def attach_OPSD_renewables(n):
available = ['DE', 'FR', 'PL', 'CH', 'DK', 'CZ', 'SE', 'GB']
tech_map = {'Onshore': 'onwind', 'Offshore': 'offwind', 'Solar': 'solar'}
countries = set(available) & set(n.buses.country)
techs = snakemake.config['electricity'].get('renewable_capacities_from_OPSD', [])
tech_map = {k: v for k, v in tech_map.items() if v in techs}
if not tech_map:
return
logger.info(f'Using OPSD renewable capacities in {", ".join(countries)} '
f'for technologies {", ".join(tech_map.values())}.')
df = pd.concat([pm.data.OPSD_VRE_country(c) for c in countries])
technology_b = ~df.Technology.isin(['Onshore', 'Offshore'])
df['Fueltype'] = df.Fueltype.where(technology_b, df.Technology)
df = df.query('Fueltype in @tech_map').powerplant.convert_country_to_alpha2()
for fueltype, carrier_like in tech_map.items():
gens = n.generators[lambda df: df.carrier.str.contains(carrier_like)]
buses = n.buses.loc[gens.bus.unique()]
gens_per_bus = gens.groupby('bus').p_nom.count()
caps = map_country_bus(df.query('Fueltype == @fueltype'), buses)
caps = caps.groupby(['bus']).Capacity.sum()
caps = caps / gens_per_bus.reindex(caps.index, fill_value=1)
n.generators.p_nom.update(gens.bus.map(caps).dropna())
def attach_OPSD_renewables(n):
available = ["DE", "FR", "PL", "CH", "DK", "CZ", "SE", "GB"]
tech_map = {"Onshore": "onwind", "Offshore": "offwind", "Solar": "solar"}
countries = set(available) & set(n.buses.country)
techs = snakemake.config["electricity"].get(
"renewable_capacities_from_OPSD", [])
tech_map = {k: v for k, v in tech_map.items() if v in techs}
if not tech_map:
return
logger.info(f'Using OPSD renewable capacities in {", ".join(countries)} '
f'for technologies {", ".join(tech_map.values())}.')
df = pd.concat([pm.data.OPSD_VRE_country(c) for c in countries])
technology_b = ~df.Technology.isin(["Onshore", "Offshore"])
df["Fueltype"] = df.Fueltype.where(technology_b, df.Technology)
df = df.query(
"Fueltype in @tech_map").powerplant.convert_country_to_alpha2()
for fueltype, carrier_like in tech_map.items():
gens = n.generators[lambda df: df.carrier.str.contains(carrier_like)]
buses = n.buses.loc[gens.bus.unique()]
gens_per_bus = gens.groupby("bus").p_nom.count()
caps = map_country_bus(df.query("Fueltype == @fueltype"), buses)
caps = caps.groupby(["bus"]).Capacity.sum()
caps = caps / gens_per_bus.reindex(caps.index, fill_value=1)
n.generators.p_nom.update(gens.bus.map(caps).dropna())
n.generators.p_nom_min.update(gens.bus.map(caps).dropna())