add_electricity: Fix for choices of countries without any offshore or hydro
fixes #22.
This commit is contained in:
Jonas Hoersch
parent
31aefae93c
commit
f0a0a2531e
@ -178,6 +178,8 @@ def attach_wind_and_solar(n, costs):
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n.add("Carrier", name=tech)
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with xr.open_dataset(getattr(snakemake.input, 'profile_' + tech)) as ds:
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if ds.indexes['bus'].empty: continue
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suptech = tech.split('-', 2)[0]
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if suptech == 'offwind':
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underwater_fraction = ds['underwater_fraction'].to_pandas()
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@ -249,83 +251,88 @@ def attach_hydro(n, costs, ppl):
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has_pump=ppl.technology.str.contains('Pumped Storage')
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)
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country = ppl['bus'].map(n.buses.country)
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# distribute by p_nom in each country
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dist_key = ppl.loc[ppl.has_inflow, 'p_nom'].groupby(country).transform(normed)
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country = ppl['bus'].map(n.buses.country).rename("country")
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with xr.open_dataarray(snakemake.input.profile_hydro) as inflow:
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inflow_countries = pd.Index(country.loc[ppl.has_inflow].values)
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assert len(inflow_countries.unique().difference(inflow.indexes['countries'])) == 0, \
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"'{}' is missing inflow time-series for at least one country: {}".format(snakemake.input.profile_hydro, ", ".join(inflow_countries.unique().difference(inflow.indexes['countries'])))
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if ppl.has_inflow.any():
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dist_key = ppl.loc[ppl.has_inflow, 'p_nom'].groupby(country).transform(normed)
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inflow_t = (
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inflow.sel(countries=inflow_countries)
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.rename({'countries': 'name'})
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.assign_coords(name=ppl.index[ppl.has_inflow])
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.transpose('time', 'name')
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.to_pandas()
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.multiply(dist_key, axis=1)
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)
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with xr.open_dataarray(snakemake.input.profile_hydro) as inflow:
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inflow_countries = pd.Index(country.loc[ppl.has_inflow].values)
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assert len(inflow_countries.unique().difference(inflow.indexes['countries'])) == 0, (
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"'{}' is missing inflow time-series for at least one country: {}"
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.format(snakemake.input.profile_hydro, ", ".join(inflow_countries.unique().difference(inflow.indexes['countries'])))
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)
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inflow_t = (
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inflow.sel(countries=inflow_countries)
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.rename({'countries': 'name'})
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.assign_coords(name=ppl.index[ppl.has_inflow])
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.transpose('time', 'name')
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.to_pandas()
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.multiply(dist_key, axis=1)
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)
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if 'ror' in carriers:
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ror = ppl.loc[ppl.has_inflow & ~ ppl.has_store]
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n.madd("Generator", ror.index,
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carrier='ror',
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bus=ror['bus'],
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p_nom=ror['p_nom'],
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efficiency=costs.at['ror', 'efficiency'],
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capital_cost=costs.at['ror', 'capital_cost'],
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weight=ror['p_nom'],
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p_max_pu=(inflow_t.loc[:, ror.index]
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.divide(ror['p_nom'], axis=1)
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.where(lambda df: df<=1., other=1.)))
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if not ror.empty:
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n.madd("Generator", ror.index,
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carrier='ror',
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bus=ror['bus'],
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p_nom=ror['p_nom'],
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efficiency=costs.at['ror', 'efficiency'],
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capital_cost=costs.at['ror', 'capital_cost'],
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weight=ror['p_nom'],
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p_max_pu=(inflow_t.loc[:, ror.index]
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.divide(ror['p_nom'], axis=1)
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.where(lambda df: df<=1., other=1.)))
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if 'PHS' in carriers:
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phs = ppl.loc[ppl.has_store & ppl.has_pump]
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n.madd('StorageUnit', phs.index,
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carrier='PHS',
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bus=phs['bus'],
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p_nom=phs['p_nom'],
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capital_cost=costs.at['PHS', 'capital_cost'],
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max_hours=c['PHS_max_hours'],
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efficiency_store=np.sqrt(costs.at['PHS','efficiency']),
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efficiency_dispatch=np.sqrt(costs.at['PHS','efficiency']),
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cyclic_state_of_charge=True,
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inflow=inflow_t.loc[:, phs.index[phs.has_inflow]])
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if not phs.empty:
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n.madd('StorageUnit', phs.index,
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carrier='PHS',
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bus=phs['bus'],
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p_nom=phs['p_nom'],
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capital_cost=costs.at['PHS', 'capital_cost'],
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max_hours=c['PHS_max_hours'],
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efficiency_store=np.sqrt(costs.at['PHS','efficiency']),
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efficiency_dispatch=np.sqrt(costs.at['PHS','efficiency']),
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cyclic_state_of_charge=True,
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inflow=inflow_t.loc[:, phs.index[phs.has_inflow]])
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if 'hydro' in carriers:
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hydro = ppl.loc[ppl.has_store & ~ ppl.has_pump & ppl.has_inflow].join(country.rename('country'))
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hydro = ppl.loc[ppl.has_store & ~ ppl.has_pump & ppl.has_inflow].join(country)
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if not hydro.empty:
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hydro_max_hours = c.get('hydro_max_hours')
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if hydro_max_hours == 'energy_capacity_totals_by_country':
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hydro_e_country = pd.read_csv(snakemake.input.hydro_capacities, index_col=0)["E_store[TWh]"].clip(lower=0.2)*1e6
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hydro_max_hours_country = hydro_e_country / hydro.groupby('country').p_nom.sum()
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hydro_max_hours = hydro.country.map(hydro_e_country / hydro.groupby('country').p_nom.sum())
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elif hydro_max_hours == 'estimate_by_large_installations':
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hydro_capacities = pd.read_csv(snakemake.input.hydro_capacities, comment="#", na_values='-', index_col=0)
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estim_hydro_max_hours = hydro_capacities.e_stor / hydro_capacities.p_nom_discharge
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hydro_max_hours = c.get('hydro_max_hours')
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if hydro_max_hours == 'energy_capacity_totals_by_country':
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hydro_e_country = pd.read_csv(snakemake.input.hydro_capacities, index_col=0)["E_store[TWh]"].clip(lower=0.2)*1e6
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hydro_max_hours_country = hydro_e_country / hydro.groupby('country').p_nom.sum()
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hydro_max_hours = hydro.country.map(hydro_e_country / hydro.groupby('country').p_nom.sum())
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elif hydro_max_hours == 'estimate_by_large_installations':
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hydro_capacities = pd.read_csv(snakemake.input.hydro_capacities, comment="#", na_values='-', index_col=0)
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estim_hydro_max_hours = hydro_capacities.e_stor / hydro_capacities.p_nom_discharge
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missing_countries = (pd.Index(hydro['country'].unique())
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.difference(estim_hydro_max_hours.dropna().index))
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if not missing_countries.empty:
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logger.warning("Assuming max_hours=6 for hydro reservoirs in the countries: {}"
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.format(", ".join(missing_countries)))
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missing_countries = (pd.Index(hydro['country'].unique())
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.difference(estim_hydro_max_hours.dropna().index))
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if not missing_countries.empty:
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logger.warning("Assuming max_hours=6 for hydro reservoirs in the countries: {}"
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.format(", ".join(missing_countries)))
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hydro_max_hours = hydro['country'].map(estim_hydro_max_hours).fillna(6)
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hydro_max_hours = hydro['country'].map(estim_hydro_max_hours).fillna(6)
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n.madd('StorageUnit', hydro.index, carrier='hydro',
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bus=hydro['bus'],
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p_nom=hydro['p_nom'],
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max_hours=hydro_max_hours,
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capital_cost=(costs.at['hydro', 'capital_cost']
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if c.get('hydro_capital_cost') else 0.),
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marginal_cost=costs.at['hydro', 'marginal_cost'],
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p_max_pu=1., # dispatch
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p_min_pu=0., # store
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efficiency_dispatch=costs.at['hydro', 'efficiency'],
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efficiency_store=0.,
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cyclic_state_of_charge=True,
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inflow=inflow_t.loc[:, hydro.index])
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n.madd('StorageUnit', hydro.index, carrier='hydro',
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bus=hydro['bus'],
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p_nom=hydro['p_nom'],
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max_hours=hydro_max_hours,
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capital_cost=(costs.at['hydro', 'capital_cost']
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if c.get('hydro_capital_cost') else 0.),
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marginal_cost=costs.at['hydro', 'marginal_cost'],
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p_max_pu=1., # dispatch
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p_min_pu=0., # store
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efficiency_dispatch=costs.at['hydro', 'efficiency'],
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efficiency_store=0.,
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cyclic_state_of_charge=True,
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inflow=inflow_t.loc[:, hydro.index])
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def attach_extendable_generators(n, costs, ppl):
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