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Merge pull request #324 from openego/features/#308-do-not-scale-heat-…
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…demand-timeseries

Features/#308 do not scale heat demand timeseries
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@ClaraBuettner
ClaraBuettner authored Sep 25, 2024
2 parents f6ec6f6 + aee228e commit c3c3210
Showing 1 changed file with 124 additions and 67 deletions.
191 changes: 124 additions & 67 deletions src/egon/data/datasets/pypsaeur/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1478,8 +1478,8 @@ def geothermal_district_heating(network):

network.add(
"Generator",
f"DE1 0 urban central geo thermal {i}",
bus="DE1 0 urban central heat",
f"DE0 0 urban central geo thermal {i}",
bus="DE0 0 urban central heat",
carrier="urban central geo thermal",
p_nom_extendable=True,
p_nom_max=row["potential [MW]"],
Expand Down Expand Up @@ -1564,10 +1564,28 @@ def drop_biomass(network):


def drop_urban_decentral_heat(network):
carrier = "urban decentral"
carrier = "urban decentral heat"

# Add urban decentral heat demand to urban central heat demand
for country in network.loads.loc[
network.loads.carrier==carrier, "bus"].str[:5]:

if f"{country} {carrier}" in network.loads_t.p_set.columns:
network.loads_t.p_set[f"{country} rural heat"] += (
network.loads_t.p_set[f"{country} {carrier}"]
)
else:
print(f"""No time series available for {country} {carrier}.
Using static p_set.""")

network.loads_t.p_set[f"{country} rural heat"] += (
network.loads.loc[f"{country} {carrier}", "p_set"]
)

# Drop componentents attached to urban decentral heat
for c in network.iterate_components():
network.mremove(c.name, c.df[c.df.index.str.contains(carrier)].index)
network.mremove(c.name, c.df[c.df.index.str.contains("urban decentral")].index)

return network


Expand Down Expand Up @@ -1659,81 +1677,120 @@ def execute():
) as stream:
data_config = yaml.safe_load(stream)

networks = pd.Series()

for i in range(0, len(data_config["scenario"]["planning_horizons"])):
nc_file = pd.Series(
f"elec_s_{data_config['scenario']['clusters'][0]}"
f"_l{data_config['scenario']['ll'][0]}"
f"_{data_config['scenario']['opts'][0]}"
f"_{data_config['scenario']['sector_opts'][0]}"
f"_{data_config['scenario']['planning_horizons'][i]}.nc"
)
networks = networks._append(nc_file)
if data_config["foresight"] == "myopic":

scn_path = pd.DataFrame(
index=["2025", "2030", "2035", "2045", "2050"],
columns=["prenetwork", "functions"],
)
print("Adjusting scenarios on the myopic pathway...")

for year in scn_path.index:
scn_path.at[year, "prenetwork"] = networks[
networks.str.contains(year)
].values
networks = pd.Series()

for year in ["2025", "2030", "2035"]:
scn_path.loc[year, "functions"] = [
for i in range(0, len(data_config["scenario"]["planning_horizons"])):
nc_file = pd.Series(
f"elec_s_{data_config['scenario']['clusters'][0]}"
f"_l{data_config['scenario']['ll'][0]}"
f"_{data_config['scenario']['opts'][0]}"
f"_{data_config['scenario']['sector_opts'][0]}"
f"_{data_config['scenario']['planning_horizons'][i]}.nc"
)
networks = networks._append(nc_file)

scn_path = pd.DataFrame(
index=["2025", "2030", "2035", "2045"],
columns=["prenetwork", "functions"],
)

for year in scn_path.index:
scn_path.at[year, "prenetwork"] = networks[
networks.str.contains(year)
].values

for year in ["2025", "2030", "2035"]:
scn_path.loc[year, "functions"] = [
drop_urban_decentral_heat,
update_electrical_timeseries_germany,
geothermal_district_heating,
h2_overground_stores,
drop_new_gas_pipelines,
]

scn_path.loc["2045", "functions"] = [
drop_biomass,
drop_urban_decentral_heat,
district_heating_shares,
update_heat_timeseries_germany,
update_electrical_timeseries_germany,
geothermal_district_heating,
h2_overground_stores,
drop_new_gas_pipelines,
drop_fossil_gas,
# rual_heat_technologies, #To be defined
]

scn_path.loc["2045", "functions"] = [
drop_biomass,
drop_urban_decentral_heat,
district_heating_shares,
update_heat_timeseries_germany,
update_electrical_timeseries_germany,
geothermal_district_heating,
h2_overground_stores,
drop_new_gas_pipelines,
drop_fossil_gas,
# rual_heat_technologies, #To be defined
]
network_path = (
Path(".")
/ "run-pypsa-eur"
/ "pypsa-eur"
/ "results"
/ data_config["run"]["name"]
/ "prenetworks"
)

scn_path.loc["2050", "functions"] = [
drop_biomass,
drop_urban_decentral_heat,
district_heating_shares,
update_heat_timeseries_germany,
update_electrical_timeseries_germany,
geothermal_district_heating,
h2_overground_stores,
drop_new_gas_pipelines,
drop_fossil_gas,
rual_heat_technologies,
]
for scn in scn_path.index:
path = network_path / scn_path.at[scn, "prenetwork"]
network = pypsa.Network(path)
network.year = int(scn)
for manipulator in scn_path.at[scn, "functions"]:
network = manipulator(network)
network.export_to_netcdf(path)

network_path = (
Path(".")
/ "run-pypsa-eur"
/ "pypsa-eur"
/ "results"
/ data_config["run"]["name"]
/ "prenetworks"
)

for scn in scn_path.index:
path = network_path / scn_path.at[scn, "prenetwork"]
network = pypsa.Network(path)
network.year = int(scn)
for manipulator in scn_path.at[scn, "functions"]:
network = manipulator(network)
network.export_to_netcdf(path)
elif ((data_config["foresight"] == "overnight")
& (int(data_config['scenario']['planning_horizons'][0]) > 2040)):

print("Adjusting overnight long-term scenario...")

network_path = (
Path(".")
/ "run-pypsa-eur"
/ "pypsa-eur"
/ "results"
/ data_config["run"]["name"]
/ "prenetworks"
/ f"elec_s_{data_config['scenario']['clusters'][0]}"
f"_l{data_config['scenario']['ll'][0]}"
f"_{data_config['scenario']['opts'][0]}"
f"_{data_config['scenario']['sector_opts'][0]}"
f"_{data_config['scenario']['planning_horizons'][0]}.nc"
)

network = pypsa.Network(network_path)

network = drop_biomass(network)

network = drop_urban_decentral_heat(network)

network = district_heating_shares(network)

network = update_heat_timeseries_germany(network)

network = update_electrical_timeseries_germany(network)

network = geothermal_district_heating(network)

network = h2_overground_stores(network)

network = drop_new_gas_pipelines(network)

network = drop_fossil_gas(network)

network = rual_heat_technologies(network)

network.export_to_netcdf(network_path)

else:
print(
f"""Adjustments on prenetworks are not implemented for
foresight option {data_config['foresight']} and
year int(data_config['scenario']['planning_horizons'][0].
Please check the pypsaeur.execute function.
"""
)

else:
print("Pypsa-eur is not executed due to the settings of egon-data")

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