pre-commit formatting [no ci]
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@ -148,7 +148,11 @@ def add_everywhere_powerplants(ppl, substations, everywhere_powerplants):
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def replace_natural_gas_technology(df):
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def replace_natural_gas_technology(df):
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mapping = {"Steam Turbine": "CCGT", "Combustion Engine": "OCGT", "Not Found": "CCGT"}
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mapping = {
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"Steam Turbine": "CCGT",
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"Combustion Engine": "OCGT",
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"Not Found": "CCGT",
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}
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tech = df.Technology.replace(mapping).fillna("CCGT")
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tech = df.Technology.replace(mapping).fillna("CCGT")
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return df.Technology.mask(df.Fueltype == "Natural Gas", tech)
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return df.Technology.mask(df.Fueltype == "Natural Gas", tech)
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@ -973,7 +973,9 @@ def insert_electricity_distribution_grid(n, costs):
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.get("electricity distribution grid", {})
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.get("electricity distribution grid", {})
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.get("efficiency_static")
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.get("efficiency_static")
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):
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):
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logger.info(f"Deducting distribution losses from electricity demand: {100*(1-efficiency)}%")
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logger.info(
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f"Deducting distribution losses from electricity demand: {100*(1-efficiency)}%"
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)
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n.loads_t.p_set.loc[:, n.loads.carrier == "electricity"] *= efficiency
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n.loads_t.p_set.loc[:, n.loads.carrier == "electricity"] *= efficiency
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# this catches regular electricity load and "industry electricity" and
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# this catches regular electricity load and "industry electricity" and
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@ -531,28 +531,39 @@ def add_CCL_constraints(n, config):
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agg_p_nom_limits: data/agg_p_nom_minmax.csv
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agg_p_nom_limits: data/agg_p_nom_minmax.csv
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"""
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"""
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agg_p_nom_minmax = pd.read_csv(
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agg_p_nom_minmax = pd.read_csv(
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config["solving"]["agg_p_nom_limits"]["file"],
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config["solving"]["agg_p_nom_limits"]["file"], index_col=[0, 1], header=[0, 1]
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index_col=[0, 1], header=[0, 1]
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)[snakemake.wildcards.planning_horizons]
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)[snakemake.wildcards.planning_horizons]
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logger.info("Adding generation capacity constraints per carrier and country")
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logger.info("Adding generation capacity constraints per carrier and country")
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p_nom = n.model["Generator-p_nom"]
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p_nom = n.model["Generator-p_nom"]
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gens = n.generators.query("p_nom_extendable").rename_axis(index="Generator-ext")
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gens = n.generators.query("p_nom_extendable").rename_axis(index="Generator-ext")
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if config["solving"]["agg_p_nom_limits"]["agg_offwind"]:
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if config["solving"]["agg_p_nom_limits"]["agg_offwind"]:
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rename_offwind = {"offwind-ac": "offwind-all", "offwind-dc": "offwind-all", "offwind": "offwind-all"}
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rename_offwind = {
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"offwind-ac": "offwind-all",
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"offwind-dc": "offwind-all",
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"offwind": "offwind-all",
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}
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gens = gens.replace(rename_offwind)
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gens = gens.replace(rename_offwind)
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grouper = pd.concat([gens.bus.map(n.buses.country), gens.carrier], axis=1)
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grouper = pd.concat([gens.bus.map(n.buses.country), gens.carrier], axis=1)
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lhs = p_nom.groupby(grouper).sum().rename(bus="country")
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lhs = p_nom.groupby(grouper).sum().rename(bus="country")
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if config["solving"]["agg_p_nom_limits"]["include_existing"]:
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if config["solving"]["agg_p_nom_limits"]["include_existing"]:
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gens_cst = n.generators.query("~p_nom_extendable").rename_axis(index="Generator-cst")
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gens_cst = n.generators.query("~p_nom_extendable").rename_axis(
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index="Generator-cst"
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)
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gens_cst = gens_cst[
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gens_cst = gens_cst[
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(gens_cst["build_year"] + gens_cst["lifetime"]) >= int(snakemake.wildcards.planning_horizons)]
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(gens_cst["build_year"] + gens_cst["lifetime"])
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>= int(snakemake.wildcards.planning_horizons)
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]
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if config["solving"]["agg_p_nom_limits"]["agg_offwind"]:
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if config["solving"]["agg_p_nom_limits"]["agg_offwind"]:
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gens_cst = gens_cst.replace(rename_offwind)
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gens_cst = gens_cst.replace(rename_offwind)
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rhs_cst = (
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rhs_cst = (
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pd.concat([gens_cst.bus.map(n.buses.country), gens_cst[["carrier", "p_nom"]]], axis=1)
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pd.concat(
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.groupby(["bus", "carrier"]).sum()
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[gens_cst.bus.map(n.buses.country), gens_cst[["carrier", "p_nom"]]],
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axis=1,
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)
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.groupby(["bus", "carrier"])
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.sum()
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)
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)
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rhs_cst.index = rhs_cst.index.rename({"bus": "country"})
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rhs_cst.index = rhs_cst.index.rename({"bus": "country"})
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rhs_min = agg_p_nom_minmax["min"].dropna()
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rhs_min = agg_p_nom_minmax["min"].dropna()
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