adjustments to new due to clustering module
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@ -621,14 +621,10 @@ clustering:
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exclude_carriers: []
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aggregation_strategies:
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generators:
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p_nom_max: sum # use "min" for more conservative assumptions
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p_nom_min: sum
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p_min_pu: mean
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marginal_cost: mean
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p_nom_max: weighted_min
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committable: any
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ramp_limit_up: max
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ramp_limit_down: max
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efficiency: mean
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solving:
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#tmpdir: "path/to/tmp"
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@ -775,6 +771,8 @@ plotting:
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H2: "Hydrogen Storage"
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lines: "Transmission Lines"
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ror: "Run of River"
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ac: "AC"
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dc: "DC"
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tech_colors:
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# wind
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@ -499,13 +499,6 @@ if __name__ == "__main__":
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Nyears,
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).at["HVAC overhead", "capital_cost"]
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def consense(x):
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v = x.iat[0]
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assert (
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x == v
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).all() or x.isnull().all(), "The `potential` configuration option must agree for all renewable carriers, for now!"
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return v
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custom_busmap = params.custom_busmap
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if custom_busmap:
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custom_busmap = pd.read_csv(
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@ -36,7 +36,11 @@ if __name__ == "__main__":
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# %%
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def rename_index(ds):
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return ds.set_axis(ds.index.map(lambda x: f"{x[1]}\n({x[0].lower()})"))
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specific = ds.index.map(lambda x: f"{x[1]}\n({x[0].lower()})")
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generic = ds.index.get_level_values("carrier")
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duplicated = generic.duplicated(keep=False)
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index = specific.where(duplicated, generic)
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return ds.set_axis(index)
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def plot_static_per_carrier(ds, ax, drop_zero=True):
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if drop_zero:
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@ -256,8 +256,12 @@ def _aggregate_and_move_components(
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_, generator_strategies = get_aggregation_strategies(aggregation_strategies)
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carriers = set(n.generators.carrier) - set(exclude_carriers)
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generators, generators_pnl = aggregategenerators(
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n, busmap, carriers=carriers, custom_strategies=generator_strategies
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generators, generators_pnl = aggregateoneport(
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n,
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busmap,
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"Generator",
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carriers=carriers,
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custom_strategies=generator_strategies,
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)
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replace_components(n, "Generator", generators, generators_pnl)
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@ -602,14 +606,16 @@ if __name__ == "__main__":
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# some entries in n.buses are not updated in previous functions, therefore can be wrong. as they are not needed
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# and are lost when clustering (for example with the simpl wildcard), we remove them for consistency:
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buses_c = {
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remove = [
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"symbol",
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"tags",
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"under_construction",
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"substation_lv",
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"substation_off",
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}.intersection(n.buses.columns)
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n.buses = n.buses.drop(buses_c, axis=1)
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"geometry",
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]
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n.buses.drop(remove, axis=1, inplace=True, errors="ignore")
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n.lines.drop(remove, axis=1, errors="ignore", inplace=True)
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update_p_nom_max(n)
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