare_sector_network import prepare_costs, define_spatial
 from helper import override_component_attrs
 
+from types import SimpleNamespace
+spatial = SimpleNamespace()
 
 def add_build_year_to_new_assets(n, baseyear):
     """
@@ -28,7 +30,7 @@ def add_build_year_to_new_assets(n, baseyear):
     # Give assets with lifetimes and no build year the build year baseyear
     for c in n.iterate_components(["Link", "Generator", "Store"]):
 
-        assets = c.df.index[~c.df.lifetime.isna() & c.df.build_year==0]
+        assets = c.df.index[(c.df.lifetime!=np.inf) & (c.df.build_year==0)]
         c.df.loc[assets, "build_year"] = baseyear
 
         # add -baseyear to name
@@ -153,13 +155,13 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas
     df_agg.Fueltype = df_agg.Fueltype.map(rename_fuel)
 
     # assign clustered bus
-    busmap_s = pd.read_csv(snakemake.input.busmap_s, index_col=0, squeeze=True)
+    busmap_s = pd.read_csv(snakemake.input.busmap_s, index_col=0).squeeze()
-    busmap = pd.read_csv(snakemake.input.busmap, index_col=0, squeeze=True)
+    busmap = pd.read_csv(snakemake.input.busmap, index_col=0).squeeze()
 
     inv_busmap = {}
     for k, v in busmap.iteritems():
         inv_busmap[v] = inv_busmap.get(v, []) + [k]
-        
+
     clustermaps = busmap_s.map(busmap)
     clustermaps.index = clustermaps.index.astype(int)
 
@@ -197,10 +199,15 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas
         capacity = capacity[capacity > snakemake.config['existing_capacities']['threshold_capacity']]
 
         if generator in ['solar', 'onwind', 'offwind']:
-        
+
             suffix = '-ac' if generator == 'offwind' else ''
             name_suffix = f' {generator}{suffix}-{baseyear}'
 
+            # to consider electricity grid connection costs or a split between
+            # solar utility and rooftop as well, rather take cost assumptions
+            # from existing network than from the cost database
+            capital_cost = n.generators.loc[n.generators.carrier==generator+suffix, "capital_cost"].mean()
+
             if 'm' in snakemake.wildcards.clusters:
 
                 for ind in capacity.index:
@@ -213,14 +220,14 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas
 
                     p_max_pu = n.generators_t.p_max_pu[[i + name_suffix for i in inv_ind]]
                     p_max_pu.columns=[i + name_suffix for i in inv_ind ]
-                
+
                     n.madd("Generator",
                         [i + name_suffix for i in inv_ind],
                         bus=ind,
                         carrier=generator,
                         p_nom=capacity[ind] / len(inv_ind), # split among regions in a country
                         marginal_cost=costs.at[generator,'VOM'],
-                        capital_cost=costs.at[generator,'fixed'],
+                        capital_cost=capital_cost,
                         efficiency=costs.at[generator, 'efficiency'],
                         p_max_pu=p_max_pu,
                         build_year=grouping_year,
@@ -238,7 +245,7 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas
                     carrier=generator,
                     p_nom=capacity,
                     marginal_cost=costs.at[generator, 'VOM'],
-                    capital_cost=costs.at[generator, 'fixed'],
+                    capital_cost=capital_cost,
                     efficiency=costs.at[generator, 'efficiency'],
                     p_max_pu=p_max_pu.rename(columns=n.generators.bus),
                     build_year=grouping_year,
@@ -246,11 +253,14 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas
                 )
 
         else:
+            bus0 = vars(spatial)[carrier[generator]].nodes
+            if "EU" not in vars(spatial)[carrier[generator]].locations:
+                bus0 = bus0.intersection(capacity.index + " gas")
 
             n.madd("Link",
                 capacity.index,
                 suffix= " " + generator +"-" + str(grouping_year),
-                bus0="EU " + carrier[generator],
+                bus0=bus0,
                 bus1=capacity.index,
                 bus2="co2 atmosphere",
                 carrier=generator,
@@ -399,10 +409,11 @@ def add_heating_capacities_installed_before_baseyear(n, baseyear, grouping_years
                 lifetime=costs.at[costs_name, 'lifetime']
             )
 
+
             n.madd("Link",
                 nodes[name],
                 suffix= f" {name} gas boiler-{grouping_year}",
-                bus0="EU gas",
+                bus0=spatial.gas.nodes,
                 bus1=nodes[name] + " " + name + " heat",
                 bus2="co2 atmosphere",
                 carrier=name + " gas boiler",
@@ -417,7 +428,7 @@ def add_heating_capacities_installed_before_baseyear(n, baseyear, grouping_years
             n.madd("Link",
                 nodes[name],
                 suffix=f" {name} oil boiler-{grouping_year}",
-                bus0="EU oil",
+                bus0=spatial.oil.nodes,
                 bus1=nodes[name] + " " + name + " heat",
                 bus2="co2 atmosphere",
                 carrier=name + " oil boiler",
@@ -436,17 +447,17 @@ def add_heating_capacities_installed_before_baseyear(n, baseyear, grouping_years
             threshold = snakemake.config['existing_capacities']['threshold_capacity']
             n.mremove("Link", [index for index in n.links.index.to_list() if str(grouping_year) in index and n.links.p_nom[index] < threshold])
 
-
+#%%
 if __name__ == "__main__":
     if 'snakemake' not in globals():
         from helper import mock_snakemake
         snakemake = mock_snakemake(
             'add_existing_baseyear',
             simpl='',
-            clusters=45,
+            clusters="37",
             lv=1.0,
             opts='',
-            sector_opts='Co2L0-168H-T-H-B-I-solar+p3-dist1',
+            sector_opts='168H-T-H-B-I-solar+p3-dist1',
             planning_horizons=2020,
         )
 
@@ -459,7 +470,8 @@ if __name__ == "__main__":
 
     overrides = override_component_attrs(snakemake.input.overrides)
     n = pypsa.Network(snakemake.input.network, override_component_attrs=overrides)
-
+    # define spatial resolution of carriers
+    spatial = define_spatial(n.buses[n.buses.carrier=="AC"].index, options)
     add_build_year_to_new_assets(n, baseyear)
 
     Nyears = n.snapshot_weightings.generators.sum() / 8760.
@@ -471,7 +483,7 @@ if __name__ == "__main__":
         snakemake.config['costs']['lifetime']
     )
 
-    grouping_years=snakemake.config['existing_capacities']['grouping_years']
+    grouping_years = snakemake.config['existing_capacities']['grouping_years']
     add_power_capacities_installed_before_baseyear(n, grouping_years, costs, baseyear)
 
     if "H" in opts:

scripts/build_biomass_potentials.py

@@ -144,10 +144,12 @@ def build_nuts2_shapes():
     nuts2 = gpd.GeoDataFrame(gpd.read_file(snakemake.input.nuts2).set_index('id').geometry)
 
     countries = gpd.read_file(snakemake.input.country_shapes).set_index('name')
-    missing = countries.loc[["AL", "RS", "BA"]]
+    missing_iso2 = countries.index.intersection(["AL", "RS", "BA"])
+    missing = countries.loc[missing_iso2]
+
     nuts2.rename(index={"ME00": "ME", "MK00": "MK"}, inplace=True)
 
-    return nuts2.append(missing)
+    return pd.concat([nuts2, missing])
 
 
 def area(gdf):

scripts/build_gas_input_locations.py

@@ -26,7 +26,7 @@ def build_gas_input_locations(lng_fn, planned_lng_fn, entry_fn, prod_fn, countri
     planned_lng = pd.read_csv(planned_lng_fn)
     planned_lng.geometry = planned_lng.geometry.apply(wkt.loads)
     planned_lng = gpd.GeoDataFrame(planned_lng, crs=4326)
-    lng = lng.append(planned_lng, ignore_index=True)
+    lng = pd.concat([lng, planned_lng], ignore_index=True)
 
     # Entry points from outside the model scope
     entry = read_scigrid_gas(entry_fn)

scripts/build_industrial_production_per_country.py

@@ -115,14 +115,14 @@ def get_energy_ratio(country):
         # estimate physical output, energy consumption in the sector and country
         fn = f"{eurostat_dir}/{eb_names[country]}.XLSX"
         df = pd.read_excel(fn, sheet_name='2016', index_col=2,
-                           header=0, skiprows=1, squeeze=True)
+                           header=0, skiprows=1).squeeze('columns')
         e_country = df.loc[eb_sectors.keys(
         ), 'Total all products'].rename(eb_sectors)
 
     fn = f'{jrc_dir}/JRC-IDEES-2015_Industry_EU28.xlsx'
 
     df = pd.read_excel(fn, sheet_name='Ind_Summary',
-                       index_col=0, header=0, squeeze=True)
+                       index_col=0, header=0).squeeze('columns')
 
     assert df.index[48] == "by sector"
     year_i = df.columns.get_loc(year)
@@ -142,7 +142,7 @@ def industry_production_per_country(country):
         fn = f'{jrc_dir}/JRC-IDEES-2015_Industry_{jrc_country}.xlsx'
         sheet = sub_sheet_name_dict[sector]
         df = pd.read_excel(fn, sheet_name=sheet,
-                           index_col=0, header=0, squeeze=True)
+                           index_col=0, header=0).squeeze('columns')
 
         year_i = df.columns.get_loc(year)
         df = df.iloc[find_physical_output(df), year_i]

scripts/build_industry_sector_ratios.py

@@ -78,9 +78,8 @@ def load_idees_data(sector, country="EU28"):
         sheet_name=list(sheets.values()),
         index_col=0,
         header=0,
-        squeeze=True,
         usecols=usecols,
-    )
+    ).squeeze('columns')
 
     for k, v in sheets.items():
         idees[k] = idees.pop(v)

scripts/build_population_layouts.py

@@ -33,7 +33,7 @@ if __name__ == '__main__':
 
     urban_fraction = pd.read_csv(snakemake.input.urban_percent,
                                 header=None, index_col=0,
-                                names=['fraction'], squeeze=True) / 100.
+                                names=['fraction']).squeeze() / 100.
 
     # fill missing Balkans values
     missing = ["AL", "ME", "MK"]

scripts/plot_network.py

@@ -223,6 +223,26 @@ def plot_map(network, components=["links", "stores", "storage_units", "generator
         bbox_inches="tight"
     )
 
+def group_pipes(df, drop_direction=False):
+    """Group pipes which connect same buses and return overall capacity.
+    """
+    if drop_direction:
+        positive_order = df.bus0 < df.bus1
+        df_p = df[positive_order]
+        swap_buses = {"bus0": "bus1", "bus1": "bus0"}
+        df_n = df[~positive_order].rename(columns=swap_buses)
+        df = pd.concat([df_p, df_n])
+
+    # there are pipes for each investment period rename to AC buses name for plotting
+    df.index = df.apply(
+        lambda x: f"H2 pipeline {x.bus0.replace(' H2', '')} -> {x.bus1.replace(' H2', '')}",
+        axis=1
+    )
+    # group pipe lines connecting the same buses and rename them for plotting
+    pipe_capacity = df["p_nom_opt"].groupby(level=0).sum()
+
+    return pipe_capacity
+
 
 def plot_h2_map(network):
 
@@ -235,7 +255,7 @@ def plot_h2_map(network):
     bus_size_factor = 1e5
     linewidth_factor = 1e4
     # MW below which not drawn
-    line_lower_threshold = 1e3
+    line_lower_threshold = 1e2
 
     # Drop non-electric buses so they don't clutter the plot
     n.buses.drop(n.buses.index[n.buses.carrier != "AC"], inplace=True)
@@ -246,28 +266,20 @@ def plot_h2_map(network):
 
     # make a fake MultiIndex so that area is correct for legend
     bus_sizes.rename(index=lambda x: x.replace(" H2", ""), level=0, inplace=True)
-
+    # drop all links which are not H2 pipelines
     n.links.drop(n.links.index[~n.links.carrier.str.contains("H2 pipeline")], inplace=True)
 
-    h2_new = n.links.loc[n.links.carrier=="H2 pipeline", "p_nom_opt"]
+    h2_new = n.links.loc[n.links.carrier=="H2 pipeline"]
-
     h2_retro = n.links.loc[n.links.carrier=='H2 pipeline retrofitted']
+    # sum capacitiy for pipelines from different investment periods
+    h2_new = group_pipes(h2_new)
+    h2_retro = group_pipes(h2_retro, drop_direction=True).reindex(h2_new.index).fillna(0)
 
-    positive_order = h2_retro.bus0 < h2_retro.bus1
-    h2_retro_p = h2_retro[positive_order]
-    swap_buses = {"bus0": "bus1", "bus1": "bus0"}
-    h2_retro_n = h2_retro[~positive_order].rename(columns=swap_buses)
-    h2_retro = pd.concat([h2_retro_p, h2_retro_n])
-
-    h2_retro.index = h2_retro.apply(
-        lambda x: f"H2 pipeline {x.bus0.replace(' H2', '')} -> {x.bus1.replace(' H2', '')}",
-        axis=1
-    )
-
-    h2_retro = h2_retro["p_nom_opt"]
 
+    n.links.rename(index=lambda x: x.split("-2")[0], inplace=True)
+    n.links = n.links.groupby(level=0).first()
     link_widths_total = (h2_new + h2_retro) / linewidth_factor
-    link_widths_total = link_widths_total.groupby(level=0).sum().reindex(n.links.index).fillna(0.)
+    link_widths_total = link_widths_total.reindex(n.links.index).fillna(0.)
     link_widths_total[n.links.p_nom_opt < line_lower_threshold] = 0.
 
     retro = n.links.p_nom_opt.where(n.links.carrier=='H2 pipeline retrofitted', other=0.)
@@ -281,7 +293,7 @@ def plot_h2_map(network):
         figsize=(7, 6),
         subplot_kw={"projection": ccrs.PlateCarree()}
     )
-    
+
     n.plot(
         bus_sizes=bus_sizes,
         bus_colors=snakemake.config['plotting']['tech_colors'],
@@ -365,7 +377,7 @@ def plot_ch4_map(network):
     # Drop non-electric buses so they don't clutter the plot
     n.buses.drop(n.buses.index[n.buses.carrier != "AC"], inplace=True)
 
-    fossil_gas_i = n.generators[n.generators.carrier=="gas"].index   
+    fossil_gas_i = n.generators[n.generators.carrier=="gas"].index
     fossil_gas = n.generators_t.p.loc[:,fossil_gas_i].mul(n.snapshot_weightings.generators, axis=0).sum().groupby(n.generators.loc[fossil_gas_i,"bus"]).sum() / bus_size_factor
     fossil_gas.rename(index=lambda x: x.replace(" gas", ""), inplace=True)
     fossil_gas = fossil_gas.reindex(n.buses.index).fillna(0)
@@ -390,10 +402,10 @@ def plot_ch4_map(network):
     to_remove = n.links.index[~n.links.carrier.str.contains("gas pipeline")]
     n.links.drop(to_remove, inplace=True)
 
-    link_widths_rem = n.links.p_nom_opt / linewidth_factor  
+    link_widths_rem = n.links.p_nom_opt / linewidth_factor
     link_widths_rem[n.links.p_nom_opt < line_lower_threshold] = 0.
 
-    link_widths_orig = n.links.p_nom / linewidth_factor  
+    link_widths_orig = n.links.p_nom / linewidth_factor
     link_widths_orig[n.links.p_nom < line_lower_threshold] = 0.
 
     max_usage = n.links_t.p0.abs().max(axis=0)
@@ -422,7 +434,7 @@ def plot_ch4_map(network):
         link_colors='lightgrey',
         link_widths=link_widths_orig,
         branch_components=["Link"],
-        ax=ax, 
+        ax=ax,
         **map_opts
     )
 
@@ -452,7 +464,7 @@ def plot_ch4_map(network):
         facecolor='grey'
     )
     labels = ["{} TWh".format(s) for s in (10, 100)]
-    
+
     l2 = ax.legend(
         handles, labels,
         loc="upper left",
@@ -462,7 +474,7 @@ def plot_ch4_map(network):
         title='gas generation',
         handler_map=make_handler_map_to_scale_circles_as_in(ax)
     )
-    
+
     ax.add_artist(l2)
 
     handles = []
@@ -471,7 +483,7 @@ def plot_ch4_map(network):
     for s in (50, 10):
         handles.append(plt.Line2D([0], [0], color="grey", linewidth=s * 1e3 / linewidth_factor))
         labels.append("{} GW".format(s))
-    
+
     l1_1 = ax.legend(
         handles, labels,
         loc="upper left",
@@ -481,7 +493,7 @@ def plot_ch4_map(network):
         handletextpad=1.5,
         title='gas pipeline used capacity'
     )
-    
+
     ax.add_artist(l1_1)
 
     fig.savefig(
@@ -695,11 +707,11 @@ if __name__ == "__main__":
         snakemake = mock_snakemake(
             'plot_network',
             simpl='',
-            clusters=45,
+            clusters="45",
-            lv=1.5,
+            lv=1.0,
             opts='',
-            sector_opts='Co2L0-168H-T-H-B-I-solar+p3-dist1',
+            sector_opts='168H-T-H-B-I-A-solar+p3-dist1',
-            planning_horizons=2030,
+            planning_horizons="2050",
         )
 
     overrides = override_component_attrs(snakemake.input.overrides)

scripts/prepare_sector_network.py

@@ -27,7 +27,7 @@ from types import SimpleNamespace
 spatial = SimpleNamespace()
 
 
-def define_spatial(nodes):
+def define_spatial(nodes, options):
     """
     Namespace for spatial
 
@@ -37,7 +37,6 @@ def define_spatial(nodes):
     """
 
     global spatial
-    global options
 
     spatial.nodes = nodes
 
@@ -72,7 +71,7 @@ def define_spatial(nodes):
         spatial.co2.vents = ["co2 vent"]
 
     spatial.co2.df = pd.DataFrame(vars(spatial.co2), index=nodes)
-    
+
     # gas
 
     spatial.gas = SimpleNamespace()
@@ -94,6 +93,28 @@ def define_spatial(nodes):
 
     spatial.gas.df = pd.DataFrame(vars(spatial.gas), index=nodes)
 
+    # oil
+    spatial.oil = SimpleNamespace()
+    spatial.oil.nodes = ["EU oil"]
+    spatial.oil.locations = ["EU"]
+
+    # uranium
+    spatial.uranium = SimpleNamespace()
+    spatial.uranium.nodes = ["EU uranium"]
+    spatial.uranium.locations = ["EU"]
+
+    # coal
+    spatial.coal = SimpleNamespace()
+    spatial.coal.nodes = ["EU coal"]
+    spatial.coal.locations = ["EU"]
+
+    # lignite
+    spatial.lignite = SimpleNamespace()
+    spatial.lignite.nodes = ["EU lignite"]
+    spatial.lignite.locations = ["EU"]
+
+    return spatial
+
 
 from types import SimpleNamespace
 spatial = SimpleNamespace()
@@ -251,6 +272,7 @@ def create_network_topology(n, prefix, carriers=["DC"], connector=" -> ", bidire
 
     ln_attrs = ["bus0", "bus1", "length"]
     lk_attrs = ["bus0", "bus1", "length", "underwater_fraction"]
+    lk_attrs = n.links.columns.intersection(lk_attrs)
 
     candidates = pd.concat([
         n.lines[ln_attrs],
@@ -277,7 +299,7 @@ def create_network_topology(n, prefix, carriers=["DC"], connector=" -> ", bidire
         topo_reverse = topo.copy()
         topo_reverse.rename(columns=swap_buses, inplace=True)
         topo_reverse.index = topo_reverse.apply(make_index, axis=1)
-        topo = topo.append(topo_reverse)
+        topo = pd.concat([topo, topo_reverse])
 
     return topo
 
@@ -351,7 +373,8 @@ def add_carrier_buses(n, carrier, nodes=None):
     """
 
     if nodes is None:
-        nodes = ["EU " + carrier]
+        nodes = vars(spatial)[carrier].nodes
+    location = vars(spatial)[carrier].locations
 
     # skip if carrier already exists
     if carrier in n.carriers.index:
@@ -364,7 +387,7 @@ def add_carrier_buses(n, carrier, nodes=None):
 
     n.madd("Bus",
         nodes,
-        location=nodes.str.replace(" " + carrier, ""),
+        location=location,
         carrier=carrier
     )
 
@@ -572,7 +595,6 @@ def cycling_shift(df, steps=1):
     return df
 
 
-
 # TODO checkout PyPSA-Eur script
 def prepare_costs(cost_file, USD_to_EUR, discount_rate, Nyears, lifetime):
 
@@ -612,10 +634,8 @@ def add_generation(n, costs):
 
     for generator, carrier in conventionals.items():
 
-        if carrier == 'gas':
+
-            carrier_nodes = spatial.gas.nodes
+        carrier_nodes = vars(spatial)[carrier].nodes
-        else:
-            carrier_nodes = ["EU " + carrier]
 
         add_carrier_buses(n, carrier, carrier_nodes)
 
@@ -851,18 +871,20 @@ def add_storage_and_grids(n, costs):
     )
 
     cavern_types = snakemake.config["sector"]["hydrogen_underground_storage_locations"]
-    h2_caverns = pd.read_csv(snakemake.input.h2_cavern, index_col=0)[cavern_types].sum(axis=1)
+    h2_caverns = pd.read_csv(snakemake.input.h2_cavern, index_col=0)
 
-    # only use sites with at least 2 TWh potential
+    if not h2_caverns.empty and options['hydrogen_underground_storage']:
-    h2_caverns = h2_caverns[h2_caverns > 2]
-    
-    # convert TWh to MWh
-    h2_caverns = h2_caverns * 1e6
 
-    # clip at 1000 TWh for one location
+        h2_caverns = h2_caverns[cavern_types].sum(axis=1)
-    h2_caverns.clip(upper=1e9, inplace=True)
 
-    if options['hydrogen_underground_storage']:
+        # only use sites with at least 2 TWh potential
+        h2_caverns = h2_caverns[h2_caverns > 2]
+
+        # convert TWh to MWh
+        h2_caverns = h2_caverns * 1e6
+
+        # clip at 1000 TWh for one location
+        h2_caverns.clip(upper=1e9, inplace=True)
 
         logger.info("Add hydrogen underground storage")
 
@@ -875,7 +897,8 @@ def add_storage_and_grids(n, costs):
             e_nom_max=h2_caverns.values,
             e_cyclic=True,
             carrier="H2 Store",
-            capital_cost=h2_capital_cost
+            capital_cost=h2_capital_cost,
+            lifetime=costs.at["hydrogen storage underground", "lifetime"]
         )
 
     # hydrogen stored overground (where not already underground)
@@ -925,7 +948,7 @@ def add_storage_and_grids(n, costs):
             carrier="gas pipeline",
             lifetime=costs.at['CH4 (g) pipeline', 'lifetime']
         )
-        
+
         # remove fossil generators where there is neither
         # production, LNG terminal, nor entry-point beyond system scope
 
@@ -960,24 +983,27 @@ def add_storage_and_grids(n, costs):
 
         # apply k_edge_augmentation weighted by length of complement edges
         k_edge = options.get("gas_network_connectivity_upgrade", 3)
-        augmentation = k_edge_augmentation(G, k_edge, avail=complement_edges.values)
+        augmentation = list(k_edge_augmentation(G, k_edge, avail=complement_edges.values))
-        new_gas_pipes = pd.DataFrame(augmentation, columns=["bus0", "bus1"])
-        new_gas_pipes["length"] = new_gas_pipes.apply(haversine, axis=1)
 
-        new_gas_pipes.index = new_gas_pipes.apply(
+        if augmentation:
-            lambda x: f"gas pipeline new {x.bus0} <-> {x.bus1}", axis=1)
 
-        n.madd("Link",
+            new_gas_pipes = pd.DataFrame(augmentation, columns=["bus0", "bus1"])
-            new_gas_pipes.index,
+            new_gas_pipes["length"] = new_gas_pipes.apply(haversine, axis=1)
-            bus0=new_gas_pipes.bus0 + " gas",
+
-            bus1=new_gas_pipes.bus1 + " gas",
+            new_gas_pipes.index = new_gas_pipes.apply(
-            p_min_pu=-1, # new gas pipes are bidirectional
+                lambda x: f"gas pipeline new {x.bus0} <-> {x.bus1}", axis=1)
-            p_nom_extendable=True,
+
-            length=new_gas_pipes.length,
+            n.madd("Link",
-            capital_cost=new_gas_pipes.length * costs.at['CH4 (g) pipeline', 'fixed'],
+                new_gas_pipes.index,
-            carrier="gas pipeline new",
+                bus0=new_gas_pipes.bus0 + " gas",
-            lifetime=costs.at['CH4 (g) pipeline', 'lifetime']
+                bus1=new_gas_pipes.bus1 + " gas",
-        )
+                p_min_pu=-1, # new gas pipes are bidirectional
+                p_nom_extendable=True,
+                length=new_gas_pipes.length,
+                capital_cost=new_gas_pipes.length * costs.at['CH4 (g) pipeline', 'fixed'],
+                carrier="gas pipeline new",
+                lifetime=costs.at['CH4 (g) pipeline', 'lifetime']
+            )
 
     if options["H2_retrofit"]:
 
@@ -1225,10 +1251,10 @@ def add_land_transport(n, costs):
 
     if ice_share > 0:
 
-        if "EU oil" not in n.buses.index:
+        if "oil" not in n.buses.carrier.unique():
-            n.add("Bus",
+            n.madd("Bus",
-                "EU oil",
+                spatial.oil.nodes,
-                location="EU",
+                location=spatial.oil.locations,
                 carrier="oil"
             )
 
@@ -1237,7 +1263,7 @@ def add_land_transport(n, costs):
         n.madd("Load",
             nodes,
             suffix=" land transport oil",
-            bus="EU oil",
+            bus=spatial.oil.nodes,
             carrier="land transport oil",
             p_set=ice_share / ice_efficiency * transport[nodes]
         )
@@ -1743,8 +1769,7 @@ def add_biomass(n, costs):
         transport_costs = pd.read_csv(
             snakemake.input.biomass_transport_costs,
             index_col=0,
-            squeeze=True
+        ).squeeze()
-        )
 
         # add biomass transport
         biomass_transport = create_network_topology(n, "biomass transport ", bidirectional=False)
@@ -1955,7 +1980,7 @@ def add_industry(n, costs):
         n.madd("Load",
             nodes,
             suffix=" shipping oil",
-            bus="EU oil",
+            bus=spatial.oil.nodes,
             carrier="shipping oil",
             p_set=p_set
         )
@@ -1969,30 +1994,29 @@ def add_industry(n, costs):
             p_set=-co2
         )
 
-    if "EU oil" not in n.buses.index:
+    if "oil" not in n.buses.carrier.unique():
-
+        n.madd("Bus",
-        n.add("Bus",
+            spatial.oil.nodes,
-            "EU oil",
+            location=spatial.oil.locations,
-            location="EU",
             carrier="oil"
         )
 
-    if "EU oil Store" not in n.stores.index:
+    if "oil" not in n.stores.carrier.unique():
 
         #could correct to e.g. 0.001 EUR/kWh * annuity and O&M
-        n.add("Store",
+        n.madd("Store",
-            "EU oil Store",
+            [oil_bus + " Store" for oil_bus in spatial.oil.nodes],
-            bus="EU oil",
+            bus=spatial.oil.nodes,
             e_nom_extendable=True,
             e_cyclic=True,
             carrier="oil",
         )
 
-    if "EU oil" not in n.generators.index:
+    if "oil" not in n.generators.carrier.unique():
 
-        n.add("Generator",
+        n.madd("Generator",
-            "EU oil",
+            spatial.oil.nodes,
-            bus="EU oil",
+            bus=spatial.oil.nodes,
             p_nom_extendable=True,
             carrier="oil",
             marginal_cost=costs.at["oil", 'fuel']
@@ -2007,7 +2031,7 @@ def add_industry(n, costs):
             n.madd("Link",
                 nodes_heat[name] + f" {name} oil boiler",
                 p_nom_extendable=True,
-                bus0="EU oil",
+                bus0=spatial.oil.nodes,
                 bus1=nodes_heat[name] + f" {name}  heat",
                 bus2="co2 atmosphere",
                 carrier=f"{name} oil boiler",
@@ -2020,7 +2044,7 @@ def add_industry(n, costs):
     n.madd("Link",
         nodes + " Fischer-Tropsch",
         bus0=nodes + " H2",
-        bus1="EU oil",
+        bus1=spatial.oil.nodes,
         bus2=spatial.co2.nodes,
         carrier="Fischer-Tropsch",
         efficiency=costs.at["Fischer-Tropsch", 'efficiency'],
@@ -2030,9 +2054,9 @@ def add_industry(n, costs):
         lifetime=costs.at['Fischer-Tropsch', 'lifetime']
     )
 
-    n.add("Load",
+    n.madd("Load",
-        "naphtha for industry",
+        ["naphtha for industry"],
-        bus="EU oil",
+        bus=spatial.oil.nodes,
         carrier="naphtha for industry",
         p_set=industrial_demand.loc[nodes, "naphtha"].sum() / 8760
     )
@@ -2040,9 +2064,9 @@ def add_industry(n, costs):
     all_aviation = ["total international aviation", "total domestic aviation"]
     p_set = pop_weighted_energy_totals.loc[nodes, all_aviation].sum(axis=1).sum() * 1e6 / 8760
 
-    n.add("Load",
+    n.madd("Load",
-        "kerosene for aviation",
+        ["kerosene for aviation"],
-        bus="EU oil",
+        bus=spatial.oil.nodes,
         carrier="kerosene for aviation",
         p_set=p_set
     )
@@ -2195,7 +2219,7 @@ def add_agriculture(n, costs):
 
         n.add("Load",
             "agriculture machinery oil",
-            bus="EU oil",
+            bus=spatial.oil.nodes,
             carrier="agriculture machinery oil",
             p_set=ice_share * machinery_nodal_energy.sum() * 1e6 / 8760
         )
@@ -2301,7 +2325,7 @@ if __name__ == "__main__":
 
     patch_electricity_network(n)
 
-    define_spatial(pop_layout.index)
+    spatial = define_spatial(pop_layout.index, options)
 
     if snakemake.config["foresight"] == 'myopic':
 
@@ -2376,7 +2400,7 @@ if __name__ == "__main__":
         fn = snakemake.config['results_dir'] + snakemake.config['run'] + '/csvs/carbon_budget_distribution.csv'
         if not os.path.exists(fn):
             build_carbon_budget(o, fn)
-        co2_cap = pd.read_csv(fn, index_col=0, squeeze=True)
+        co2_cap = pd.read_csv(fn, index_col=0).squeeze()
         limit = co2_cap[investment_year]
         break
     for o in opts:

scripts/solve_network.py

@@ -33,14 +33,14 @@ def _add_land_use_constraint(n):
         existing = n.generators.loc[n.generators.carrier==carrier,"p_nom"].groupby(n.generators.bus.map(n.buses.location)).sum()
         existing.index += " " + carrier + "-" + snakemake.wildcards.planning_horizons
         n.generators.loc[existing.index,"p_nom_max"] -= existing
-    
+
     n.generators.p_nom_max.clip(lower=0, inplace=True)
 
 
 def _add_land_use_constraint_m(n):
     # if generators clustering is lower than network clustering, land_use accounting is at generators clusters
 
-    planning_horizons = snakemake.config["scenario"]["planning_horizons"] 
+    planning_horizons = snakemake.config["scenario"]["planning_horizons"]
     grouping_years = snakemake.config["existing_capacities"]["grouping_years"]
     current_horizon = snakemake.wildcards.planning_horizons
 
@@ -48,9 +48,9 @@ def _add_land_use_constraint_m(n):
 
         existing = n.generators.loc[n.generators.carrier==carrier,"p_nom"]
         ind = list(set([i.split(sep=" ")[0] + ' ' + i.split(sep=" ")[1] for i in existing.index]))
-        
+
         previous_years = [
-            str(y) for y in 
+            str(y) for y in
             planning_horizons + grouping_years
             if y < int(snakemake.wildcards.planning_horizons)
         ]
@@ -59,13 +59,13 @@ def _add_land_use_constraint_m(n):
             ind2 = [i for i in ind if i + " " + carrier + "-" + p_year in existing.index]
             sel_current = [i + " " + carrier + "-" + current_horizon for i in ind2]
             sel_p_year = [i + " " + carrier + "-" + p_year for i in ind2]
-            n.generators.loc[sel_current, "p_nom_max"] -= existing.loc[sel_p_year].rename(lambda x: x[:-4] + current_horizon) 
+            n.generators.loc[sel_current, "p_nom_max"] -= existing.loc[sel_p_year].rename(lambda x: x[:-4] + current_horizon)
-    
+
     n.generators.p_nom_max.clip(lower=0, inplace=True)
 
 
 def prepare_network(n, solve_opts=None):
-    
+
     if 'clip_p_max_pu' in solve_opts:
         for df in (n.generators_t.p_max_pu, n.generators_t.p_min_pu, n.storage_units_t.inflow):
             df.where(df>solve_opts['clip_p_max_pu'], other=0., inplace=True)
@@ -185,40 +185,43 @@ def add_chp_constraints(n):
 
         define_constraints(n, lhs, "<=", 0, 'chplink', 'backpressure')
 
+def basename(x):
+     return x.split("-2")[0]
 
 def add_pipe_retrofit_constraint(n):
     """Add constraint for retrofitting existing CH4 pipelines to H2 pipelines."""
 
-    gas_pipes_i = n.links[n.links.carrier=="gas pipeline"].index
+    gas_pipes_i = n.links.query("carrier == 'gas pipeline' and p_nom_extendable").index
-    h2_retrofitted_i = n.links[n.links.carrier=='H2 pipeline retrofitted'].index
+    h2_retrofitted_i = n.links.query("carrier == 'H2 pipeline retrofitted' and p_nom_extendable").index
 
     if h2_retrofitted_i.empty or gas_pipes_i.empty: return
 
     link_p_nom = get_var(n, "Link", "p_nom")
 
-    pipe_capacity = n.links.loc[gas_pipes_i, 'p_nom']
-
     CH4_per_H2 = 1 / n.config["sector"]["H2_retrofit_capacity_per_CH4"]
-
     fr = "H2 pipeline retrofitted"
     to = "gas pipeline"
+
+    pipe_capacity = n.links.loc[gas_pipes_i, 'p_nom'].rename(basename)
+
     lhs = linexpr(
         (CH4_per_H2, link_p_nom.loc[h2_retrofitted_i].rename(index=lambda x: x.replace(fr, to))),
         (1, link_p_nom.loc[gas_pipes_i])
     )
 
+    lhs.rename(basename, inplace=True)
     define_constraints(n, lhs, "=", pipe_capacity, 'Link', 'pipe_retrofit')
 
 
 def add_co2_sequestration_limit(n, sns):
-    
+
     co2_stores = n.stores.loc[n.stores.carrier=='co2 stored'].index
 
     if co2_stores.empty or ('Store', 'e') not in n.variables.index:
         return
-    
+
     vars_final_co2_stored = get_var(n, 'Store', 'e').loc[sns[-1], co2_stores]
-    
+
     lhs = linexpr((1, vars_final_co2_stored)).sum()
 
     limit = n.config["sector"].get("co2_sequestration_potential", 200) * 1e6
@@ -226,7 +229,7 @@ def add_co2_sequestration_limit(n, sns):
         if not "seq" in o: continue
         limit = float(o[o.find("seq")+3:])
         break
-    
+
     name = 'co2_sequestration_limit'
     sense = "<="
 
@@ -258,7 +261,7 @@ def solve_network(n, config, opts='', **kwargs):
 
     if cf_solving.get('skip_iterations', False):
         network_lopf(n, solver_name=solver_name, solver_options=solver_options,
-                     extra_functionality=extra_functionality, 
+                     extra_functionality=extra_functionality,
                      keep_shadowprices=keep_shadowprices, **kwargs)
     else:
         ilopf(n, solver_name=solver_name, solver_options=solver_options,
@@ -277,10 +280,11 @@ if __name__ == "__main__":
         snakemake = mock_snakemake(
             'solve_network',
             simpl='',
-            clusters=48,
+            opts="",
+            clusters="37",
             lv=1.0,
-            sector_opts='Co2L0-168H-T-H-B-I-solar3-dist1',
+            sector_opts='168H-T-H-B-I-A-solar+p3-dist1',
-            planning_horizons=2050,
+            planning_horizons="2030",
         )
 
     logging.basicConfig(filename=snakemake.log.python,

test/config.myopic.yaml

@@ -0,0 +1,607 @@
+version: 0.6.0
+
+logging_level: INFO
+
+retrieve_sector_databundle: true
+
+results_dir: results/
+summary_dir: results
+costs_dir: ../technology-data/outputs/
+run: test-myopic  # use this to keep track of runs with different settings
+foresight: myopic # options are overnight, myopic, perfect (perfect is not yet implemented)
+# if you use myopic or perfect foresight, set the investment years in "planning_horizons" below
+
+scenario:
+  simpl: # only relevant for PyPSA-Eur
+    - ''
+  lv: # allowed transmission line volume expansion, can be any float >= 1.0 (today) or "opt"
+    - 1.5
+  clusters: # number of nodes in Europe, any integer between 37 (1 node per country-zone) and several hundred
+    - 5
+  opts: # only relevant for PyPSA-Eur
+    - ''
+  sector_opts: # this is where the main scenario settings are
+    - 191H-T-H-B-I-A-solar+p3-dist1
+  # to really understand the options here, look in scripts/prepare_sector_network.py
+  # Co2Lx specifies the CO2 target in x% of the 1990 values; default will give default (5%);
+  # Co2L0p25 will give 25% CO2 emissions; Co2Lm0p05 will give 5% negative emissions
+  # xH is the temporal resolution; 3H is 3-hourly, i.e. one snapshot every 3 hours
+  # single letters are sectors: T for land transport, H for building heating,
+  # B for biomass supply, I for industry, shipping and aviation,
+  # A for agriculture, forestry and fishing
+  # solar+c0.5 reduces the capital cost of solar to 50\% of reference value
+  # solar+p3 multiplies the available installable potential by factor 3
+  # co2 stored+e2 multiplies the potential of CO2 sequestration by a factor 2
+  # dist{n} includes distribution grids with investment cost of n times cost in data/costs.csv
+  # for myopic/perfect foresight cb states the carbon budget in GtCO2 (cumulative
+  # emissions throughout the transition path in the timeframe determined by the
+  # planning_horizons), be:beta decay; ex:exponential decay
+  # cb40ex0 distributes a carbon budget of 40 GtCO2 following an exponential
+  # decay with initial growth rate 0
+  planning_horizons: # investment years for myopic and perfect; or costs year for overnight
+    - 2030
+    - 2040
+    - 2050
+  # for example, set to [2020, 2030, 2040, 2050] for myopic foresight
+
+# CO2 budget as a fraction of 1990 emissions
+# this is over-ridden if CO2Lx is set in sector_opts
+# this is also over-ridden if cb is set in sector_opts
+co2_budget:
+  2020: 0.7011648746
+  2025: 0.5241935484
+  2030: 0.2970430108
+  2035: 0.1500896057
+  2040: 0.0712365591
+  2045: 0.0322580645
+  2050: 0
+
+# snapshots are originally set in PyPSA-Eur/config.yaml but used again by PyPSA-Eur-Sec
+snapshots:
+  # arguments to pd.date_range
+  start: "2013-03-01"
+  end: "2013-04-01"
+  closed: left # end is not inclusive
+
+atlite:
+  cutout: ../pypsa-eur/cutouts/be-03-2013-era5.nc
+
+# this information is NOT used but needed as an argument for
+# pypsa-eur/scripts/add_electricity.py/load_costs in make_summary.py
+electricity:
+  max_hours:
+    battery: 6
+    H2: 168
+
+# regulate what components with which carriers are kept from PyPSA-Eur;
+# some technologies are removed because they are implemented differently
+# (e.g. battery or H2 storage) or have different year-dependent costs
+# in PyPSA-Eur-Sec
+pypsa_eur:
+  Bus:
+    - AC
+  Link:
+    - DC
+  Generator:
+    - onwind
+    - offwind-ac
+    - offwind-dc
+    - solar
+    - ror
+  StorageUnit:
+    - PHS
+    - hydro
+  Store: []
+
+
+energy:
+  energy_totals_year: 2011
+  base_emissions_year: 1990
+  eurostat_report_year: 2016
+  emissions: CO2 # "CO2" or "All greenhouse gases - (CO2 equivalent)"
+
+biomass:
+  year: 2030
+  scenario: ENS_Med
+  classes:
+    solid biomass:
+      - Agricultural waste
+      - Fuelwood residues
+      - Secondary Forestry residues - woodchips
+      - Sawdust
+      - Residues from landscape care
+      - Municipal waste
+    not included:
+      - Sugar from sugar beet
+      - Rape seed
+      - "Sunflower, soya seed "
+      - Bioethanol barley, wheat, grain maize, oats, other cereals and rye
+      - Miscanthus, switchgrass, RCG
+      - Willow
+      - Poplar
+      - FuelwoodRW
+      - C&P_RW
+    biogas:
+      - Manure solid, liquid
+      - Sludge
+
+
+solar_thermal:
+  clearsky_model: simple  # should be "simple" or "enhanced"?
+  orientation:
+    slope: 45.
+    azimuth: 180.
+
+# only relevant for foresight = myopic or perfect
+existing_capacities:
+  grouping_years: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2019]
+  threshold_capacity: 10
+  conventional_carriers:
+    - lignite
+    - coal
+    - oil
+    - uranium
+
+
+sector:
+  district_heating:
+    potential: 0.6  # maximum fraction of urban demand which can be supplied by district heating
+     # increase of today's district heating demand to potential maximum district heating share
+     # progress = 0 means today's district heating share, progress = 1 means maximum fraction of urban demand is supplied by district heating
+    progress:
+      2020: 0.0
+      2030: 0.3
+      2040: 0.6
+      2050: 1.0
+    district_heating_loss: 0.15
+  bev_dsm_restriction_value: 0.75  #Set to 0 for no restriction on BEV DSM
+  bev_dsm_restriction_time: 7  #Time at which SOC of BEV has to be dsm_restriction_value
+  transport_heating_deadband_upper: 20.
+  transport_heating_deadband_lower: 15.
+  ICE_lower_degree_factor: 0.375  #in per cent increase in fuel consumption per degree above deadband
+  ICE_upper_degree_factor: 1.6
+  EV_lower_degree_factor: 0.98
+  EV_upper_degree_factor: 0.63
+  bev_dsm: true #turns on EV battery
+  bev_availability: 0.5  #How many cars do smart charging
+  bev_energy: 0.05  #average battery size in MWh
+  bev_charge_efficiency: 0.9  #BEV (dis-)charging efficiency
+  bev_plug_to_wheel_efficiency: 0.2 #kWh/km from EPA https://www.fueleconomy.gov/feg/ for Tesla Model S
+  bev_charge_rate: 0.011 #3-phase charger with 11 kW
+  bev_avail_max: 0.95
+  bev_avail_mean: 0.8
+  v2g: true #allows feed-in to grid from EV battery
+  #what is not EV or FCEV is oil-fuelled ICE
+  land_transport_fuel_cell_share:
+    2020: 0
+    2030: 0.05
+    2040: 0.1
+    2050: 0.15
+  land_transport_electric_share:
+    2020: 0
+    2030: 0.25
+    2040: 0.6
+    2050: 0.85
+  transport_fuel_cell_efficiency: 0.5
+  transport_internal_combustion_efficiency: 0.3
+  agriculture_machinery_electric_share: 0
+  agriculture_machinery_fuel_efficiency: 0.7 # fuel oil per use
+  agriculture_machinery_electric_efficiency: 0.3 # electricity per use
+  shipping_average_efficiency: 0.4 #For conversion of fuel oil to propulsion in 2011
+  shipping_hydrogen_liquefaction: false # whether to consider liquefaction costs for shipping H2 demands
+  shipping_hydrogen_share:
+    2020: 0
+    2025: 0
+    2030: 0.05
+    2035: 0.15
+    2040: 0.3
+    2045: 0.6
+    2050: 1
+  time_dep_hp_cop: true #time dependent heat pump coefficient of performance
+  heat_pump_sink_T: 55. # Celsius, based on DTU / large area radiators; used in build_cop_profiles.py
+   # conservatively high to cover hot water and space heating in poorly-insulated buildings
+  reduce_space_heat_exogenously: true  # reduces space heat demand by a given factor (applied before losses in DH)
+  # this can represent e.g. building renovation, building demolition, or if
+  # the factor is negative: increasing floor area, increased thermal comfort, population growth
+  reduce_space_heat_exogenously_factor: # 0.29 # per unit reduction in space heat demand
+  # the default factors are determined by the LTS scenario from http://tool.european-calculator.eu/app/buildings/building-types-area/?levers=1ddd4444421213bdbbbddd44444ffffff11f411111221111211l212221
+    2020: 0.10  # this results in a space heat demand reduction of 10%
+    2025: 0.09  # first heat demand increases compared to 2020 because of larger floor area per capita
+    2030: 0.09
+    2035: 0.11
+    2040: 0.16
+    2045: 0.21
+    2050: 0.29
+  retrofitting :  # co-optimises building renovation to reduce space heat demand
+    retro_endogen: false  # co-optimise space heat savings
+    cost_factor: 1.0   # weight costs for building renovation
+    interest_rate: 0.04  # for investment in building components
+    annualise_cost: true  # annualise the investment costs
+    tax_weighting: false   # weight costs depending on taxes in countries
+    construction_index: true   # weight costs depending on labour/material costs per country
+  tes: true
+  tes_tau: # 180 day time constant for centralised, 3 day for decentralised
+    decentral: 3
+    central: 180
+  boilers: true
+  oil_boilers: false
+  chp: true
+  micro_chp: false
+  solar_thermal: true
+  solar_cf_correction: 0.788457  # =  >>> 1/1.2683
+  marginal_cost_storage: 0. #1e-4
+  methanation: true
+  helmeth: true
+  dac: true
+  co2_vent: true
+  SMR: true
+  co2_sequestration_potential: 200  #MtCO2/a sequestration potential for Europe
+  co2_sequestration_cost: 10   #EUR/tCO2 for sequestration of CO2
+  co2_network: false
+  cc_fraction: 0.9  # default fraction of CO2 captured with post-combustion capture
+  hydrogen_underground_storage: true
+  hydrogen_underground_storage_locations:
+    # - onshore  # more than 50 km from sea
+    - nearshore  # within 50 km of sea
+    # - offshore
+  use_fischer_tropsch_waste_heat: true
+  use_fuel_cell_waste_heat: true
+  electricity_distribution_grid: true
+  electricity_distribution_grid_cost_factor: 1.0  #multiplies cost in data/costs.csv
+  electricity_grid_connection: true  # only applies to onshore wind and utility PV
+  H2_network: true
+  gas_network: false
+  H2_retrofit: false  # if set to True existing gas pipes can be retrofitted to H2 pipes
+  # according to hydrogen backbone strategy (April, 2020) p.15
+  # https://gasforclimate2050.eu/wp-content/uploads/2020/07/2020_European-Hydrogen-Backbone_Report.pdf
+  # 60% of original natural gas capacity could be used in cost-optimal case as H2 capacity
+  H2_retrofit_capacity_per_CH4: 0.6  # ratio for H2 capacity per original CH4 capacity of retrofitted pipelines
+  gas_network_connectivity_upgrade: 1 # https://networkx.org/documentation/stable/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation.html#networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation
+  gas_distribution_grid: true
+  gas_distribution_grid_cost_factor: 1.0  #multiplies cost in data/costs.csv
+  biomass_transport: false  # biomass transport between nodes
+  conventional_generation: # generator : carrier
+    OCGT: gas
+
+
+industry:
+  St_primary_fraction: # 0.3 # fraction of steel produced via primary route versus secondary route (scrap+EAF); today fraction is 0.6
+    2020: 0.6
+    2025: 0.55
+    2030: 0.5
+    2035: 0.45
+    2040: 0.4
+    2045: 0.35
+    2050: 0.3
+  DRI_fraction: # 1 # fraction of the primary route converted to DRI + EAF
+    2020: 0
+    2025: 0
+    2030: 0.05
+    2035: 0.2
+    2040: 0.4
+    2045: 0.7
+    2050: 1
+  H2_DRI: 1.7   #H2 consumption in Direct Reduced Iron (DRI),  MWh_H2,LHV/ton_Steel from 51kgH2/tSt in Vogl et al (2018) doi:10.1016/j.jclepro.2018.08.279
+  elec_DRI: 0.322   #electricity consumption in Direct Reduced Iron (DRI) shaft, MWh/tSt HYBRIT brochure https://ssabwebsitecdn.azureedge.net/-/media/hybrit/files/hybrit_brochure.pdf
+  Al_primary_fraction: # 0.2 # fraction of aluminium produced via the primary route versus scrap; today fraction is 0.4
+    2020: 0.4
+    2025: 0.375
+    2030: 0.35
+    2035: 0.325
+    2040: 0.3
+    2045: 0.25
+    2050: 0.2
+  MWh_CH4_per_tNH3_SMR: 10.8 # 2012's demand from https://ec.europa.eu/docsroom/documents/4165/attachments/1/translations/en/renditions/pdf
+  MWh_elec_per_tNH3_SMR: 0.7 # same source, assuming 94-6% split methane-elec of total energy demand 11.5 MWh/tNH3
+  MWh_H2_per_tNH3_electrolysis: 6.5 # from https://doi.org/10.1016/j.joule.2018.04.017, around 0.197 tH2/tHN3 (>3/17 since some H2 lost and used for energy)
+  MWh_elec_per_tNH3_electrolysis: 1.17 # from https://doi.org/10.1016/j.joule.2018.04.017 Table 13 (air separation and HB)
+  NH3_process_emissions: 24.5 # in MtCO2/a from SMR for H2 production for NH3 from UNFCCC for 2015 for EU28
+  petrochemical_process_emissions: 25.5 # in MtCO2/a for petrochemical and other from UNFCCC for 2015 for EU28
+  HVC_primary_fraction: 1. # fraction of today's HVC produced via primary route
+  HVC_mechanical_recycling_fraction: 0. # fraction of today's HVC produced via mechanical recycling
+  HVC_chemical_recycling_fraction: 0. # fraction of today's HVC produced via chemical recycling
+  HVC_production_today: 52. # MtHVC/a from DECHEMA (2017), Figure 16, page 107; includes ethylene, propylene and BTX
+  MWh_elec_per_tHVC_mechanical_recycling: 0.547 # from SI of https://doi.org/10.1016/j.resconrec.2020.105010, Table S5, for HDPE, PP, PS, PET. LDPE would be 0.756.
+  MWh_elec_per_tHVC_chemical_recycling: 6.9 # Material Economics (2019), page 125; based on pyrolysis and electric steam cracking
+  chlorine_production_today: 9.58 # MtCl/a from DECHEMA (2017), Table 7, page 43
+  MWh_elec_per_tCl: 3.6 # DECHEMA (2017), Table 6, page 43
+  MWh_H2_per_tCl: -0.9372  # DECHEMA (2017), page 43; negative since hydrogen produced in chloralkali process
+  methanol_production_today: 1.5 # MtMeOH/a from DECHEMA (2017), page 62
+  MWh_elec_per_tMeOH: 0.167 # DECHEMA (2017), Table 14, page 65
+  MWh_CH4_per_tMeOH: 10.25 # DECHEMA (2017), Table 14, page 65
+  hotmaps_locate_missing: false
+  reference_year: 2015
+  # references:
+  # DECHEMA (2017): https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf
+  # Material Economics (2019): https://materialeconomics.com/latest-updates/industrial-transformation-2050
+
+costs:
+  lifetime: 25 #default lifetime
+  # From a Lion Hirth paper, also reflects average of Noothout et al 2016
+  discountrate: 0.07
+  # [EUR/USD] ECB: https://www.ecb.europa.eu/stats/exchange/eurofxref/html/eurofxref-graph-usd.en.html # noqa: E501
+  USD2013_to_EUR2013: 0.7532
+
+  # Marginal and capital costs can be overwritten
+  # capital_cost:
+  #   onwind: 500
+  marginal_cost:
+    solar: 0.01
+    onwind: 0.015
+    offwind: 0.015
+    hydro: 0.
+    H2: 0.
+    battery: 0.
+
+  emission_prices: # only used with the option Ep (emission prices)
+    co2: 0.
+
+  lines:
+    length_factor: 1.25 #to estimate offwind connection costs
+
+
+solving:
+  #tmpdir: "path/to/tmp"
+  options:
+    formulation: kirchhoff
+    clip_p_max_pu: 1.e-2
+    load_shedding: false
+    noisy_costs: true
+    skip_iterations: true
+    track_iterations: false
+    min_iterations: 4
+    max_iterations: 6
+    keep_shadowprices:
+      - Bus
+      - Line
+      - Link
+      - Transformer
+      - GlobalConstraint
+      - Generator
+      - Store
+      - StorageUnit
+
+  solver:
+    name: cbc
+    # threads: 4
+    # method: 2 # barrier
+    # crossover: 0
+    # BarConvTol: 1.e-6
+    # Seed: 123
+    # AggFill: 0
+    # PreDual: 0
+    # GURO_PAR_BARDENSETHRESH: 200
+    #FeasibilityTol: 1.e-6
+
+    #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
+  mem: 4000 #memory in MB; 20 GB enough for 50+B+I+H2; 100 GB for 181+B+I+H2
+
+
+plotting:
+  map:
+    boundaries: [-11, 30, 34, 71]
+    color_geomap:
+      ocean: white
+      land: whitesmoke
+  costs_max: 1000
+  costs_threshold: 1
+  energy_max: 20000
+  energy_min: -20000
+  energy_threshold: 50
+  vre_techs:
+    - onwind
+    - offwind-ac
+    - offwind-dc
+    - solar
+    - ror
+  renewable_storage_techs:
+    - PHS
+    - hydro
+  conv_techs:
+    - OCGT
+    - CCGT
+    - Nuclear
+    - Coal
+  storage_techs:
+    - hydro+PHS
+    - battery
+    - H2
+  load_carriers:
+    - AC load
+  AC_carriers:
+    - AC line
+    - AC transformer
+  link_carriers:
+    - DC line
+    - Converter AC-DC
+  heat_links:
+    - heat pump
+    - resistive heater
+    - CHP heat
+    - CHP electric
+    - gas boiler
+    - central heat pump
+    - central resistive heater
+    - central CHP heat
+    - central CHP electric
+    - central gas boiler
+  heat_generators:
+    - gas boiler
+    - central gas boiler
+    - solar thermal collector
+    - central solar thermal collector
+  tech_colors:
+    # wind
+    onwind: "#235ebc"
+    onshore wind: "#235ebc"
+    offwind: "#6895dd"
+    offshore wind: "#6895dd"
+    offwind-ac: "#6895dd"
+    offshore wind (AC): "#6895dd"
+    offwind-dc: "#74c6f2"
+    offshore wind (DC): "#74c6f2"
+    # water
+    hydro: '#298c81'
+    hydro reservoir: '#298c81'
+    ror: '#3dbfb0'
+    run of river: '#3dbfb0'
+    hydroelectricity: '#298c81'
+    PHS: '#51dbcc'
+    wave: '#a7d4cf'
+    # solar
+    solar: "#f9d002"
+    solar PV: "#f9d002"
+    solar thermal: '#ffbf2b'
+    solar rooftop: '#ffea80'
+    # gas
+    OCGT: '#e0986c'
+    OCGT marginal: '#e0986c'
+    OCGT-heat: '#e0986c'
+    gas boiler: '#db6a25'
+    gas boilers: '#db6a25'
+    gas boiler marginal: '#db6a25'
+    gas: '#e05b09'
+    fossil gas: '#e05b09'
+    natural gas: '#e05b09'
+    CCGT: '#a85522'
+    CCGT marginal: '#a85522'
+    gas for industry co2 to atmosphere: '#692e0a'
+    gas for industry co2 to stored: '#8a3400'
+    gas for industry: '#853403'
+    gas for industry CC: '#692e0a'
+    gas pipeline: '#ebbca0'
+    gas pipeline new: '#a87c62'
+    # oil
+    oil: '#c9c9c9'
+    oil boiler: '#adadad'
+    agriculture machinery oil: '#949494'
+    shipping oil: "#808080"
+    land transport oil: '#afafaf'
+    # nuclear
+    Nuclear: '#ff8c00'
+    Nuclear marginal: '#ff8c00'
+    nuclear: '#ff8c00'
+    uranium: '#ff8c00'
+    # coal
+    Coal: '#545454'
+    coal: '#545454'
+    Coal marginal: '#545454'
+    solid: '#545454'
+    Lignite: '#826837'
+    lignite: '#826837'
+    Lignite marginal: '#826837'
+    # biomass
+    biogas: '#e3d37d'
+    biomass: '#baa741'
+    solid biomass: '#baa741'
+    solid biomass transport: '#baa741'
+    solid biomass for industry: '#7a6d26'
+    solid biomass for industry CC: '#47411c'
+    solid biomass for industry co2 from atmosphere: '#736412'
+    solid biomass for industry co2 to stored: '#47411c'
+    # power transmission
+    lines: '#6c9459'
+    transmission lines: '#6c9459'
+    electricity distribution grid: '#97ad8c'
+    # electricity demand
+    Electric load: '#110d63'
+    electric demand: '#110d63'
+    electricity: '#110d63'
+    industry electricity: '#2d2a66'
+    industry new electricity: '#2d2a66'
+    agriculture electricity: '#494778'
+    # battery + EVs
+    battery: '#ace37f'
+    battery storage: '#ace37f'
+    home battery: '#80c944'
+    home battery storage: '#80c944'
+    BEV charger: '#baf238'
+    V2G: '#e5ffa8'
+    land transport EV: '#baf238'
+    Li ion: '#baf238'
+    # hot water storage
+    water tanks: '#e69487'
+    hot water storage: '#e69487'
+    hot water charging: '#e69487'
+    hot water discharging: '#e69487'
+    # heat demand
+    Heat load: '#cc1f1f'
+    heat: '#cc1f1f'
+    heat demand: '#cc1f1f'
+    rural heat: '#ff5c5c'
+    central heat: '#cc1f1f'
+    decentral heat: '#750606'
+    low-temperature heat for industry: '#8f2727'
+    process heat: '#ff0000'
+    agriculture heat: '#d9a5a5'
+    # heat supply
+    heat pumps: '#2fb537'
+    heat pump: '#2fb537'
+    air heat pump: '#36eb41'
+    ground heat pump: '#2fb537'
+    Ambient: '#98eb9d'
+    CHP: '#8a5751'
+    CHP CC: '#634643'
+    CHP heat: '#8a5751'
+    CHP electric: '#8a5751'
+    district heating: '#e8beac'
+    resistive heater: '#d8f9b8'
+    retrofitting: '#8487e8'
+    building retrofitting: '#8487e8'
+    # hydrogen
+    H2 for industry: "#f073da"
+    H2 for shipping: "#ebaee0"
+    H2: '#bf13a0'
+    hydrogen: '#bf13a0'
+    SMR: '#870c71'
+    SMR CC: '#4f1745'
+    H2 liquefaction: '#d647bd'
+    hydrogen storage: '#bf13a0'
+    H2 storage: '#bf13a0'
+    land transport fuel cell: '#6b3161'
+    H2 pipeline: '#f081dc'
+    H2 pipeline retrofitted: '#ba99b5'
+    H2 Fuel Cell: '#c251ae'
+    H2 Electrolysis: '#ff29d9'
+    # syngas
+    Sabatier: '#9850ad'
+    methanation: '#c44ce6'
+    methane: '#c44ce6'
+    helmeth: '#e899ff'
+    # synfuels
+    Fischer-Tropsch: '#25c49a'
+    liquid: '#25c49a'
+    kerosene for aviation: '#a1ffe6'
+    naphtha for industry: '#57ebc4'
+    # co2
+    CC: '#f29dae'
+    CCS: '#f29dae'
+    CO2 sequestration: '#f29dae'
+    DAC: '#ff5270'
+    co2 stored: '#f2385a'
+    co2: '#f29dae'
+    co2 vent: '#ffd4dc'
+    CO2 pipeline: '#f5627f'
+    # emissions
+    process emissions CC: '#000000'
+    process emissions: '#222222'
+    process emissions to stored: '#444444'
+    process emissions to atmosphere: '#888888'
+    oil emissions: '#aaaaaa'
+    shipping oil emissions: "#555555"
+    land transport oil emissions: '#777777'
+    agriculture machinery oil emissions: '#333333'
+    # other
+    shipping: '#03a2ff'
+    power-to-heat: '#2fb537'
+    power-to-gas: '#c44ce6'
+    power-to-H2: '#ff29d9'
+    power-to-liquid: '#25c49a'
+    gas-to-power/heat: '#ee8340'
+    waste: '#e3d37d'
+    other: '#000000'

test/config.overnight.yaml

@@ -0,0 +1,605 @@
+version: 0.6.0
+
+logging_level: INFO
+
+retrieve_sector_databundle: true
+
+results_dir: results/
+summary_dir: results
+costs_dir: ../technology-data/outputs/
+run: test-overnight  # use this to keep track of runs with different settings
+foresight: overnight # options are overnight, myopic, perfect (perfect is not yet implemented)
+# if you use myopic or perfect foresight, set the investment years in "planning_horizons" below
+
+scenario:
+  simpl: # only relevant for PyPSA-Eur
+    - ''
+  lv: # allowed transmission line volume expansion, can be any float >= 1.0 (today) or "opt"
+    - 1.5
+  clusters: # number of nodes in Europe, any integer between 37 (1 node per country-zone) and several hundred
+    - 5
+  opts: # only relevant for PyPSA-Eur
+    - ''
+  sector_opts: # this is where the main scenario settings are
+    - CO2L0-191H-T-H-B-I-A-solar+p3-dist1
+  # to really understand the options here, look in scripts/prepare_sector_network.py
+  # Co2Lx specifies the CO2 target in x% of the 1990 values; default will give default (5%);
+  # Co2L0p25 will give 25% CO2 emissions; Co2Lm0p05 will give 5% negative emissions
+  # xH is the temporal resolution; 3H is 3-hourly, i.e. one snapshot every 3 hours
+  # single letters are sectors: T for land transport, H for building heating,
+  # B for biomass supply, I for industry, shipping and aviation,
+  # A for agriculture, forestry and fishing
+  # solar+c0.5 reduces the capital cost of solar to 50\% of reference value
+  # solar+p3 multiplies the available installable potential by factor 3
+  # co2 stored+e2 multiplies the potential of CO2 sequestration by a factor 2
+  # dist{n} includes distribution grids with investment cost of n times cost in data/costs.csv
+  # for myopic/perfect foresight cb states the carbon budget in GtCO2 (cumulative
+  # emissions throughout the transition path in the timeframe determined by the
+  # planning_horizons), be:beta decay; ex:exponential decay
+  # cb40ex0 distributes a carbon budget of 40 GtCO2 following an exponential
+  # decay with initial growth rate 0
+  planning_horizons: # investment years for myopic and perfect; or costs year for overnight
+    - 2030
+  # for example, set to [2020, 2030, 2040, 2050] for myopic foresight
+
+# CO2 budget as a fraction of 1990 emissions
+# this is over-ridden if CO2Lx is set in sector_opts
+# this is also over-ridden if cb is set in sector_opts
+co2_budget:
+  2020: 0.7011648746
+  2025: 0.5241935484
+  2030: 0.2970430108
+  2035: 0.1500896057
+  2040: 0.0712365591
+  2045: 0.0322580645
+  2050: 0
+
+# snapshots are originally set in PyPSA-Eur/config.yaml but used again by PyPSA-Eur-Sec
+snapshots:
+  # arguments to pd.date_range
+  start: "2013-03-01"
+  end: "2013-04-01"
+  closed: left # end is not inclusive
+
+atlite:
+  cutout: ../pypsa-eur/cutouts/be-03-2013-era5.nc
+
+# this information is NOT used but needed as an argument for
+# pypsa-eur/scripts/add_electricity.py/load_costs in make_summary.py
+electricity:
+  max_hours:
+    battery: 6
+    H2: 168
+
+# regulate what components with which carriers are kept from PyPSA-Eur;
+# some technologies are removed because they are implemented differently
+# (e.g. battery or H2 storage) or have different year-dependent costs
+# in PyPSA-Eur-Sec
+pypsa_eur:
+  Bus:
+    - AC
+  Link:
+    - DC
+  Generator:
+    - onwind
+    - offwind-ac
+    - offwind-dc
+    - solar
+    - ror
+  StorageUnit:
+    - PHS
+    - hydro
+  Store: []
+
+
+energy:
+  energy_totals_year: 2011
+  base_emissions_year: 1990
+  eurostat_report_year: 2016
+  emissions: CO2 # "CO2" or "All greenhouse gases - (CO2 equivalent)"
+
+biomass:
+  year: 2030
+  scenario: ENS_Med
+  classes:
+    solid biomass:
+      - Agricultural waste
+      - Fuelwood residues
+      - Secondary Forestry residues - woodchips
+      - Sawdust
+      - Residues from landscape care
+      - Municipal waste
+    not included:
+      - Sugar from sugar beet
+      - Rape seed
+      - "Sunflower, soya seed "
+      - Bioethanol barley, wheat, grain maize, oats, other cereals and rye
+      - Miscanthus, switchgrass, RCG
+      - Willow
+      - Poplar
+      - FuelwoodRW
+      - C&P_RW
+    biogas:
+      - Manure solid, liquid
+      - Sludge
+
+
+solar_thermal:
+  clearsky_model: simple  # should be "simple" or "enhanced"?
+  orientation:
+    slope: 45.
+    azimuth: 180.
+
+# only relevant for foresight = myopic or perfect
+existing_capacities:
+  grouping_years: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2019]
+  threshold_capacity: 10
+  conventional_carriers:
+    - lignite
+    - coal
+    - oil
+    - uranium
+
+
+sector:
+  district_heating:
+    potential: 0.6  # maximum fraction of urban demand which can be supplied by district heating
+     # increase of today's district heating demand to potential maximum district heating share
+     # progress = 0 means today's district heating share, progress = 1 means maximum fraction of urban demand is supplied by district heating
+    progress: 1
+      # 2020: 0.0
+      # 2030: 0.3
+      # 2040: 0.6
+      # 2050: 1.0
+    district_heating_loss: 0.15
+  bev_dsm_restriction_value: 0.75  #Set to 0 for no restriction on BEV DSM
+  bev_dsm_restriction_time: 7  #Time at which SOC of BEV has to be dsm_restriction_value
+  transport_heating_deadband_upper: 20.
+  transport_heating_deadband_lower: 15.
+  ICE_lower_degree_factor: 0.375  #in per cent increase in fuel consumption per degree above deadband
+  ICE_upper_degree_factor: 1.6
+  EV_lower_degree_factor: 0.98
+  EV_upper_degree_factor: 0.63
+  bev_dsm: true #turns on EV battery
+  bev_availability: 0.5  #How many cars do smart charging
+  bev_energy: 0.05  #average battery size in MWh
+  bev_charge_efficiency: 0.9  #BEV (dis-)charging efficiency
+  bev_plug_to_wheel_efficiency: 0.2 #kWh/km from EPA https://www.fueleconomy.gov/feg/ for Tesla Model S
+  bev_charge_rate: 0.011 #3-phase charger with 11 kW
+  bev_avail_max: 0.95
+  bev_avail_mean: 0.8
+  v2g: true #allows feed-in to grid from EV battery
+  #what is not EV or FCEV is oil-fuelled ICE
+  land_transport_fuel_cell_share: 0.15 # 1 means all FCEVs
+    # 2020: 0
+    # 2030: 0.05
+    # 2040: 0.1
+    # 2050: 0.15
+  land_transport_electric_share: 0.85 # 1 means all EVs
+    # 2020: 0
+    # 2030: 0.25
+    # 2040: 0.6
+    # 2050: 0.85
+  transport_fuel_cell_efficiency: 0.5
+  transport_internal_combustion_efficiency: 0.3
+  agriculture_machinery_electric_share: 0
+  agriculture_machinery_fuel_efficiency: 0.7 # fuel oil per use
+  agriculture_machinery_electric_efficiency: 0.3 # electricity per use
+  shipping_average_efficiency: 0.4 #For conversion of fuel oil to propulsion in 2011
+  shipping_hydrogen_liquefaction: false # whether to consider liquefaction costs for shipping H2 demands
+  shipping_hydrogen_share: 1 # 1 means all hydrogen FC
+    # 2020: 0
+    # 2025: 0
+    # 2030: 0.05
+    # 2035: 0.15
+    # 2040: 0.3
+    # 2045: 0.6
+    # 2050: 1
+  time_dep_hp_cop: true #time dependent heat pump coefficient of performance
+  heat_pump_sink_T: 55. # Celsius, based on DTU / large area radiators; used in build_cop_profiles.py
+   # conservatively high to cover hot water and space heating in poorly-insulated buildings
+  reduce_space_heat_exogenously: true  # reduces space heat demand by a given factor (applied before losses in DH)
+  # this can represent e.g. building renovation, building demolition, or if
+  # the factor is negative: increasing floor area, increased thermal comfort, population growth
+  reduce_space_heat_exogenously_factor: 0.29 # per unit reduction in space heat demand
+  # the default factors are determined by the LTS scenario from http://tool.european-calculator.eu/app/buildings/building-types-area/?levers=1ddd4444421213bdbbbddd44444ffffff11f411111221111211l212221
+    # 2020: 0.10  # this results in a space heat demand reduction of 10%
+    # 2025: 0.09  # first heat demand increases compared to 2020 because of larger floor area per capita
+    # 2030: 0.09
+    # 2035: 0.11
+    # 2040: 0.16
+    # 2045: 0.21
+    # 2050: 0.29
+  retrofitting :  # co-optimises building renovation to reduce space heat demand
+    retro_endogen: false  # co-optimise space heat savings
+    cost_factor: 1.0   # weight costs for building renovation
+    interest_rate: 0.04  # for investment in building components
+    annualise_cost: true  # annualise the investment costs
+    tax_weighting: false   # weight costs depending on taxes in countries
+    construction_index: true   # weight costs depending on labour/material costs per country
+  tes: true
+  tes_tau: # 180 day time constant for centralised, 3 day for decentralised
+    decentral: 3
+    central: 180
+  boilers: true
+  oil_boilers: false
+  chp: true
+  micro_chp: false
+  solar_thermal: true
+  solar_cf_correction: 0.788457  # =  >>> 1/1.2683
+  marginal_cost_storage: 0. #1e-4
+  methanation: true
+  helmeth: true
+  dac: true
+  co2_vent: true
+  SMR: true
+  co2_sequestration_potential: 200  #MtCO2/a sequestration potential for Europe
+  co2_sequestration_cost: 10   #EUR/tCO2 for sequestration of CO2
+  co2_network: false
+  cc_fraction: 0.9  # default fraction of CO2 captured with post-combustion capture
+  hydrogen_underground_storage: true
+  hydrogen_underground_storage_locations:
+    # - onshore  # more than 50 km from sea
+    - nearshore  # within 50 km of sea
+    # - offshore
+  use_fischer_tropsch_waste_heat: true
+  use_fuel_cell_waste_heat: true
+  electricity_distribution_grid: true
+  electricity_distribution_grid_cost_factor: 1.0  #multiplies cost in data/costs.csv
+  electricity_grid_connection: true  # only applies to onshore wind and utility PV
+  H2_network: true
+  gas_network: true
+  H2_retrofit: true  # if set to True existing gas pipes can be retrofitted to H2 pipes
+  # according to hydrogen backbone strategy (April, 2020) p.15
+  # https://gasforclimate2050.eu/wp-content/uploads/2020/07/2020_European-Hydrogen-Backbone_Report.pdf
+  # 60% of original natural gas capacity could be used in cost-optimal case as H2 capacity
+  H2_retrofit_capacity_per_CH4: 0.6  # ratio for H2 capacity per original CH4 capacity of retrofitted pipelines
+  gas_network_connectivity_upgrade: 1 # https://networkx.org/documentation/stable/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation.html#networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation
+  gas_distribution_grid: true
+  gas_distribution_grid_cost_factor: 1.0  #multiplies cost in data/costs.csv
+  biomass_transport: false  # biomass transport between nodes
+  conventional_generation: # generator : carrier
+    OCGT: gas
+
+
+industry:
+  St_primary_fraction: 0.3 # fraction of steel produced via primary route versus secondary route (scrap+EAF); today fraction is 0.6
+    # 2020: 0.6
+    # 2025: 0.55
+    # 2030: 0.5
+    # 2035: 0.45
+    # 2040: 0.4
+    # 2045: 0.35
+    # 2050: 0.3
+  DRI_fraction: 1 # fraction of the primary route converted to DRI + EAF
+    # 2020: 0
+    # 2025: 0
+    # 2030: 0.05
+    # 2035: 0.2
+    # 2040: 0.4
+    # 2045: 0.7
+    # 2050: 1
+  H2_DRI: 1.7   #H2 consumption in Direct Reduced Iron (DRI),  MWh_H2,LHV/ton_Steel from 51kgH2/tSt in Vogl et al (2018) doi:10.1016/j.jclepro.2018.08.279
+  elec_DRI: 0.322   #electricity consumption in Direct Reduced Iron (DRI) shaft, MWh/tSt HYBRIT brochure https://ssabwebsitecdn.azureedge.net/-/media/hybrit/files/hybrit_brochure.pdf
+  Al_primary_fraction: 0.2 # fraction of aluminium produced via the primary route versus scrap; today fraction is 0.4
+    # 2020: 0.4
+    # 2025: 0.375
+    # 2030: 0.35
+    # 2035: 0.325
+    # 2040: 0.3
+    # 2045: 0.25
+    # 2050: 0.2
+  MWh_CH4_per_tNH3_SMR: 10.8 # 2012's demand from https://ec.europa.eu/docsroom/documents/4165/attachments/1/translations/en/renditions/pdf
+  MWh_elec_per_tNH3_SMR: 0.7 # same source, assuming 94-6% split methane-elec of total energy demand 11.5 MWh/tNH3
+  MWh_H2_per_tNH3_electrolysis: 6.5 # from https://doi.org/10.1016/j.joule.2018.04.017, around 0.197 tH2/tHN3 (>3/17 since some H2 lost and used for energy)
+  MWh_elec_per_tNH3_electrolysis: 1.17 # from https://doi.org/10.1016/j.joule.2018.04.017 Table 13 (air separation and HB)
+  NH3_process_emissions: 24.5 # in MtCO2/a from SMR for H2 production for NH3 from UNFCCC for 2015 for EU28
+  petrochemical_process_emissions: 25.5 # in MtCO2/a for petrochemical and other from UNFCCC for 2015 for EU28
+  HVC_primary_fraction: 1. # fraction of today's HVC produced via primary route
+  HVC_mechanical_recycling_fraction: 0. # fraction of today's HVC produced via mechanical recycling
+  HVC_chemical_recycling_fraction: 0. # fraction of today's HVC produced via chemical recycling
+  HVC_production_today: 52. # MtHVC/a from DECHEMA (2017), Figure 16, page 107; includes ethylene, propylene and BTX
+  MWh_elec_per_tHVC_mechanical_recycling: 0.547 # from SI of https://doi.org/10.1016/j.resconrec.2020.105010, Table S5, for HDPE, PP, PS, PET. LDPE would be 0.756.
+  MWh_elec_per_tHVC_chemical_recycling: 6.9 # Material Economics (2019), page 125; based on pyrolysis and electric steam cracking
+  chlorine_production_today: 9.58 # MtCl/a from DECHEMA (2017), Table 7, page 43
+  MWh_elec_per_tCl: 3.6 # DECHEMA (2017), Table 6, page 43
+  MWh_H2_per_tCl: -0.9372  # DECHEMA (2017), page 43; negative since hydrogen produced in chloralkali process
+  methanol_production_today: 1.5 # MtMeOH/a from DECHEMA (2017), page 62
+  MWh_elec_per_tMeOH: 0.167 # DECHEMA (2017), Table 14, page 65
+  MWh_CH4_per_tMeOH: 10.25 # DECHEMA (2017), Table 14, page 65
+  hotmaps_locate_missing: false
+  reference_year: 2015
+  # references:
+  # DECHEMA (2017): https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf
+  # Material Economics (2019): https://materialeconomics.com/latest-updates/industrial-transformation-2050
+
+costs:
+  lifetime: 25 #default lifetime
+  # From a Lion Hirth paper, also reflects average of Noothout et al 2016
+  discountrate: 0.07
+  # [EUR/USD] ECB: https://www.ecb.europa.eu/stats/exchange/eurofxref/html/eurofxref-graph-usd.en.html # noqa: E501
+  USD2013_to_EUR2013: 0.7532
+
+  # Marginal and capital costs can be overwritten
+  # capital_cost:
+  #   onwind: 500
+  marginal_cost:
+    solar: 0.01
+    onwind: 0.015
+    offwind: 0.015
+    hydro: 0.
+    H2: 0.
+    battery: 0.
+
+  emission_prices: # only used with the option Ep (emission prices)
+    co2: 0.
+
+  lines:
+    length_factor: 1.25 #to estimate offwind connection costs
+
+
+solving:
+  #tmpdir: "path/to/tmp"
+  options:
+    formulation: kirchhoff
+    clip_p_max_pu: 1.e-2
+    load_shedding: false
+    noisy_costs: true
+    skip_iterations: true
+    track_iterations: false
+    min_iterations: 4
+    max_iterations: 6
+    keep_shadowprices:
+      - Bus
+      - Line
+      - Link
+      - Transformer
+      - GlobalConstraint
+      - Generator
+      - Store
+      - StorageUnit
+
+  solver:
+    name: cbc
+    # threads: 4
+    # method: 2 # barrier
+    # crossover: 0
+    # BarConvTol: 1.e-6
+    # Seed: 123
+    # AggFill: 0
+    # PreDual: 0
+    # GURO_PAR_BARDENSETHRESH: 200
+    #FeasibilityTol: 1.e-6
+
+    #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
+  mem: 4000 #memory in MB; 20 GB enough for 50+B+I+H2; 100 GB for 181+B+I+H2
+
+
+plotting:
+  map:
+    boundaries: [-11, 30, 34, 71]
+    color_geomap:
+      ocean: white
+      land: whitesmoke
+  costs_max: 1000
+  costs_threshold: 1
+  energy_max: 20000
+  energy_min: -20000
+  energy_threshold: 50
+  vre_techs:
+    - onwind
+    - offwind-ac
+    - offwind-dc
+    - solar
+    - ror
+  renewable_storage_techs:
+    - PHS
+    - hydro
+  conv_techs:
+    - OCGT
+    - CCGT
+    - Nuclear
+    - Coal
+  storage_techs:
+    - hydro+PHS
+    - battery
+    - H2
+  load_carriers:
+    - AC load
+  AC_carriers:
+    - AC line
+    - AC transformer
+  link_carriers:
+    - DC line
+    - Converter AC-DC
+  heat_links:
+    - heat pump
+    - resistive heater
+    - CHP heat
+    - CHP electric
+    - gas boiler
+    - central heat pump
+    - central resistive heater
+    - central CHP heat
+    - central CHP electric
+    - central gas boiler
+  heat_generators:
+    - gas boiler
+    - central gas boiler
+    - solar thermal collector
+    - central solar thermal collector
+  tech_colors:
+    # wind
+    onwind: "#235ebc"
+    onshore wind: "#235ebc"
+    offwind: "#6895dd"
+    offshore wind: "#6895dd"
+    offwind-ac: "#6895dd"
+    offshore wind (AC): "#6895dd"
+    offwind-dc: "#74c6f2"
+    offshore wind (DC): "#74c6f2"
+    # water
+    hydro: '#298c81'
+    hydro reservoir: '#298c81'
+    ror: '#3dbfb0'
+    run of river: '#3dbfb0'
+    hydroelectricity: '#298c81'
+    PHS: '#51dbcc'
+    wave: '#a7d4cf'
+    # solar
+    solar: "#f9d002"
+    solar PV: "#f9d002"
+    solar thermal: '#ffbf2b'
+    solar rooftop: '#ffea80'
+    # gas
+    OCGT: '#e0986c'
+    OCGT marginal: '#e0986c'
+    OCGT-heat: '#e0986c'
+    gas boiler: '#db6a25'
+    gas boilers: '#db6a25'
+    gas boiler marginal: '#db6a25'
+    gas: '#e05b09'
+    fossil gas: '#e05b09'
+    natural gas: '#e05b09'
+    CCGT: '#a85522'
+    CCGT marginal: '#a85522'
+    gas for industry co2 to atmosphere: '#692e0a'
+    gas for industry co2 to stored: '#8a3400'
+    gas for industry: '#853403'
+    gas for industry CC: '#692e0a'
+    gas pipeline: '#ebbca0'
+    gas pipeline new: '#a87c62'
+    # oil
+    oil: '#c9c9c9'
+    oil boiler: '#adadad'
+    agriculture machinery oil: '#949494'
+    shipping oil: "#808080"
+    land transport oil: '#afafaf'
+    # nuclear
+    Nuclear: '#ff8c00'
+    Nuclear marginal: '#ff8c00'
+    nuclear: '#ff8c00'
+    uranium: '#ff8c00'
+    # coal
+    Coal: '#545454'
+    coal: '#545454'
+    Coal marginal: '#545454'
+    solid: '#545454'
+    Lignite: '#826837'
+    lignite: '#826837'
+    Lignite marginal: '#826837'
+    # biomass
+    biogas: '#e3d37d'
+    biomass: '#baa741'
+    solid biomass: '#baa741'
+    solid biomass transport: '#baa741'
+    solid biomass for industry: '#7a6d26'
+    solid biomass for industry CC: '#47411c'
+    solid biomass for industry co2 from atmosphere: '#736412'
+    solid biomass for industry co2 to stored: '#47411c'
+    # power transmission
+    lines: '#6c9459'
+    transmission lines: '#6c9459'
+    electricity distribution grid: '#97ad8c'
+    # electricity demand
+    Electric load: '#110d63'
+    electric demand: '#110d63'
+    electricity: '#110d63'
+    industry electricity: '#2d2a66'
+    industry new electricity: '#2d2a66'
+    agriculture electricity: '#494778'
+    # battery + EVs
+    battery: '#ace37f'
+    battery storage: '#ace37f'
+    home battery: '#80c944'
+    home battery storage: '#80c944'
+    BEV charger: '#baf238'
+    V2G: '#e5ffa8'
+    land transport EV: '#baf238'
+    Li ion: '#baf238'
+    # hot water storage
+    water tanks: '#e69487'
+    hot water storage: '#e69487'
+    hot water charging: '#e69487'
+    hot water discharging: '#e69487'
+    # heat demand
+    Heat load: '#cc1f1f'
+    heat: '#cc1f1f'
+    heat demand: '#cc1f1f'
+    rural heat: '#ff5c5c'
+    central heat: '#cc1f1f'
+    decentral heat: '#750606'
+    low-temperature heat for industry: '#8f2727'
+    process heat: '#ff0000'
+    agriculture heat: '#d9a5a5'
+    # heat supply
+    heat pumps: '#2fb537'
+    heat pump: '#2fb537'
+    air heat pump: '#36eb41'
+    ground heat pump: '#2fb537'
+    Ambient: '#98eb9d'
+    CHP: '#8a5751'
+    CHP CC: '#634643'
+    CHP heat: '#8a5751'
+    CHP electric: '#8a5751'
+    district heating: '#e8beac'
+    resistive heater: '#d8f9b8'
+    retrofitting: '#8487e8'
+    building retrofitting: '#8487e8'
+    # hydrogen
+    H2 for industry: "#f073da"
+    H2 for shipping: "#ebaee0"
+    H2: '#bf13a0'
+    hydrogen: '#bf13a0'
+    SMR: '#870c71'
+    SMR CC: '#4f1745'
+    H2 liquefaction: '#d647bd'
+    hydrogen storage: '#bf13a0'
+    H2 storage: '#bf13a0'
+    land transport fuel cell: '#6b3161'
+    H2 pipeline: '#f081dc'
+    H2 pipeline retrofitted: '#ba99b5'
+    H2 Fuel Cell: '#c251ae'
+    H2 Electrolysis: '#ff29d9'
+    # syngas
+    Sabatier: '#9850ad'
+    methanation: '#c44ce6'
+    methane: '#c44ce6'
+    helmeth: '#e899ff'
+    # synfuels
+    Fischer-Tropsch: '#25c49a'
+    liquid: '#25c49a'
+    kerosene for aviation: '#a1ffe6'
+    naphtha for industry: '#57ebc4'
+    # co2
+    CC: '#f29dae'
+    CCS: '#f29dae'
+    CO2 sequestration: '#f29dae'
+    DAC: '#ff5270'
+    co2 stored: '#f2385a'
+    co2: '#f29dae'
+    co2 vent: '#ffd4dc'
+    CO2 pipeline: '#f5627f'
+    # emissions
+    process emissions CC: '#000000'
+    process emissions: '#222222'
+    process emissions to stored: '#444444'
+    process emissions to atmosphere: '#888888'
+    oil emissions: '#aaaaaa'
+    shipping oil emissions: "#555555"
+    land transport oil emissions: '#777777'
+    agriculture machinery oil emissions: '#333333'
+    # other
+    shipping: '#03a2ff'
+    power-to-heat: '#2fb537'
+    power-to-gas: '#c44ce6'
+    power-to-H2: '#ff29d9'
+    power-to-liquid: '#25c49a'
+    gas-to-power/heat: '#ee8340'
+    waste: '#e3d37d'
+    other: '#000000'