1096 lines
38 KiB
Plaintext
1096 lines
38 KiB
Plaintext
# SPDX-FileCopyrightText: : 2023-2024 The PyPSA-Eur Authors
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#
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# SPDX-License-Identifier: MIT
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rule build_population_layouts:
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input:
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nuts3_shapes=resources("nuts3_shapes.geojson"),
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urban_percent="data/urban_percent.csv",
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cutout=lambda w: "cutouts/"
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+ CDIR
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+ config_provider("atlite", "default_cutout")(w)
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+ ".nc",
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output:
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pop_layout_total=resources("pop_layout_total.nc"),
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pop_layout_urban=resources("pop_layout_urban.nc"),
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pop_layout_rural=resources("pop_layout_rural.nc"),
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log:
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logs("build_population_layouts.log"),
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resources:
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mem_mb=20000,
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benchmark:
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benchmarks("build_population_layouts")
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threads: 8
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/build_population_layouts.py"
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rule build_clustered_population_layouts:
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input:
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pop_layout_total=resources("pop_layout_total.nc"),
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pop_layout_urban=resources("pop_layout_urban.nc"),
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pop_layout_rural=resources("pop_layout_rural.nc"),
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regions_onshore=resources("regions_onshore_elec_s{simpl}_{clusters}.geojson"),
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cutout=lambda w: "cutouts/"
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+ CDIR
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+ config_provider("atlite", "default_cutout")(w)
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+ ".nc",
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output:
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clustered_pop_layout=resources("pop_layout_elec_s{simpl}_{clusters}.csv"),
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log:
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logs("build_clustered_population_layouts_{simpl}_{clusters}.log"),
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resources:
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mem_mb=10000,
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benchmark:
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benchmarks("build_clustered_population_layouts/s{simpl}_{clusters}")
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/build_clustered_population_layouts.py"
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rule build_simplified_population_layouts:
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input:
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pop_layout_total=resources("pop_layout_total.nc"),
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pop_layout_urban=resources("pop_layout_urban.nc"),
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pop_layout_rural=resources("pop_layout_rural.nc"),
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regions_onshore=resources("regions_onshore_elec_s{simpl}.geojson"),
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cutout=lambda w: "cutouts/"
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+ CDIR
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+ config_provider("atlite", "default_cutout")(w)
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+ ".nc",
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output:
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clustered_pop_layout=resources("pop_layout_elec_s{simpl}.csv"),
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resources:
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mem_mb=10000,
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log:
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logs("build_simplified_population_layouts_{simpl}"),
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benchmark:
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benchmarks("build_simplified_population_layouts/s{simpl}")
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/build_clustered_population_layouts.py"
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rule build_gas_network:
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input:
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gas_network="data/gas_network/scigrid-gas/data/IGGIELGN_PipeSegments.geojson",
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output:
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cleaned_gas_network=resources("gas_network.csv"),
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resources:
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mem_mb=4000,
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log:
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logs("build_gas_network.log"),
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/build_gas_network.py"
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rule build_gas_input_locations:
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input:
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gem=storage(
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"https://globalenergymonitor.org/wp-content/uploads/2023/07/Europe-Gas-Tracker-2023-03-v3.xlsx",
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keep_local=True,
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),
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entry="data/gas_network/scigrid-gas/data/IGGIELGN_BorderPoints.geojson",
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storage="data/gas_network/scigrid-gas/data/IGGIELGN_Storages.geojson",
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regions_onshore=resources("regions_onshore_elec_s{simpl}_{clusters}.geojson"),
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regions_offshore=resources("regions_offshore_elec_s{simpl}_{clusters}.geojson"),
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output:
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gas_input_nodes=resources("gas_input_locations_s{simpl}_{clusters}.geojson"),
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gas_input_nodes_simplified=resources(
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"gas_input_locations_s{simpl}_{clusters}_simplified.csv"
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),
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resources:
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mem_mb=2000,
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log:
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logs("build_gas_input_locations_s{simpl}_{clusters}.log"),
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/build_gas_input_locations.py"
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rule cluster_gas_network:
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input:
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cleaned_gas_network=resources("gas_network.csv"),
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regions_onshore=resources("regions_onshore_elec_s{simpl}_{clusters}.geojson"),
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regions_offshore=resources("regions_offshore_elec_s{simpl}_{clusters}.geojson"),
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output:
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clustered_gas_network=resources("gas_network_elec_s{simpl}_{clusters}.csv"),
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resources:
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mem_mb=4000,
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log:
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logs("cluster_gas_network_s{simpl}_{clusters}.log"),
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/cluster_gas_network.py"
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def heat_demand_cutout(wildcards):
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c = config_provider("sector", "heat_demand_cutout")(wildcards)
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if c == "default":
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return (
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"cutouts/"
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+ CDIR
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+ config_provider("atlite", "default_cutout")(wildcards)
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+ ".nc"
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)
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else:
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return "cutouts/" + CDIR + c + ".nc"
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rule build_daily_heat_demand:
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params:
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snapshots=config_provider("snapshots"),
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drop_leap_day=config_provider("enable", "drop_leap_day"),
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input:
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pop_layout=resources("pop_layout_total.nc"),
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regions_onshore=resources("regions_onshore_elec_s{simpl}_{clusters}.geojson"),
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cutout=heat_demand_cutout,
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output:
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heat_demand=resources("daily_heat_demand_total_elec_s{simpl}_{clusters}.nc"),
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resources:
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mem_mb=20000,
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threads: 8
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log:
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logs("build_daily_heat_demand_total_{simpl}_{clusters}.loc"),
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benchmark:
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benchmarks("build_daily_heat_demand/total_s{simpl}_{clusters}")
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/build_daily_heat_demand.py"
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rule build_hourly_heat_demand:
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params:
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snapshots=config_provider("snapshots"),
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drop_leap_day=config_provider("enable", "drop_leap_day"),
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input:
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heat_profile="data/heat_load_profile_BDEW.csv",
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heat_demand=resources("daily_heat_demand_total_elec_s{simpl}_{clusters}.nc"),
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output:
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heat_demand=resources("hourly_heat_demand_total_elec_s{simpl}_{clusters}.nc"),
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resources:
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mem_mb=2000,
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threads: 8
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log:
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logs("build_hourly_heat_demand_total_{simpl}_{clusters}.loc"),
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benchmark:
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benchmarks("build_hourly_heat_demand/total_s{simpl}_{clusters}")
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/build_hourly_heat_demand.py"
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rule build_temperature_profiles:
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params:
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snapshots=config_provider("snapshots"),
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drop_leap_day=config_provider("enable", "drop_leap_day"),
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input:
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pop_layout=resources("pop_layout_total.nc"),
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regions_onshore=resources("regions_onshore_elec_s{simpl}_{clusters}.geojson"),
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cutout=heat_demand_cutout,
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output:
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temp_soil=resources("temp_soil_total_elec_s{simpl}_{clusters}.nc"),
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temp_air=resources("temp_air_total_elec_s{simpl}_{clusters}.nc"),
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resources:
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mem_mb=20000,
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threads: 8
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log:
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logs("build_temperature_profiles_total_{simpl}_{clusters}.log"),
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benchmark:
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benchmarks("build_temperature_profiles/total_s{simpl}_{clusters}")
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/build_temperature_profiles.py"
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rule build_cop_profiles:
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params:
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heat_pump_sink_T_decentral_heating=config_provider(
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"sector", "heat_pump_sink_T_individual_heating"
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),
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forward_temperature_central_heating=config_provider(
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"sector", "district_heating", "forward_temperature"
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),
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return_temperature_central_heating=config_provider(
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"sector", "district_heating", "return_temperature"
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),
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heat_source_cooling_central_heating=config_provider(
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"sector", "district_heating", "heat_source_cooling"
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),
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heat_pump_cop_approximation_central_heating=config_provider(
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"sector", "district_heating", "heat_pump_cop_approximation"
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),
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input:
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temp_soil_total=resources("temp_soil_total_elec_s{simpl}_{clusters}.nc"),
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temp_air_total=resources("temp_air_total_elec_s{simpl}_{clusters}.nc"),
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output:
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cop_air_decentral_heating=resources(
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"cop_air_decentral_heating_elec_s{simpl}_{clusters}.nc"
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),
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cop_soil_decentral_heating=resources(
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"cop_soil_decentral_heating_elec_s{simpl}_{clusters}.nc"
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),
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cop_air_central_heating=resources(
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"cop_air_central_heating_elec_s{simpl}_{clusters}.nc"
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),
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cop_soil_central_heating=resources(
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"cop_soil_central_heating_elec_s{simpl}_{clusters}.nc"
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),
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resources:
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mem_mb=20000,
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log:
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logs("build_cop_profiles_s{simpl}_{clusters}.log"),
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benchmark:
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benchmarks("build_cop_profiles/s{simpl}_{clusters}")
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/build_cop_profiles/run.py"
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def solar_thermal_cutout(wildcards):
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c = config_provider("solar_thermal", "cutout")(wildcards)
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if c == "default":
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return (
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"cutouts/"
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+ CDIR
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+ config_provider("atlite", "default_cutout")(wildcards)
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+ ".nc"
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)
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else:
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return "cutouts/" + CDIR + c + ".nc"
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rule build_solar_thermal_profiles:
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params:
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snapshots=config_provider("snapshots"),
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drop_leap_day=config_provider("enable", "drop_leap_day"),
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solar_thermal=config_provider("solar_thermal"),
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input:
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pop_layout=resources("pop_layout_total.nc"),
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regions_onshore=resources("regions_onshore_elec_s{simpl}_{clusters}.geojson"),
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cutout=solar_thermal_cutout,
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output:
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solar_thermal=resources("solar_thermal_total_elec_s{simpl}_{clusters}.nc"),
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resources:
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mem_mb=20000,
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threads: 16
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log:
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logs("build_solar_thermal_profiles_total_s{simpl}_{clusters}.log"),
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benchmark:
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benchmarks("build_solar_thermal_profiles/total_s{simpl}_{clusters}")
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/build_solar_thermal_profiles.py"
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rule build_energy_totals:
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params:
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countries=config_provider("countries"),
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energy=config_provider("energy"),
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input:
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nuts3_shapes=resources("nuts3_shapes.geojson"),
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co2="data/bundle/eea/UNFCCC_v23.csv",
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swiss="data/switzerland-new_format-all_years.csv",
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swiss_transport="data/gr-e-11.03.02.01.01-cc.csv",
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idees="data/bundle/jrc-idees-2015",
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district_heat_share="data/district_heat_share.csv",
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eurostat="data/eurostat/Balances-April2023",
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eurostat_households="data/eurostat/eurostat-household_energy_balances-february_2024.csv",
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output:
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energy_name=resources("energy_totals.csv"),
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co2_name=resources("co2_totals.csv"),
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transport_name=resources("transport_data.csv"),
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district_heat_share=resources("district_heat_share.csv"),
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threads: 16
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resources:
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mem_mb=10000,
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log:
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logs("build_energy_totals.log"),
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benchmark:
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benchmarks("build_energy_totals")
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/build_energy_totals.py"
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rule build_heat_totals:
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input:
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hdd="data/era5-annual-HDD-per-country.csv",
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energy_totals=resources("energy_totals.csv"),
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output:
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heat_totals=resources("heat_totals.csv"),
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threads: 1
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resources:
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mem_mb=2000,
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log:
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logs("build_heat_totals.log"),
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benchmark:
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benchmarks("build_heat_totals")
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/build_heat_totals.py"
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rule build_biomass_potentials:
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params:
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biomass=config_provider("biomass"),
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input:
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enspreso_biomass=storage(
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"https://zenodo.org/records/10356004/files/ENSPRESO_BIOMASS.xlsx",
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keep_local=True,
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),
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nuts2="data/bundle/nuts/NUTS_RG_10M_2013_4326_LEVL_2.geojson", # https://gisco-services.ec.europa.eu/distribution/v2/nuts/download/#nuts21
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regions_onshore=resources("regions_onshore_elec_s{simpl}_{clusters}.geojson"),
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nuts3_population=ancient("data/bundle/nama_10r_3popgdp.tsv.gz"),
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swiss_cantons=ancient("data/ch_cantons.csv"),
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swiss_population=ancient("data/bundle/je-e-21.03.02.xls"),
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country_shapes=resources("country_shapes.geojson"),
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output:
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biomass_potentials_all=resources(
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"biomass_potentials_all_s{simpl}_{clusters}_{planning_horizons}.csv"
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),
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biomass_potentials=resources(
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"biomass_potentials_s{simpl}_{clusters}_{planning_horizons}.csv"
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),
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threads: 1
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resources:
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mem_mb=1000,
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log:
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logs("build_biomass_potentials_s{simpl}_{clusters}_{planning_horizons}.log"),
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benchmark:
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benchmarks("build_biomass_potentials_s{simpl}_{clusters}_{planning_horizons}")
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/build_biomass_potentials.py"
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rule build_biomass_transport_costs:
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input:
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transport_cost_data=storage(
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"https://publications.jrc.ec.europa.eu/repository/bitstream/JRC98626/biomass potentials in europe_web rev.pdf",
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keep_local=True,
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),
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output:
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biomass_transport_costs=resources("biomass_transport_costs.csv"),
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threads: 1
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resources:
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mem_mb=1000,
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log:
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logs("build_biomass_transport_costs.log"),
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benchmark:
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benchmarks("build_biomass_transport_costs")
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/build_biomass_transport_costs.py"
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rule build_sequestration_potentials:
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params:
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sequestration_potential=config_provider(
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"sector", "regional_co2_sequestration_potential"
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),
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input:
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sequestration_potential=storage(
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"https://raw.githubusercontent.com/ericzhou571/Co2Storage/main/resources/complete_map_2020_unit_Mt.geojson",
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keep_local=True,
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),
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regions_onshore=resources("regions_onshore_elec_s{simpl}_{clusters}.geojson"),
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regions_offshore=resources("regions_offshore_elec_s{simpl}_{clusters}.geojson"),
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output:
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sequestration_potential=resources(
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"co2_sequestration_potential_elec_s{simpl}_{clusters}.csv"
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),
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threads: 1
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resources:
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mem_mb=4000,
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log:
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logs("build_sequestration_potentials_s{simpl}_{clusters}.log"),
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benchmark:
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benchmarks("build_sequestration_potentials_s{simpl}_{clusters}")
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/build_sequestration_potentials.py"
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rule build_salt_cavern_potentials:
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input:
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salt_caverns="data/bundle/h2_salt_caverns_GWh_per_sqkm.geojson",
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regions_onshore=resources("regions_onshore_elec_s{simpl}_{clusters}.geojson"),
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regions_offshore=resources("regions_offshore_elec_s{simpl}_{clusters}.geojson"),
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output:
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h2_cavern_potential=resources("salt_cavern_potentials_s{simpl}_{clusters}.csv"),
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threads: 1
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resources:
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mem_mb=2000,
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log:
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logs("build_salt_cavern_potentials_s{simpl}_{clusters}.log"),
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benchmark:
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benchmarks("build_salt_cavern_potentials_s{simpl}_{clusters}")
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/build_salt_cavern_potentials.py"
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rule build_ammonia_production:
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input:
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usgs="data/bundle/myb1-2017-nitro.xls",
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output:
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ammonia_production=resources("ammonia_production.csv"),
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threads: 1
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resources:
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mem_mb=1000,
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log:
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logs("build_ammonia_production.log"),
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benchmark:
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benchmarks("build_ammonia_production")
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conda:
|
|
"../envs/environment.yaml"
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script:
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"../scripts/build_ammonia_production.py"
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rule build_industry_sector_ratios:
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params:
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industry=config_provider("industry"),
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ammonia=config_provider("sector", "ammonia", default=False),
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input:
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ammonia_production=resources("ammonia_production.csv"),
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idees="data/bundle/jrc-idees-2015",
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output:
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industry_sector_ratios=resources("industry_sector_ratios.csv"),
|
|
threads: 1
|
|
resources:
|
|
mem_mb=1000,
|
|
log:
|
|
logs("build_industry_sector_ratios.log"),
|
|
benchmark:
|
|
benchmarks("build_industry_sector_ratios")
|
|
conda:
|
|
"../envs/environment.yaml"
|
|
script:
|
|
"../scripts/build_industry_sector_ratios.py"
|
|
|
|
|
|
rule build_industry_sector_ratios_intermediate:
|
|
params:
|
|
industry=config_provider("industry"),
|
|
input:
|
|
industry_sector_ratios=resources("industry_sector_ratios.csv"),
|
|
industrial_energy_demand_per_country_today=resources(
|
|
"industrial_energy_demand_per_country_today.csv"
|
|
),
|
|
industrial_production_per_country=resources(
|
|
"industrial_production_per_country.csv"
|
|
),
|
|
output:
|
|
industry_sector_ratios=resources(
|
|
"industry_sector_ratios_{planning_horizons}.csv"
|
|
),
|
|
threads: 1
|
|
resources:
|
|
mem_mb=1000,
|
|
log:
|
|
logs("build_industry_sector_ratios_{planning_horizons}.log"),
|
|
benchmark:
|
|
benchmarks("build_industry_sector_ratios_{planning_horizons}")
|
|
conda:
|
|
"../envs/environment.yaml"
|
|
script:
|
|
"../scripts/build_industry_sector_ratios_intermediate.py"
|
|
|
|
|
|
rule build_industrial_production_per_country:
|
|
params:
|
|
industry=config_provider("industry"),
|
|
countries=config_provider("countries"),
|
|
input:
|
|
ammonia_production=resources("ammonia_production.csv"),
|
|
jrc="data/bundle/jrc-idees-2015",
|
|
eurostat="data/eurostat/Balances-April2023",
|
|
output:
|
|
industrial_production_per_country=resources(
|
|
"industrial_production_per_country.csv"
|
|
),
|
|
threads: 8
|
|
resources:
|
|
mem_mb=1000,
|
|
log:
|
|
logs("build_industrial_production_per_country.log"),
|
|
benchmark:
|
|
benchmarks("build_industrial_production_per_country")
|
|
conda:
|
|
"../envs/environment.yaml"
|
|
script:
|
|
"../scripts/build_industrial_production_per_country.py"
|
|
|
|
|
|
rule build_industrial_production_per_country_tomorrow:
|
|
params:
|
|
industry=config_provider("industry"),
|
|
input:
|
|
industrial_production_per_country=resources(
|
|
"industrial_production_per_country.csv"
|
|
),
|
|
output:
|
|
industrial_production_per_country_tomorrow=resources(
|
|
"industrial_production_per_country_tomorrow_{planning_horizons}.csv"
|
|
),
|
|
threads: 1
|
|
resources:
|
|
mem_mb=1000,
|
|
log:
|
|
logs("build_industrial_production_per_country_tomorrow_{planning_horizons}.log"),
|
|
benchmark:
|
|
(
|
|
benchmarks(
|
|
"build_industrial_production_per_country_tomorrow_{planning_horizons}"
|
|
)
|
|
)
|
|
conda:
|
|
"../envs/environment.yaml"
|
|
script:
|
|
"../scripts/build_industrial_production_per_country_tomorrow.py"
|
|
|
|
|
|
rule build_industrial_distribution_key:
|
|
params:
|
|
hotmaps_locate_missing=config_provider(
|
|
"industry", "hotmaps_locate_missing", default=False
|
|
),
|
|
countries=config_provider("countries"),
|
|
input:
|
|
regions_onshore=resources("regions_onshore_elec_s{simpl}_{clusters}.geojson"),
|
|
clustered_pop_layout=resources("pop_layout_elec_s{simpl}_{clusters}.csv"),
|
|
hotmaps_industrial_database=storage(
|
|
"https://gitlab.com/hotmaps/industrial_sites/industrial_sites_Industrial_Database/-/raw/master/data/Industrial_Database.csv",
|
|
keep_local=True,
|
|
),
|
|
output:
|
|
industrial_distribution_key=resources(
|
|
"industrial_distribution_key_elec_s{simpl}_{clusters}.csv"
|
|
),
|
|
threads: 1
|
|
resources:
|
|
mem_mb=1000,
|
|
log:
|
|
logs("build_industrial_distribution_key_s{simpl}_{clusters}.log"),
|
|
benchmark:
|
|
benchmarks("build_industrial_distribution_key/s{simpl}_{clusters}")
|
|
conda:
|
|
"../envs/environment.yaml"
|
|
script:
|
|
"../scripts/build_industrial_distribution_key.py"
|
|
|
|
|
|
rule build_industrial_production_per_node:
|
|
input:
|
|
industrial_distribution_key=resources(
|
|
"industrial_distribution_key_elec_s{simpl}_{clusters}.csv"
|
|
),
|
|
industrial_production_per_country_tomorrow=resources(
|
|
"industrial_production_per_country_tomorrow_{planning_horizons}.csv"
|
|
),
|
|
output:
|
|
industrial_production_per_node=resources(
|
|
"industrial_production_elec_s{simpl}_{clusters}_{planning_horizons}.csv"
|
|
),
|
|
threads: 1
|
|
resources:
|
|
mem_mb=1000,
|
|
log:
|
|
logs(
|
|
"build_industrial_production_per_node_s{simpl}_{clusters}_{planning_horizons}.log"
|
|
),
|
|
benchmark:
|
|
(
|
|
benchmarks(
|
|
"build_industrial_production_per_node/s{simpl}_{clusters}_{planning_horizons}"
|
|
)
|
|
)
|
|
conda:
|
|
"../envs/environment.yaml"
|
|
script:
|
|
"../scripts/build_industrial_production_per_node.py"
|
|
|
|
|
|
rule build_industrial_energy_demand_per_node:
|
|
input:
|
|
industry_sector_ratios=resources(
|
|
"industry_sector_ratios_{planning_horizons}.csv"
|
|
),
|
|
industrial_production_per_node=resources(
|
|
"industrial_production_elec_s{simpl}_{clusters}_{planning_horizons}.csv"
|
|
),
|
|
industrial_energy_demand_per_node_today=resources(
|
|
"industrial_energy_demand_today_elec_s{simpl}_{clusters}.csv"
|
|
),
|
|
output:
|
|
industrial_energy_demand_per_node=resources(
|
|
"industrial_energy_demand_elec_s{simpl}_{clusters}_{planning_horizons}.csv"
|
|
),
|
|
threads: 1
|
|
resources:
|
|
mem_mb=1000,
|
|
log:
|
|
logs(
|
|
"build_industrial_energy_demand_per_node_s{simpl}_{clusters}_{planning_horizons}.log"
|
|
),
|
|
benchmark:
|
|
(
|
|
benchmarks(
|
|
"build_industrial_energy_demand_per_node/s{simpl}_{clusters}_{planning_horizons}"
|
|
)
|
|
)
|
|
conda:
|
|
"../envs/environment.yaml"
|
|
script:
|
|
"../scripts/build_industrial_energy_demand_per_node.py"
|
|
|
|
|
|
rule build_industrial_energy_demand_per_country_today:
|
|
params:
|
|
countries=config_provider("countries"),
|
|
industry=config_provider("industry"),
|
|
input:
|
|
jrc="data/bundle/jrc-idees-2015",
|
|
industrial_production_per_country=resources(
|
|
"industrial_production_per_country.csv"
|
|
),
|
|
output:
|
|
industrial_energy_demand_per_country_today=resources(
|
|
"industrial_energy_demand_per_country_today.csv"
|
|
),
|
|
threads: 8
|
|
resources:
|
|
mem_mb=1000,
|
|
log:
|
|
logs("build_industrial_energy_demand_per_country_today.log"),
|
|
benchmark:
|
|
benchmarks("build_industrial_energy_demand_per_country_today")
|
|
conda:
|
|
"../envs/environment.yaml"
|
|
script:
|
|
"../scripts/build_industrial_energy_demand_per_country_today.py"
|
|
|
|
|
|
rule build_industrial_energy_demand_per_node_today:
|
|
input:
|
|
industrial_distribution_key=resources(
|
|
"industrial_distribution_key_elec_s{simpl}_{clusters}.csv"
|
|
),
|
|
industrial_energy_demand_per_country_today=resources(
|
|
"industrial_energy_demand_per_country_today.csv"
|
|
),
|
|
output:
|
|
industrial_energy_demand_per_node_today=resources(
|
|
"industrial_energy_demand_today_elec_s{simpl}_{clusters}.csv"
|
|
),
|
|
threads: 1
|
|
resources:
|
|
mem_mb=1000,
|
|
log:
|
|
logs("build_industrial_energy_demand_per_node_today_s{simpl}_{clusters}.log"),
|
|
benchmark:
|
|
benchmarks("build_industrial_energy_demand_per_node_today/s{simpl}_{clusters}")
|
|
conda:
|
|
"../envs/environment.yaml"
|
|
script:
|
|
"../scripts/build_industrial_energy_demand_per_node_today.py"
|
|
|
|
|
|
rule build_retro_cost:
|
|
params:
|
|
retrofitting=config_provider("sector", "retrofitting"),
|
|
countries=config_provider("countries"),
|
|
input:
|
|
building_stock="data/retro/data_building_stock.csv",
|
|
data_tabula="data/bundle/retro/tabula-calculator-calcsetbuilding.csv",
|
|
air_temperature=resources("temp_air_total_elec_s{simpl}_{clusters}.nc"),
|
|
u_values_PL="data/retro/u_values_poland.csv",
|
|
tax_w="data/retro/electricity_taxes_eu.csv",
|
|
construction_index="data/retro/comparative_level_investment.csv",
|
|
floor_area_missing="data/retro/floor_area_missing.csv",
|
|
clustered_pop_layout=resources("pop_layout_elec_s{simpl}_{clusters}.csv"),
|
|
cost_germany="data/retro/retro_cost_germany.csv",
|
|
window_assumptions="data/retro/window_assumptions.csv",
|
|
output:
|
|
retro_cost=resources("retro_cost_elec_s{simpl}_{clusters}.csv"),
|
|
floor_area=resources("floor_area_elec_s{simpl}_{clusters}.csv"),
|
|
resources:
|
|
mem_mb=1000,
|
|
log:
|
|
logs("build_retro_cost_s{simpl}_{clusters}.log"),
|
|
benchmark:
|
|
benchmarks("build_retro_cost/s{simpl}_{clusters}")
|
|
conda:
|
|
"../envs/environment.yaml"
|
|
script:
|
|
"../scripts/build_retro_cost.py"
|
|
|
|
|
|
rule build_population_weighted_energy_totals:
|
|
params:
|
|
snapshots=config_provider("snapshots"),
|
|
input:
|
|
energy_totals=resources("{kind}_totals.csv"),
|
|
clustered_pop_layout=resources("pop_layout_elec_s{simpl}_{clusters}.csv"),
|
|
output:
|
|
resources("pop_weighted_{kind}_totals_s{simpl}_{clusters}.csv"),
|
|
threads: 1
|
|
resources:
|
|
mem_mb=2000,
|
|
log:
|
|
logs("build_population_weighted_{kind}_totals_s{simpl}_{clusters}.log"),
|
|
conda:
|
|
"../envs/environment.yaml"
|
|
script:
|
|
"../scripts/build_population_weighted_energy_totals.py"
|
|
|
|
|
|
rule build_shipping_demand:
|
|
input:
|
|
ports="data/attributed_ports.json",
|
|
scope=resources("europe_shape.geojson"),
|
|
regions=resources("regions_onshore_elec_s{simpl}_{clusters}.geojson"),
|
|
demand=resources("energy_totals.csv"),
|
|
params:
|
|
energy_totals_year=config_provider("energy", "energy_totals_year"),
|
|
output:
|
|
resources("shipping_demand_s{simpl}_{clusters}.csv"),
|
|
threads: 1
|
|
resources:
|
|
mem_mb=2000,
|
|
log:
|
|
logs("build_shipping_demand_s{simpl}_{clusters}.log"),
|
|
conda:
|
|
"../envs/environment.yaml"
|
|
script:
|
|
"../scripts/build_shipping_demand.py"
|
|
|
|
|
|
rule build_transport_demand:
|
|
params:
|
|
snapshots=config_provider("snapshots"),
|
|
drop_leap_day=config_provider("enable", "drop_leap_day"),
|
|
sector=config_provider("sector"),
|
|
energy_totals_year=config_provider("energy", "energy_totals_year"),
|
|
input:
|
|
clustered_pop_layout=resources("pop_layout_elec_s{simpl}_{clusters}.csv"),
|
|
pop_weighted_energy_totals=resources(
|
|
"pop_weighted_energy_totals_s{simpl}_{clusters}.csv"
|
|
),
|
|
transport_data=resources("transport_data.csv"),
|
|
traffic_data_KFZ="data/bundle/emobility/KFZ__count",
|
|
traffic_data_Pkw="data/bundle/emobility/Pkw__count",
|
|
temp_air_total=resources("temp_air_total_elec_s{simpl}_{clusters}.nc"),
|
|
output:
|
|
transport_demand=resources("transport_demand_s{simpl}_{clusters}.csv"),
|
|
transport_data=resources("transport_data_s{simpl}_{clusters}.csv"),
|
|
avail_profile=resources("avail_profile_s{simpl}_{clusters}.csv"),
|
|
dsm_profile=resources("dsm_profile_s{simpl}_{clusters}.csv"),
|
|
threads: 1
|
|
resources:
|
|
mem_mb=2000,
|
|
log:
|
|
logs("build_transport_demand_s{simpl}_{clusters}.log"),
|
|
conda:
|
|
"../envs/environment.yaml"
|
|
script:
|
|
"../scripts/build_transport_demand.py"
|
|
|
|
|
|
rule build_district_heat_share:
|
|
params:
|
|
sector=config_provider("sector"),
|
|
energy_totals_year=config_provider("energy", "energy_totals_year"),
|
|
input:
|
|
district_heat_share=resources("district_heat_share.csv"),
|
|
clustered_pop_layout=resources("pop_layout_elec_s{simpl}_{clusters}.csv"),
|
|
output:
|
|
district_heat_share=resources(
|
|
"district_heat_share_elec_s{simpl}_{clusters}_{planning_horizons}.csv"
|
|
),
|
|
threads: 1
|
|
resources:
|
|
mem_mb=1000,
|
|
log:
|
|
logs("build_district_heat_share_s{simpl}_{clusters}_{planning_horizons}.log"),
|
|
conda:
|
|
"../envs/environment.yaml"
|
|
script:
|
|
"../scripts/build_district_heat_share.py"
|
|
|
|
|
|
rule build_existing_heating_distribution:
|
|
params:
|
|
baseyear=config_provider("scenario", "planning_horizons", 0),
|
|
sector=config_provider("sector"),
|
|
existing_capacities=config_provider("existing_capacities"),
|
|
input:
|
|
existing_heating="data/existing_infrastructure/existing_heating_raw.csv",
|
|
clustered_pop_layout=resources("pop_layout_elec_s{simpl}_{clusters}.csv"),
|
|
clustered_pop_energy_layout=resources(
|
|
"pop_weighted_energy_totals_s{simpl}_{clusters}.csv"
|
|
),
|
|
district_heat_share=resources(
|
|
"district_heat_share_elec_s{simpl}_{clusters}_{planning_horizons}.csv"
|
|
),
|
|
output:
|
|
existing_heating_distribution=resources(
|
|
"existing_heating_distribution_elec_s{simpl}_{clusters}_{planning_horizons}.csv"
|
|
),
|
|
threads: 1
|
|
resources:
|
|
mem_mb=2000,
|
|
log:
|
|
logs(
|
|
"build_existing_heating_distribution_elec_s{simpl}_{clusters}_{planning_horizons}.log"
|
|
),
|
|
benchmark:
|
|
benchmarks(
|
|
"build_existing_heating_distribution/elec_s{simpl}_{clusters}_{planning_horizons}"
|
|
)
|
|
conda:
|
|
"../envs/environment.yaml"
|
|
script:
|
|
"../scripts/build_existing_heating_distribution.py"
|
|
|
|
|
|
rule time_aggregation:
|
|
params:
|
|
time_resolution=config_provider("clustering", "temporal", "resolution_sector"),
|
|
drop_leap_day=config_provider("enable", "drop_leap_day"),
|
|
solver_name=config_provider("solving", "solver", "name"),
|
|
input:
|
|
network=resources("networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc"),
|
|
hourly_heat_demand_total=lambda w: (
|
|
resources("hourly_heat_demand_total_elec_s{simpl}_{clusters}.nc")
|
|
if config_provider("sector", "heating")(w)
|
|
else []
|
|
),
|
|
solar_thermal_total=lambda w: (
|
|
resources("solar_thermal_total_elec_s{simpl}_{clusters}.nc")
|
|
if config_provider("sector", "solar_thermal")(w)
|
|
else []
|
|
),
|
|
output:
|
|
snapshot_weightings=resources(
|
|
"snapshot_weightings_elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.csv"
|
|
),
|
|
threads: 1
|
|
resources:
|
|
mem_mb=5000,
|
|
log:
|
|
logs("time_aggregation_elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.log"),
|
|
benchmark:
|
|
benchmarks("time_aggregation_elec_s{simpl}_{clusters}_ec_l{ll}_{opts}")
|
|
conda:
|
|
"../envs/environment.yaml"
|
|
script:
|
|
"../scripts/time_aggregation.py"
|
|
|
|
|
|
def input_profile_offwind(w):
|
|
return {
|
|
f"profile_{tech}": resources(f"profile_{tech}.nc")
|
|
for tech in ["offwind-ac", "offwind-dc", "offwind-float"]
|
|
if (tech in config_provider("electricity", "renewable_carriers")(w))
|
|
}
|
|
|
|
|
|
rule build_egs_potentials:
|
|
params:
|
|
snapshots=config_provider("snapshots"),
|
|
sector=config_provider("sector"),
|
|
costs=config_provider("costs"),
|
|
input:
|
|
egs_cost="data/egs_costs.json",
|
|
regions=resources("regions_onshore_elec_s{simpl}_{clusters}.geojson"),
|
|
air_temperature=(
|
|
resources("temp_air_total_elec_s{simpl}_{clusters}.nc")
|
|
if config_provider("sector", "enhanced_geothermal", "var_cf")
|
|
else []
|
|
),
|
|
output:
|
|
egs_potentials=resources("egs_potentials_s{simpl}_{clusters}.csv"),
|
|
egs_overlap=resources("egs_overlap_s{simpl}_{clusters}.csv"),
|
|
egs_capacity_factors=resources("egs_capacity_factors_s{simpl}_{clusters}.csv"),
|
|
threads: 1
|
|
resources:
|
|
mem_mb=2000,
|
|
log:
|
|
logs("build_egs_potentials_s{simpl}_{clusters}.log"),
|
|
conda:
|
|
"../envs/environment.yaml"
|
|
script:
|
|
"../scripts/build_egs_potentials.py"
|
|
|
|
|
|
rule prepare_sector_network:
|
|
params:
|
|
time_resolution=config_provider("clustering", "temporal", "resolution_sector"),
|
|
co2_budget=config_provider("co2_budget"),
|
|
conventional_carriers=config_provider(
|
|
"existing_capacities", "conventional_carriers"
|
|
),
|
|
foresight=config_provider("foresight"),
|
|
costs=config_provider("costs"),
|
|
sector=config_provider("sector"),
|
|
industry=config_provider("industry"),
|
|
lines=config_provider("lines"),
|
|
pypsa_eur=config_provider("pypsa_eur"),
|
|
length_factor=config_provider("lines", "length_factor"),
|
|
planning_horizons=config_provider("scenario", "planning_horizons"),
|
|
countries=config_provider("countries"),
|
|
adjustments=config_provider("adjustments", "sector"),
|
|
emissions_scope=config_provider("energy", "emissions"),
|
|
RDIR=RDIR,
|
|
input:
|
|
unpack(input_profile_offwind),
|
|
**rules.cluster_gas_network.output,
|
|
**rules.build_gas_input_locations.output,
|
|
snapshot_weightings=resources(
|
|
"snapshot_weightings_elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.csv"
|
|
),
|
|
retro_cost=lambda w: (
|
|
resources("retro_cost_elec_s{simpl}_{clusters}.csv")
|
|
if config_provider("sector", "retrofitting", "retro_endogen")(w)
|
|
else []
|
|
),
|
|
floor_area=lambda w: (
|
|
resources("floor_area_elec_s{simpl}_{clusters}.csv")
|
|
if config_provider("sector", "retrofitting", "retro_endogen")(w)
|
|
else []
|
|
),
|
|
biomass_transport_costs=lambda w: (
|
|
resources("biomass_transport_costs.csv")
|
|
if config_provider("sector", "biomass_transport")(w)
|
|
or config_provider("sector", "biomass_spatial")(w)
|
|
else []
|
|
),
|
|
sequestration_potential=lambda w: (
|
|
resources("co2_sequestration_potential_elec_s{simpl}_{clusters}.csv")
|
|
if config_provider(
|
|
"sector", "regional_co2_sequestration_potential", "enable"
|
|
)(w)
|
|
else []
|
|
),
|
|
network=resources("networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc"),
|
|
eurostat="data/eurostat/Balances-April2023",
|
|
pop_weighted_energy_totals=resources(
|
|
"pop_weighted_energy_totals_s{simpl}_{clusters}.csv"
|
|
),
|
|
pop_weighted_heat_totals=resources(
|
|
"pop_weighted_heat_totals_s{simpl}_{clusters}.csv"
|
|
),
|
|
shipping_demand=resources("shipping_demand_s{simpl}_{clusters}.csv"),
|
|
transport_demand=resources("transport_demand_s{simpl}_{clusters}.csv"),
|
|
transport_data=resources("transport_data_s{simpl}_{clusters}.csv"),
|
|
avail_profile=resources("avail_profile_s{simpl}_{clusters}.csv"),
|
|
dsm_profile=resources("dsm_profile_s{simpl}_{clusters}.csv"),
|
|
co2_totals_name=resources("co2_totals.csv"),
|
|
co2="data/bundle/eea/UNFCCC_v23.csv",
|
|
biomass_potentials=lambda w: (
|
|
resources(
|
|
"biomass_potentials_s{simpl}_{clusters}_"
|
|
+ "{}.csv".format(config_provider("biomass", "year")(w))
|
|
)
|
|
if config_provider("foresight")(w) == "overnight"
|
|
else resources(
|
|
"biomass_potentials_s{simpl}_{clusters}_{planning_horizons}.csv"
|
|
)
|
|
),
|
|
costs=lambda w: (
|
|
resources("costs_{}.csv".format(config_provider("costs", "year")(w)))
|
|
if config_provider("foresight")(w) == "overnight"
|
|
else resources("costs_{planning_horizons}.csv")
|
|
),
|
|
h2_cavern=resources("salt_cavern_potentials_s{simpl}_{clusters}.csv"),
|
|
busmap_s=resources("busmap_elec_s{simpl}.csv"),
|
|
busmap=resources("busmap_elec_s{simpl}_{clusters}.csv"),
|
|
clustered_pop_layout=resources("pop_layout_elec_s{simpl}_{clusters}.csv"),
|
|
simplified_pop_layout=resources("pop_layout_elec_s{simpl}.csv"),
|
|
industrial_demand=resources(
|
|
"industrial_energy_demand_elec_s{simpl}_{clusters}_{planning_horizons}.csv"
|
|
),
|
|
hourly_heat_demand_total=resources(
|
|
"hourly_heat_demand_total_elec_s{simpl}_{clusters}.nc"
|
|
),
|
|
district_heat_share=resources(
|
|
"district_heat_share_elec_s{simpl}_{clusters}_{planning_horizons}.csv"
|
|
),
|
|
temp_soil_total=resources("temp_soil_total_elec_s{simpl}_{clusters}.nc"),
|
|
temp_air_total=resources("temp_air_total_elec_s{simpl}_{clusters}.nc"),
|
|
cop_soil_decentral_heating=resources(
|
|
"cop_soil_decentral_heating_elec_s{simpl}_{clusters}.nc"
|
|
),
|
|
cop_air_decentral_heating=resources(
|
|
"cop_air_decentral_heating_elec_s{simpl}_{clusters}.nc"
|
|
),
|
|
cop_air_central_heating=resources(
|
|
"cop_air_central_heating_elec_s{simpl}_{clusters}.nc"
|
|
),
|
|
cop_soil_central_heating=resources(
|
|
"cop_soil_central_heating_elec_s{simpl}_{clusters}.nc"
|
|
),
|
|
cop_soil_total=resources("cop_soil_total_elec_s{simpl}_{clusters}.nc"),
|
|
cop_air_total=resources("cop_air_total_elec_s{simpl}_{clusters}.nc"),
|
|
solar_thermal_total=lambda w: (
|
|
resources("solar_thermal_total_elec_s{simpl}_{clusters}.nc")
|
|
if config_provider("sector", "solar_thermal")(w)
|
|
else []
|
|
),
|
|
egs_potentials=lambda w: (
|
|
resources("egs_potentials_s{simpl}_{clusters}.csv")
|
|
if config_provider("sector", "enhanced_geothermal", "enable")(w)
|
|
else []
|
|
),
|
|
egs_overlap=lambda w: (
|
|
resources("egs_overlap_s{simpl}_{clusters}.csv")
|
|
if config_provider("sector", "enhanced_geothermal", "enable")(w)
|
|
else []
|
|
),
|
|
egs_capacity_factors=lambda w: (
|
|
resources("egs_capacity_factors_s{simpl}_{clusters}.csv")
|
|
if config_provider("sector", "enhanced_geothermal", "enable")(w)
|
|
else []
|
|
),
|
|
output:
|
|
RESULTS
|
|
+ "prenetworks/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc",
|
|
threads: 1
|
|
resources:
|
|
mem_mb=2000,
|
|
log:
|
|
RESULTS
|
|
+ "logs/prepare_sector_network_elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.log",
|
|
benchmark:
|
|
(
|
|
RESULTS
|
|
+ "benchmarks/prepare_sector_network/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}"
|
|
)
|
|
conda:
|
|
"../envs/environment.yaml"
|
|
script:
|
|
"../scripts/prepare_sector_network.py"
|