included Lisas PR suggestions
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LukasFrankenQ
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@ -577,13 +577,15 @@ sector:
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solar: 3
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offwind-ac: 3
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offwind-dc: 3
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enhanced_geothermal: false
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enhanced_geothermal_optimism: false # if true, egs costs are reducing towards 2050 according to Aghahosseini et al., (2020)
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enhanced_geothermal_performant: true # if true, adds only the cheapest patch of EGS potential to each region
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enhanced_geothermal_flexible: true # if true, adds a storage unit simulating flexible operation of EGS, see Ricks et al. 2023
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enhanced_geothermal_var_cf: true # if true, adds time-dependent capacity factor to EGS, see Ricks et al. 2023
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enhanced_geothermal_reservoir_max_hours: 240 # relavant for flexible EGS, see Ricks et al. 2023
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enhanced_geothermal_reservoir_max_boost: 0.25 # share of generation that can be added by flexible EGS, see Ricks et al. 2023
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enhanced_geothermal:
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enable: false
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optimism: false # if true, egs costs are reducing towards 2050 according to Aghahosseini et al., (2020)
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performant: true # if true, adds only the cheapest patch of EGS potential to each region
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flexible: true # if true, adds a storage unit simulating flexible operation of EGS, see Ricks et al. 2023
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var_cf: true # if true, adds time-dependent capacity factor to EGS, see Ricks et al. 2023
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max_hours: 240 # relavant for flexible EGS, see Ricks et al. 2023
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max_boost: 0.25 # share of generation that can be added by flexible EGS, see Ricks et al. 2023
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sustainability_factor: 0.0025 # share of capacity that is replenished from earth's core
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# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#industry
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industry:
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@ -20,7 +20,7 @@ dependencies:
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- openpyxl!=3.1.1
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- pycountry
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- seaborn
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- snakemake-minimal>=8.5
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- snakemake-minimal>=8.5,<8.6
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- memory_profiler
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- yaml
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- pytables
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@ -816,36 +816,6 @@ def input_profile_offwind(w):
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}
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rule build_egs_potentials:
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params:
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snapshots=config_provider("snapshots"),
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input:
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egs_cost="data/egs_costs.json",
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regions=resources("regions_onshore_elec_s{simpl}_{clusters}.geojson"),
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air_temperature=(
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resources("temp_air_total_elec_s{simpl}_{clusters}.nc")
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if config_provider("sector", "enhanced_geothermal_var_cf")
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else []
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),
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output:
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egs_potentials=resources("egs_potentials_s{simpl}_{clusters}.csv"),
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egs_overlap=resources("egs_overlap_s{simpl}_{clusters}.csv"),
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egs_capacity_factors=(
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resources("egs_capacity_factors_s{simpl}_{clusters}.csv")
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if config_provider("sector", "enhanced_geothermal_var_cf")
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else []
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),
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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_egs_potentials_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_egs_potentials.py"
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rule prepare_sector_network:
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params:
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time_resolution=config_provider("clustering", "temporal", "resolution_sector"),
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@ -946,13 +916,6 @@ rule prepare_sector_network:
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cop_air_total=resources("cop_air_total_elec_s{simpl}_{clusters}.nc"),
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cop_air_rural=resources("cop_air_rural_elec_s{simpl}_{clusters}.nc"),
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cop_air_urban=resources("cop_air_urban_elec_s{simpl}_{clusters}.nc"),
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egs_potentials=RESOURCES + "egs_potentials_s{simpl}_{clusters}.csv",
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egs_overlap=RESOURCES + "egs_overlap_s{simpl}_{clusters}.csv",
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egs_capacity_factors=(
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RESOURCES + "egs_capacity_factors_s{simpl}_{clusters}.csv"
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if config["sector"]["enhanced_geothermal_var_cf"]
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else []
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),
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solar_thermal_total=lambda w: (
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resources("solar_thermal_total_elec_s{simpl}_{clusters}.nc")
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if config_provider("sector", "solar_thermal")(w)
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@ -93,6 +93,10 @@ def get_capacity_factors(network_regions_file, air_temperatures_file):
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in Decarbonized Elec Systems.
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"""
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# these values are taken from the paper's
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# Supplementary Figure 20 from https://zenodo.org/records/7093330
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# and relate deviations of the ambient temperature from the year-average
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# ambient temperature to EGS capacity factors.
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delta_T = [-15, -10, -5, 0, 5, 10, 15, 20]
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cf = [1.17, 1.13, 1.07, 1, 0.925, 0.84, 0.75, 0.65]
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@ -118,6 +122,10 @@ def get_capacity_factors(network_regions_file, air_temperatures_file):
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snapshots = pd.date_range(freq="h", **snakemake.params.snapshots)
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capacity_factors = pd.DataFrame(index=snapshots)
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# bespoke computation of capacity factors for each bus.
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# Considering the respective temperatures, we compute
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# the deviation from the average temperature and relate it
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# to capacity factors based on the data from above.
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for bus in index:
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temp = air_temp.sel(name=bus).to_dataframe()["temperature"]
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capacity_factors[bus] = np.interp((temp - temp.mean()).values, x, y)
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@ -135,18 +143,20 @@ if __name__ == "__main__":
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clusters=37,
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)
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sustainability_factor = 0.0025
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egs_config = snakemake.params["sector"]["enhanced_geothermal"]
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costs_config = snakemake.params["costs"]
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sustainability_factor = egs_config["sustainability_factor"]
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# the share of heat that is replenished from the earth's core.
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# we are not constraining ourselves to the sustainable share, but
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# inversely apply it to our underlying data, which refers to the
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# sustainable heat.
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config = snakemake.config
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# sustainable heat. Source: Relative magnitude of sustainable heat vs
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# nonsustainable heat in the paper "From hot rock to useful energy..."
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egs_data = prepare_egs_data(snakemake.input.egs_cost)
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if config["sector"]["enhanced_geothermal_optimism"]:
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egs_data = egs_data[(year := config["costs"]["year"])]
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if egs_config["optimism"]:
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egs_data = egs_data[(year := costs_config["year"])]
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logger.info(
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f"EGS optimism! Building EGS potentials with costs estimated for {year}."
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)
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@ -3582,7 +3582,8 @@ def add_enhanced_geothermal(
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"'add_enhanced_geothermal' not implemented for multiple geothermal nodes."
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)
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config = snakemake.config
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egs_config = snakemake.params["sector"]["enhanced_geothermal"]
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costs_config = snakemake.config["costs"]
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# matrix defining the overlap between gridded geothermal potential estimation, and bus regions
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overlap = pd.read_csv(egs_overlap, index_col=0)
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@ -3590,7 +3591,7 @@ def add_enhanced_geothermal(
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egs_potentials = pd.read_csv(egs_potentials, index_col=0)
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Nyears = n.snapshot_weightings.generators.sum() / 8760
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dr = config["costs"]["fill_values"]["discount rate"]
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dr = costs_config["fill_values"]["discount rate"]
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lt = costs.at["geothermal", "lifetime"]
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FOM = costs.at["geothermal", "FOM"]
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@ -3673,7 +3674,7 @@ def add_enhanced_geothermal(
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bus_egs["p_nom_max"] = bus_egs["p_nom_max"].multiply(bus_overlap)
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bus_egs = bus_egs.loc[bus_egs.p_nom_max > 0.0]
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if config["sector"]["enhanced_geothermal_performant"]:
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if egs_config["performant"]:
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bus_egs = bus_egs.sort_values(by="capital_cost").iloc[:1]
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appendix = pd.Index([""])
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else:
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@ -3718,7 +3719,7 @@ def add_enhanced_geothermal(
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p_nom_extendable=True,
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carrier="geothermal organic rankine cycle",
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capital_cost=plant_capital_cost * efficiency_orc,
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efficiency=efficiency_orc if not as_chp else efficiency_orc * 2.0,
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efficiency=efficiency_orc,
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)
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if as_chp and bus + " urban central heat" in n.buses.index:
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@ -3731,7 +3732,7 @@ def add_enhanced_geothermal(
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capital_cost=plant_capital_cost
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* efficiency_orc
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* costs.at["geothermal", "district heating cost"],
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efficiency=efficiency_dh * 2.0,
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efficiency=efficiency_dh,
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p_nom_extendable=True,
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)
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elif as_chp and not bus + " urban central heat" in n.buses.index:
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@ -3739,15 +3740,13 @@ def add_enhanced_geothermal(
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efficiency_orc
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)
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if snakemake.params.sector["enhanced_geothermal_flexible"]:
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if egs_config["flexible"]:
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# this StorageUnit represents flexible operation using the geothermal reservoir.
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# Hence, it is counter-intuitive to install it at the surface bus,
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# this is however the more lean and computationally efficient solution.
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max_hours = snakemake.params.sector[
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"enhanced_geothermal_reservoir_max_hours"
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]
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boost = snakemake.params.sector["enhanced_geothermal_reservoir_max_boost"]
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max_hours = egs_config["reservoir_max_hours"]
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boost = egs_config["reservoir_max_boost"]
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n.add(
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"StorageUnit",
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@ -3912,7 +3911,7 @@ if __name__ == "__main__":
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if options.get("cluster_heat_buses", False) and not first_year_myopic:
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cluster_heat_buses(n)
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if options.get("enhanced_geothermal", False):
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if options["enhanced_geothermal"].get("enable", False):
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logger.info("Adding Enhanced Geothermal Potential.")
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add_enhanced_geothermal(
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n, snakemake.input["egs_potentials"], snakemake.input["egs_overlap"], costs
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@ -816,7 +816,7 @@ def add_geothermal_chp_constraint(n):
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def add_flexible_egs_constraint(n):
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well_index = n.links.loc[n.links.carrier == "geothermal heat"].index
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storage_index = n.storage_units.loc[
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n.storage_units.carrier == "geothermal heat "
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n.storage_units.carrier == "geothermal heat"
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].index
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p_nom_rhs = n.model["Link-p_nom"].loc[well_index]
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