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clustering strats to configurables: review suggestions

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This commit is contained in:
martacki 2022-06-21 18:42:49 +02:00
parent b4d8dd8ecb
commit bdd0cc3aa1
2 changed files with 18 additions and 12 deletions
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11
scripts/cluster_network.py
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@ -263,11 +263,8 @@ def clustering_for_n_clusters(n, n_clusters, custom_busmap=False, aggregate_carr
bus_strategies = dict(country=_make_consense("Bus", "country")) bus_strategies = dict(country=_make_consense("Bus", "country"))
bus_strategies.update(aggregation_strategies.get("buses", {})) bus_strategies.update(aggregation_strategies.get("buses", {}))
generator_strategies = aggregation_strategies.get("generators", {"p_nom_max": "sum"})
# this snippet supports compatibility of PyPSA and PyPSA-EUR: generator_strategies = aggregation_strategies.get("generators", {"p_nom_max": "sum"})
if "p_nom_max" in generator_strategies:
if generator_strategies["p_nom_max"] == "min": generator_strategies["p_nom_max"] = np.min
if not isinstance(custom_busmap, pd.Series): if not isinstance(custom_busmap, pd.Series):
busmap = busmap_for_n_clusters(n, n_clusters, solver_name, focus_weights, algorithm) busmap = busmap_for_n_clusters(n, n_clusters, solver_name, focus_weights, algorithm)
@ -369,6 +366,12 @@ if __name__ == "__main__":
) )
return v return v
aggregation_strategies = snakemake.config["clustering"].get("aggregation_strategies", {}) aggregation_strategies = snakemake.config["clustering"].get("aggregation_strategies", {})
aggregation_strategies = {}
# translate str entries of aggregation_strategies to pd.Series functions:
aggregation_strategies = {
p: {k: getattr(pd.Series, v) for k,v in aggregation_strategies[p].items()}
for p in aggregation_strategies.keys()
}
custom_busmap = snakemake.config["enable"].get("custom_busmap", False) custom_busmap = snakemake.config["enable"].get("custom_busmap", False)
if custom_busmap: if custom_busmap:

19
scripts/simplify_network.py
View File

@ -320,7 +320,7 @@ def remove_stubs(n, costs, config, output):
return n, busmap return n, busmap
def aggregate_to_substations(n, config, aggregation_strategies=dict(), buses_i=None): def aggregate_to_substations(n, aggregation_strategies=dict(), buses_i=None):
# can be used to aggregate a selection of buses to electrically closest neighbors # can be used to aggregate a selection of buses to electrically closest neighbors
# if no buses are given, nodes that are no substations or without offshore connection are aggregated # if no buses are given, nodes that are no substations or without offshore connection are aggregated
@ -345,15 +345,13 @@ def aggregate_to_substations(n, config, aggregation_strategies=dict(), buses_i=N
busmap = n.buses.index.to_series() busmap = n.buses.index.to_series()
busmap.loc[buses_i] = dist.idxmin(1) busmap.loc[buses_i] = dist.idxmin(1)
# default aggregation strategies must be specified within the function, otherwise (when defaults are passed in # default aggregation strategies must be specified within the function, otherwise (when defaults
# the function's definition) they get lost in case custom values for different variables are specified in the config # are passed in the function's definition) they get lost in case custom values for different
# variables are specified in the config.
bus_strategies = dict(country=_make_consense("Bus", "country")) bus_strategies = dict(country=_make_consense("Bus", "country"))
bus_strategies.update(aggregation_strategies.get("buses", {})) bus_strategies.update(aggregation_strategies.get("buses", {}))
generator_strategies = aggregation_strategies.get("generators", {"p_nom_max": "sum"})
# this snippet supports compatibility of PyPSA and PyPSA-EUR: generator_strategies = aggregation_strategies.get("generators", {"p_nom_max": "sum"})
if "p_nom_max" in generator_strategies:
if generator_strategies["p_nom_max"] == "min": generator_strategies["p_nom_max"] = np.min
clustering = get_clustering_from_busmap(n, busmap, clustering = get_clustering_from_busmap(n, busmap,
bus_strategies=bus_strategies, bus_strategies=bus_strategies,
@ -393,6 +391,11 @@ if __name__ == "__main__":
n = pypsa.Network(snakemake.input.network) n = pypsa.Network(snakemake.input.network)
aggregation_strategies = snakemake.config["clustering"].get("aggregation_strategies", {}) aggregation_strategies = snakemake.config["clustering"].get("aggregation_strategies", {})
# translate str entries of aggregation_strategies to pd.Series functions:
aggregation_strategies = {
p: {k: getattr(pd.Series, v) for k,v in aggregation_strategies[p].items()}
for p in aggregation_strategies.keys()
}
n, trafo_map = simplify_network_to_380(n) n, trafo_map = simplify_network_to_380(n)
@ -407,7 +410,7 @@ if __name__ == "__main__":
busmaps = [trafo_map, simplify_links_map, stub_map] busmaps = [trafo_map, simplify_links_map, stub_map]
if snakemake.config.get('clustering', {}).get('simplify', {}).get('to_substations', False): if snakemake.config.get('clustering', {}).get('simplify', {}).get('to_substations', False):
n, substation_map = aggregate_to_substations(n, snakemake.config, aggregation_strategies) n, substation_map = aggregate_to_substations(n, aggregation_strategies)
busmaps.append(substation_map) busmaps.append(substation_map)
if snakemake.wildcards.simpl: if snakemake.wildcards.simpl: