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Co-authored-by: FabianHofmann <hofmann@fias.uni-frankfurt.de>
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@ -131,8 +131,7 @@ def update_p_nom_max(n):
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# the installed capacity might exceed the expansion limit.
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# the installed capacity might exceed the expansion limit.
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# Hence, we update the assumptions.
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# Hence, we update the assumptions.
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n.generators.p_nom_max = (n.generators
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n.generators.p_nom_max = n.generators[['p_nom_min', 'p_nom_max']].max(1)
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.apply(lambda b: b[['p_nom_min','p_nom_max']].max(), axis=1))
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def aggregate_p_nom(n):
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def aggregate_p_nom(n):
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return pd.concat([
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return pd.concat([
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