Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1.
Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
This commit is contained in:
martavp
parent
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commit
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183
scripts/add_brownfield.py
Executable file
183
scripts/add_brownfield.py
Executable file
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# coding: utf-8
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import logging
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logger = logging.getLogger(__name__)
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import pandas as pd
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idx = pd.IndexSlice
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import numpy as np
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import scipy as sp
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import xarray as xr
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import re, os
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from six import iteritems, string_types
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import pypsa
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import yaml
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import pytz
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from vresutils.costdata import annuity
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from add_existing_baseyear import add_power_capacities_installed_before_baseyear
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from add_existing_baseyear import add_heating_capacities_installed_before_baseyear
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from add_existing_baseyear import prepare_costs
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#First tell PyPSA that links can have multiple outputs by
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#overriding the component_attrs. This can be done for
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#as many buses as you need with format busi for i = 2,3,4,5,....
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#See https://pypsa.org/doc/components.html#link-with-multiple-outputs-or-inputs
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override_component_attrs = pypsa.descriptors.Dict({k : v.copy() for k,v in pypsa.components.component_attrs.items()})
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override_component_attrs["Link"].loc["bus2"] = ["string",np.nan,np.nan,"2nd bus","Input (optional)"]
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override_component_attrs["Link"].loc["bus3"] = ["string",np.nan,np.nan,"3rd bus","Input (optional)"]
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override_component_attrs["Link"].loc["efficiency2"] = ["static or series","per unit",1.,"2nd bus efficiency","Input (optional)"]
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override_component_attrs["Link"].loc["efficiency3"] = ["static or series","per unit",1.,"3rd bus efficiency","Input (optional)"]
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override_component_attrs["Link"].loc["p2"] = ["series","MW",0.,"2nd bus output","Output"]
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override_component_attrs["Link"].loc["p3"] = ["series","MW",0.,"3rd bus output","Output"]
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def prepare_costs():
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#set all asset costs and other parameters
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#costs = pd.read_csv(snakemake.input.costs,index_col=list(range(3))).sort_index()
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costs = pd.read_csv(snakemake.input.costs,index_col=list(range(2))).sort_index()
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#correct units to MW and EUR
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costs.loc[costs.unit.str.contains("/kW"),"value"]*=1e3
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costs.loc[costs.unit.str.contains("USD"),"value"]*=snakemake.config['costs']['USD2013_to_EUR2013']
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#cost_year = snakemake.config['costs']['year']
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#costs = costs.loc[idx[:,cost_year,:],"value"].unstack(level=2).groupby(level="technology").sum(min_count=1)
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costs = costs.loc[:, "value"].unstack(level=1).groupby("technology").sum()
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costs = costs.fillna({"CO2 intensity" : 0,
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"FOM" : 0,
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"VOM" : 0,
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"discount rate" : snakemake.config['costs']['discountrate'],
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"efficiency" : 1,
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"fuel" : 0,
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"investment" : 0,
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"lifetime" : 25
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})
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costs["fixed"] = [(annuity(v["lifetime"],v["discount rate"])+v["FOM"]/100.)*v["investment"]*Nyears for i,v in costs.iterrows()]
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return costs
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def add_brownfield(n,n_p):
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print("adding brownfield")
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previous_timestep=snakemake.config['scenario']['planning_horizons'][snakemake.config['scenario']['planning_horizons'].index(year)-1]
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previous_timesteps=snakemake.config['scenario']['planning_horizons'][0:snakemake.config['scenario']['planning_horizons'].index(year)]
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#add generators from previous step
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n_p.mremove("Generator", [index for index in n_p.generators.index.to_list() if '<'+snakemake.config['scenario']['planning_horizons'][0] in index])
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n_p.mremove("Generator", [index for index in n_p.generators.index.to_list() if 'ror' in index])
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n_p.generators.index=np.where(n_p.generators.index.str[-4:].isin(previous_timesteps)==False,
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n_p.generators.index + '-' + previous_timestep,
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n_p.generators.index)
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n.madd("Generator",
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n_p.generators.index,
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bus=n_p.generators.bus,
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carrier=n_p.generators.carrier,
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p_nom=n_p.generators.p_nom_opt,
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marginal_cost=n_p.generators.marginal_cost,
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capital_cost=n_p.generators.capital_cost,
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efficiency=n_p.generators.efficiency,
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p_max_pu=n_p.generators_t.p_max_pu)
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#add stores from previous steps
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n_p.mremove("Store", ['co2 atmosphere', 'co2 stored', 'EU gas Store'] )
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n_p.stores.index=np.where(n_p.stores.index.str[-4:].isin(previous_timesteps)==False,
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n_p.stores.index + '-' + previous_timestep,
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n_p.stores.index)
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n.madd("Store",
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n_p.stores.index,
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bus=n_p.stores.bus,
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carrier=n_p.stores.carrier,
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e_nom=n_p.stores.e_nom_opt,
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e_cyclic=True,
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capital_cost=n_p.stores.capital_cost)
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## add links from previous steps
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# TODO: add_chp_constraint() in solve_network needs to be adjusted
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n_p.mremove("Link", [index for index in n_p.links.index.to_list() if '<'+snakemake.config['scenario']['planning_horizons'][0] in index])
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n_p.mremove("Link", [index for index in n_p.links.index.to_list() if 'CHP' in index])
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n_p.links.index=np.where(n_p.links.index.str[-4:].isin(previous_timesteps)==False,
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n_p.links.index + '-' + previous_timestep,
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n_p.links.index)
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n.madd("Link",
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n_p.links.index,
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bus0=n_p.links.bus0,
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bus1=n_p.links.bus1,
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bus2=n_p.links.bus2,
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carrier=n_p.links.carrier,
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p_nom=n_p.links.p_nom_opt,
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marginal_cost=n_p.links.marginal_cost,
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capital_cost=n_p.links.capital_cost,
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efficiency=n_p.links.efficiency,
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efficiency2=n_p.links.efficiency2)
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if __name__ == "__main__":
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# Detect running outside of snakemake and mock snakemake for testing
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if 'snakemake' not in globals():
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from vresutils.snakemake import MockSnakemake
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snakemake = MockSnakemake(
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wildcards=dict(network='elec', simpl='', clusters='37', lv='1.0',
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sector_opts='Co2L0-168H-T-H-B-I-solar3-dist1',
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co2_budget_name='go',
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planning_horizons='2050'),
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input=dict(network='pypsa-eur-sec/results/test/prenetworks/{network}_s{simpl}_{clusters}_lv{lv}__{sector_opts}_{co2_budget_name}_{planning_horizons}.nc',
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network_p='pypsa-eur-sec/results/test/postnetworks/{network}_s{simpl}_{clusters}_lv{lv}__{sector_opts}_{co2_budget_name}_2040.nc',
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costs='pypsa-eur-sec/data/costs/costs_{planning_horizons}.csv',
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cop_air_total="pypsa-eur-sec/resources/cop_air_total_{network}_s{simpl}_{clusters}.nc",
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cop_soil_total="pypsa-eur-sec/resources/cop_soil_total_{network}_s{simpl}_{clusters}.nc"),
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output=['pypsa-eur-sec/results/test/prenetworks_bf/{network}_s{simpl}_{clusters}_lv{lv}__{sector_opts}_{planning_horizons}.nc']
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)
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import yaml
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with open('config.yaml') as f:
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snakemake.config = yaml.load(f)
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print(snakemake.input.network_p)
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logging.basicConfig(level=snakemake.config['logging_level'])
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options = snakemake.config["sector"]
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opts = snakemake.wildcards.sector_opts.split('-')
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year=snakemake.wildcards.planning_horizons
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n = pypsa.Network(snakemake.input.network,
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override_component_attrs=override_component_attrs)
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n_p = pypsa.Network(snakemake.input.network_p,
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override_component_attrs=override_component_attrs)
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add_brownfield(n,n_p)
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Nyears = n.snapshot_weightings.sum()/8760.
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costs = prepare_costs()
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baseyear=snakemake.config['scenario']["planning_horizons"][0]
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add_power_capacities_installed_before_baseyear(n, year, baseyear, costs) # only the capacities with YearDecomissioning < year are added
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if "H" in opts:
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time_dep_hp_cop = options["time_dep_hp_cop"]
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ashp_cop = xr.open_dataarray(snakemake.input.cop_air_total).T.to_pandas().reindex(index=n.snapshots)
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gshp_cop = xr.open_dataarray(snakemake.input.cop_soil_total).T.to_pandas().reindex(index=n.snapshots)
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add_heating_capacities_installed_before_baseyear(n, year, baseyear, ashp_cop, gshp_cop, time_dep_hp_cop, costs) # only the capacities with YearDecomissioning < year are added
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n.export_to_netcdf(snakemake.output[0])
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394
scripts/add_existing_baseyear.py
Executable file
394
scripts/add_existing_baseyear.py
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# coding: utf-8
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import logging
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logger = logging.getLogger(__name__)
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import pandas as pd
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idx = pd.IndexSlice
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import numpy as np
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import scipy as sp
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import xarray as xr
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import re, os
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from six import iteritems, string_types
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import pypsa
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import yaml
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import pytz
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from vresutils.costdata import annuity
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#First tell PyPSA that links can have multiple outputs by
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#overriding the component_attrs. This can be done for
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#as many buses as you need with format busi for i = 2,3,4,5,....
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#See https://pypsa.org/doc/components.html#link-with-multiple-outputs-or-inputs
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override_component_attrs = pypsa.descriptors.Dict({k : v.copy() for k,v in pypsa.components.component_attrs.items()})
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override_component_attrs["Link"].loc["bus2"] = ["string",np.nan,np.nan,"2nd bus","Input (optional)"]
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override_component_attrs["Link"].loc["bus3"] = ["string",np.nan,np.nan,"3rd bus","Input (optional)"]
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override_component_attrs["Link"].loc["efficiency2"] = ["static or series","per unit",1.,"2nd bus efficiency","Input (optional)"]
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override_component_attrs["Link"].loc["efficiency3"] = ["static or series","per unit",1.,"3rd bus efficiency","Input (optional)"]
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override_component_attrs["Link"].loc["p2"] = ["series","MW",0.,"2nd bus output","Output"]
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override_component_attrs["Link"].loc["p3"] = ["series","MW",0.,"3rd bus output","Output"]
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def prepare_costs():
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#set all asset costs and other parameters
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#costs = pd.read_csv(snakemake.input.costs,index_col=list(range(3))).sort_index()
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costs = pd.read_csv(snakemake.input.costs,index_col=list(range(2))).sort_index()
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#correct units to MW and EUR
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costs.loc[costs.unit.str.contains("/kW"),"value"]*=1e3
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costs.loc[costs.unit.str.contains("USD"),"value"]*=snakemake.config['costs']['USD2013_to_EUR2013']
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#cost_year = snakemake.config['costs']['year']
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#costs = costs.loc[idx[:,cost_year,:],"value"].unstack(level=2).groupby(level="technology").sum(min_count=1)
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costs = costs.loc[:, "value"].unstack(level=1).groupby("technology").sum()
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costs = costs.fillna({"CO2 intensity" : 0,
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"FOM" : 0,
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"VOM" : 0,
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"discount rate" : snakemake.config['costs']['discountrate'],
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"efficiency" : 1,
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"fuel" : 0,
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"investment" : 0,
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"lifetime" : 25
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})
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costs["fixed"] = [(annuity(v["lifetime"],v["discount rate"])+v["FOM"]/100.)*v["investment"]*Nyears for i,v in costs.iterrows()]
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return costs
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def add_power_capacities_installed_before_baseyear(n, year, baseyear, costs):
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"""
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Parameters
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----------
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n : network
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year : capacity that fulfills YearDecomissioning < year is added
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baseyear : capacity name will be e.g. "solar <baseyear"
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this allows adding the solar capacity that was installed before
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2020 (baseyear) and is still alive in 2030 (year)
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costs : to read lifetime to estimate YearDecomissioning
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"""
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print("adding power capacities installed before baseyear")
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### add conventional capacities using 'powerplants.csv'
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df_agg = pd.read_csv('../pypsa-eur/resources/powerplants.csv', index_col=0)
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rename_fuel = {'Hard Coal':'coal',
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'Lignite':'lignite',
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'Nuclear':'nuclear',
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'Oil':'oil',
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'OCGT':'OCGT',
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'CCGT':'CCGT',
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'Natural Gas':'gas',}
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fueltype_to_drop = ['Hydro',
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'Wind',
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'Solar',
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'Geothermal',
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'Bioenergy',
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'Waste',
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'Other',
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'CCGT, Thermal']
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technology_to_drop = ['Pv',
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'Storage Technologies']
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df_agg.drop(df_agg.index[df_agg.Fueltype.isin(fueltype_to_drop)],inplace=True)
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df_agg.drop(df_agg.index[df_agg.Technology.isin(technology_to_drop)],inplace=True)
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df_agg.Fueltype = df_agg.Fueltype.map(rename_fuel)
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# add existing solar and wind capacities
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# source: https://www.irena.org/Statistics/Download-Data
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cc = pd.read_csv('data/Country_codes.csv', sep=',', index_col=-1)
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name_to_2code = dict(zip(cc['Country'].tolist(),
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cc['2 letter code (ISO-3166-2)'].tolist()))
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for tech in ['solar', 'onwind', 'offwind']:
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df = pd.read_csv('data/existing_infrastructure/{}_capacity_IRENA.csv'.format(tech),
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sep=',', index_col=0)
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df.rename(index={'Czechia':'Czech Republic',
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'UK':'United Kingdom',
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'Bosnia Herzg':'Bosnia Herzegovina',
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'North Macedonia': 'Macedonia'}, inplace=True)
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df.rename(index=lambda country : name_to_2code[country], inplace=True)
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# calculate yearly differences
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df.insert(loc=0, value=.0, column='1999')
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df = df.diff(axis=1).drop('1999', axis=1)
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df = df.clip(lower=0)
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df.replace(to_replace=0.0, value=np.nan, inplace=True)
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for year in df.columns:
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for country in df.index:
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if df.notnull().loc[country,year]:
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df_agg = df_agg.append({'Fueltype':tech,
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'Country':country,
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'Capacity':df.loc[country,year],
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'YearCommissioned':int(year),
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'YearDecommissioning':int(float(year)+costs.at[tech, 'lifetime'])},
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ignore_index=True)
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# powerplants already include an estimated decommissining year wich has been
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# calculated based on pm config, check if we want to make this calculation more
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# transparent, e.g., by loading lifetime assumptions from costs.csv into pm config
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# check how pm is dealing with retrofitting
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# pm.get_config()['fuel_to_lifetime']
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# index = df_agg.Fueltype.map(lf)+df_agg.YearCommissioned > 2020
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index=df_agg.YearDecommissioning > int(year)
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df = df_agg[index].pivot_table(index='Country', columns='Fueltype',
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values='Capacity', aggfunc='sum')
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nodes=set([node[0:2] for node in n.buses.index[n.buses.carrier == "AC"]])
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for carrier in ['coal', 'oil', 'uranium']:
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n.add("Bus",
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"EU " + carrier,
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carrier=carrier)
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for node in nodes:
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#if a country has more than one node, selects the first one
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bus_selected=[bus for bus in n.buses.index[n.buses.carrier == "AC"] if bus[0:2]==node][0]
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for generator,carrier in [("OCGT","gas"),
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("CCGT", "gas"),
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("coal", "coal"),
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("oil","oil"),
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("nuclear","uranium")]:
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if node in df.index and not np.isnan(df.loc[node, generator]):
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n.add("Link",
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bus_selected + " " + generator +" <" + baseyear,
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bus0="EU " + carrier,
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bus1=bus_selected,
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bus2="co2 atmosphere",
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marginal_cost=costs.at[generator,'efficiency']*costs.at[generator,'VOM'], #NB: VOM is per MWel
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capital_cost=costs.at[generator,'efficiency']*costs.at[generator,'fixed'], #NB: fixed cost is per MWel
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p_nom=df.loc[node, generator],
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efficiency=costs.at[generator,'efficiency'],
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efficiency2=costs.at[carrier,'CO2 intensity'])
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for generator in ['solar', 'onwind', 'offwind']:
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try:
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if not np.isnan(df.loc[node, generator]):
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if generator =='offwind':
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p_max_pu=n.generators_t.p_max_pu[bus_selected + ' offwind-ac']
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else:
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p_max_pu=n.generators_t.p_max_pu[bus_selected + ' ' + generator]
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n.add("Generator",
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bus_selected + ' ' + generator +" <"+ baseyear,
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bus=bus_selected,
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carrier=generator,
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p_nom=df.loc[node, generator],
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marginal_cost=costs.at[generator,'VOM'],
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capital_cost=costs.at[generator,'fixed'],
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efficiency=costs.at[generator, 'efficiency'],
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p_max_pu=p_max_pu)
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except:
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print("No capacity installed before base year of " + generator + " is alive in node " + node)
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# delete generators if their lifetime is over and p_nom=0
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n.mremove("Generator", [index for index in n.generators.index.to_list() if '<'+baseyear in index and n.generators.p_nom[index]==0])
|
||||
n.mremove("Link", [index for index in n.links.index.to_list() if '<'+baseyear in index and n.links.p_nom[index]==0])
|
||||
|
||||
def add_heating_capacities_installed_before_baseyear(n, year, baseyear, ashp_cop, gshp_cop, time_dep_hp_cop, costs):
|
||||
|
||||
"""
|
||||
|
||||
Parameters
|
||||
----------
|
||||
n : network
|
||||
year : capacity that fulfills YearDecomissioning < year is added
|
||||
baseyear : capacity name will be e.g. "gas boiler <baseyear"
|
||||
this allows adding the gas boiler capacity that was installed
|
||||
before 2020 (baseyear) and is still alive in 2030 (year)
|
||||
|
||||
linear decomissioning of heating capacities from 2020 to 2045 is
|
||||
currently assumed
|
||||
|
||||
heating capacities split between residential and services proportional
|
||||
to heating load in both
|
||||
50% capacities in rural busess 50% in urban buses
|
||||
"""
|
||||
print("adding heating capacities installed before baseyear")
|
||||
|
||||
# Add existing heating capacities, data comes from the study
|
||||
# "Mapping and analyses of the current and future (2020 - 2030)
|
||||
# heating/cooling fuel deployment (fossil/renewables) "
|
||||
# https://ec.europa.eu/energy/studies/mapping-and-analyses-current-and-future-2020-2030-heatingcooling-fuel-deployment_en?redir=1
|
||||
# file: "WP2_DataAnnex_1_BuildingTechs_ForPublication_201603.xls" -> "existing_heating_raw.csv".
|
||||
|
||||
# retrieve existing heating capacities
|
||||
techs = ['gas boiler',
|
||||
'oil boiler',
|
||||
'resistive heater',
|
||||
'air heat pump',
|
||||
'ground heat pump']
|
||||
df = pd.read_csv('data/existing_infrastructure/existing_heating_raw.csv',
|
||||
index_col=0,
|
||||
header=0)
|
||||
# data for Albania, Montenegro and Macedonia not included in database
|
||||
df.loc['Albania']=np.nan
|
||||
df.loc['Montenegro']=np.nan
|
||||
df.loc['Macedonia']=np.nan
|
||||
df.fillna(0, inplace=True)
|
||||
df *= 1e3 # GW to MW
|
||||
|
||||
cc = pd.read_csv('data/Country_codes.csv', sep=',', index_col=-1)
|
||||
name_to_2code = dict(zip(cc['Country'].tolist(),
|
||||
cc['2 letter code (ISO-3166-2)'].tolist()))
|
||||
df.rename(index=lambda country : name_to_2code[country], inplace=True)
|
||||
|
||||
|
||||
# coal and oil boilers are assimilated to oil boilers
|
||||
df['oil boiler'] =df['oil boiler'] + df['coal boiler']
|
||||
df.drop(['coal boiler'], axis=1, inplace=True)
|
||||
|
||||
# rename countries with network buses names
|
||||
nodes_elec=[node for node in n.buses.index[n.buses.carrier == "AC"]]
|
||||
name_to_busname={ index : [node for node in nodes_elec if index in node][0] for index in df.index}
|
||||
df.rename(index=lambda country : name_to_busname[country], inplace=True)
|
||||
|
||||
# split existing capacities between residential and services
|
||||
# proportional to energy demand
|
||||
ratio_residential=pd.Series([(n.loads_t.p_set.sum()['{} residential rural heat'.format(node)] /
|
||||
(n.loads_t.p_set.sum()['{} residential rural heat'.format(node)] +
|
||||
n.loads_t.p_set.sum()['{} services rural heat'.format(node)] ))
|
||||
for node in df.index], index=df.index)
|
||||
|
||||
for tech in techs:
|
||||
df['residential ' + tech] = df[tech]*ratio_residential
|
||||
df['services ' + tech] = df[tech]*(1-ratio_residential)
|
||||
|
||||
nodes={}
|
||||
p_nom={}
|
||||
for name in ["residential rural",
|
||||
"services rural",
|
||||
"residential urban decentral",
|
||||
"services urban decentral",
|
||||
"urban central"]:
|
||||
|
||||
name_type = "central" if name == "urban central" else "decentral"
|
||||
nodes[name] = pd.Index([index[0:5] for index in n.buses.index[n.buses.index.str.contains(name) & n.buses.index.str.contains('heat')]])
|
||||
heat_pump_type = "air" if "urban" in name else "ground"
|
||||
heat_type= "residential" if "residential" in name else "services"
|
||||
|
||||
if name == "urban central":
|
||||
p_nom[name]=df['air heat pump'][nodes[name]]
|
||||
else:
|
||||
p_nom[name] = df['{} {} heat pump'.format(heat_type, heat_pump_type)][nodes[name]]
|
||||
|
||||
# Add heat pumps
|
||||
costs_name = "{} {}-sourced heat pump".format("decentral", heat_pump_type)
|
||||
|
||||
|
||||
cop = {"air" : ashp_cop, "ground" : gshp_cop}
|
||||
efficiency = cop[heat_pump_type][nodes[name]] if time_dep_hp_cop else costs.at[costs_name,'efficiency']
|
||||
|
||||
n.madd("Link",
|
||||
nodes[name],
|
||||
suffix=" {} {} heat pump <{}".format(name,heat_pump_type, baseyear),
|
||||
bus0=nodes[name],
|
||||
bus1=nodes[name] + " " + name + " heat",
|
||||
carrier="{} {} heat pump".format(name,heat_pump_type),
|
||||
efficiency=efficiency,
|
||||
capital_cost=costs.at[costs_name,'efficiency']*costs.at[costs_name,'fixed'],
|
||||
p_nom=p_nom[name]*max(0,(2045-int(year))/25)) #decomissioning happens lineary from now to 25 years lter
|
||||
|
||||
# add resistive heater, gas boilers and oil boilers
|
||||
# (50% capacities to rural buses, 50% to urban buses)
|
||||
n.madd("Link",
|
||||
nodes[name],
|
||||
suffix= " " + name + " resistive heater <{}".format(baseyear),
|
||||
bus0=nodes[name],
|
||||
bus1=nodes[name] + " " + name + " heat",
|
||||
carrier=name + " resistive heater",
|
||||
efficiency=costs.at[name_type + ' resistive heater','efficiency'],
|
||||
capital_cost=costs.at[name_type + ' resistive heater','efficiency']*costs.at[name_type + ' resistive heater','fixed'],
|
||||
p_nom=0.5*df['{} resistive heater'.format(heat_type)][nodes[name]]*max(0,(2045-int(year))/25))
|
||||
|
||||
n.madd("Link",
|
||||
nodes[name],
|
||||
suffix= " " + name + " gas boiler <{}".format(baseyear),
|
||||
bus0=["EU gas"]*len(nodes[name]),
|
||||
bus1=nodes[name] + " " + name + " heat",
|
||||
bus2="co2 atmosphere",
|
||||
carrier=name + " gas boiler",
|
||||
efficiency=costs.at[name_type + ' gas boiler','efficiency'],
|
||||
efficiency2=costs.at['gas','CO2 intensity'],
|
||||
capital_cost=costs.at[name_type + ' gas boiler','efficiency']*costs.at[name_type + ' gas boiler','fixed'],
|
||||
p_nom=0.5*df['{} gas boiler'.format(heat_type)][nodes[name]]*max(0,(2045-int(year))/25))
|
||||
|
||||
n.madd("Link",
|
||||
nodes[name],
|
||||
suffix=" " + name + " oil boiler <{}".format(baseyear),
|
||||
bus0=["EU oil"]*len(nodes[name]),
|
||||
bus1=nodes[name] + " " + name + " heat",
|
||||
bus2="co2 atmosphere",
|
||||
carrier=name + " oil boiler",
|
||||
efficiency=costs.at['decentral oil boiler','efficiency'],
|
||||
efficiency2=costs.at['oil','CO2 intensity'],
|
||||
capital_cost=costs.at['decentral oil boiler','efficiency']*costs.at['decentral oil boiler','fixed'],
|
||||
p_nom=0.5*df['{} oil boiler'.format(heat_type)][nodes[name]]*max(0,(2045-int(year))/25))
|
||||
|
||||
# delete links with p_nom=nan corresponding to extra nodes in country
|
||||
n.mremove("Link", [index for index in n.links.index.to_list() if baseyear in index and np.isnan(n.links.p_nom[index])])
|
||||
|
||||
# delete links if their lifetime is over and p_nom=0
|
||||
n.mremove("Link", [index for index in n.links.index.to_list() if '<'+baseyear in index and n.links.p_nom[index]==0])
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Detect running outside of snakemake and mock snakemake for testing
|
||||
if 'snakemake' not in globals():
|
||||
from vresutils.snakemake import MockSnakemake
|
||||
snakemake = MockSnakemake(
|
||||
wildcards=dict(network='elec', simpl='', clusters='37', lv='1.0',
|
||||
sector_opts='Co2L0-168H-T-H-B-I-solar3-dist1',
|
||||
planning_horizons='2020'),
|
||||
input=dict(network='pypsa-eur-sec/results/test/prenetworks/{network}_s{simpl}_{clusters}_lv{lv}__{sector_opts}_{planning_horizons}.nc',
|
||||
costs='pypsa-eur-sec/data/costs/costs_{planning_horizons}.csv',
|
||||
cop_air_total="pypsa-eur-sec/resources/cop_air_total_{network}_s{simpl}_{clusters}.nc",
|
||||
cop_soil_total="pypsa-eur-sec/resources/cop_soil_total_{network}_s{simpl}_{clusters}.nc"),
|
||||
output=['pypsa-eur-sec/results/test/prenetworks_bf/{network}_s{simpl}_{clusters}_lv{lv}__{sector_opts}_{planning_horizons}.nc'],
|
||||
)
|
||||
import yaml
|
||||
with open('config.yaml') as f:
|
||||
snakemake.config = yaml.load(f)
|
||||
|
||||
|
||||
logging.basicConfig(level=snakemake.config['logging_level'])
|
||||
|
||||
options = snakemake.config["sector"]
|
||||
opts = snakemake.wildcards.sector_opts.split('-')
|
||||
|
||||
baseyear= snakemake.config['scenario']["planning_horizons"][0]
|
||||
|
||||
n = pypsa.Network(snakemake.input.network,
|
||||
override_component_attrs=override_component_attrs)
|
||||
|
||||
Nyears = n.snapshot_weightings.sum()/8760.
|
||||
costs = prepare_costs()
|
||||
|
||||
add_power_capacities_installed_before_baseyear(n, baseyear, baseyear, costs)
|
||||
|
||||
if "H" in opts:
|
||||
time_dep_hp_cop = options["time_dep_hp_cop"]
|
||||
ashp_cop = xr.open_dataarray(snakemake.input.cop_air_total).T.to_pandas().reindex(index=n.snapshots)
|
||||
gshp_cop = xr.open_dataarray(snakemake.input.cop_soil_total).T.to_pandas().reindex(index=n.snapshots)
|
||||
add_heating_capacities_installed_before_baseyear(n, baseyear, baseyear, ashp_cop, gshp_cop, time_dep_hp_cop, costs)
|
||||
|
||||
n.export_to_netcdf(snakemake.output[0])
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user