treatment of outliers and small feature-bugfix
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@ -272,6 +272,8 @@ def busmap_for_n_clusters(n, n_clusters, solver_name, focus_weights=None, algori
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algorithm_kwds.setdefault('tol', 1e-6)
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def fix_country_assignment_for_hac(n):
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from scipy.sparse import csgraph
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# overwrite country of nodes that are disconnected from their country-topology
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for country in n.buses.country.unique():
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m = n.copy()
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@ -288,19 +290,18 @@ def busmap_for_n_clusters(n, n_clusters, solver_name, focus_weights=None, algori
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neighbor_bus = n.lines.query("bus0 in @disconnected_bus or bus1 in @disconnected_bus").iloc[0][['bus0','bus1']]
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new_country = list(set(n.buses.loc[neighbor_bus].country)-set([country]))[0]
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logger.info(f"overwriting country ``{country}`` of bus ``{disconnected_bus}`` to new country ``{new_country}``, "
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logger.info(f"overwriting country `{country}` of bus `{disconnected_bus}` to new country `{new_country}`, "
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"because it is disconnected from its inital inter-country transmission grid.")
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n.buses.at[disconnected_bus, "country"] = new_country
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return n
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if algorithm == "hac":
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from scipy.sparse import csgraph
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feature = get_feature_for_hac(n, buses_i=n.buses.index, feature=feature)
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n = fix_country_assignment_for_hac(n)
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elif feature is not None:
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logger.warning(f"Keyword argument feature is only valid for algorithm 'hac'."
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f"given feature ``{feature}`` will be ignored.")
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if (algorithm != "hac") and (feature is not None):
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logger.warning(f"Keyword argument feature is only valid for algorithm `hac`. "
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f"Given feature `{feature}` will be ignored.")
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n.determine_network_topology()
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@ -338,7 +339,7 @@ def clustering_for_n_clusters(n, n_clusters, custom_busmap=False, aggregate_carr
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line_length_factor=1.25, potential_mode='simple', solver_name="cbc",
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algorithm="hac", feature=None, extended_link_costs=0, focus_weights=None):
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logger.info(f"Clustering network using algorithm ``{algorithm}`` and feature ``{feature}``...")
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logger.info(f"Clustering network using algorithm `{algorithm}` and feature `{feature}`...")
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if potential_mode == 'simple':
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p_nom_max_strategy = np.sum
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@ -348,7 +349,7 @@ def clustering_for_n_clusters(n, n_clusters, custom_busmap=False, aggregate_carr
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raise AttributeError(f"potential_mode should be one of 'simple' or 'conservative' but is '{potential_mode}'")
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if not custom_busmap:
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busmap = busmap_for_n_clusters(n, n_clusters, solver_name, focus_weights, algorithm)
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busmap = busmap_for_n_clusters(n, n_clusters, solver_name, focus_weights, algorithm, feature)
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else:
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busmap = custom_busmap
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@ -407,7 +407,21 @@ if __name__ == "__main__":
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n, substation_map = aggregate_to_substations(n)
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busmaps.append(substation_map)
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# treatment of outliers (nodes without a profile for considered carrier) for "cluster_network"
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if snakemake.config.get("clustering", {}).get("cluster_network", {}).get("algorithm", "hac") == "hac":
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carriers = cluster_config.get("feature", "solar+onwind-time").split('-')[0].split('+')
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buses_i = list(set(n.buses.index)-set(n.generators.query("carrier in @carriers").bus))
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n, busmap_hac = aggregate_to_substations(n, buses_i)
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busmaps.append(busmap_hac)
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if snakemake.wildcards.simpl:
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# treatment of outliers (nodes without a profile for a considered carrier) for "simplify"
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if cluster_config.get("algorithm", "hac") == "hac":
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carriers = cluster_config.get("feature", "solar+onwind-time").split('-')[0].split('+')
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buses_i = list(set(n.buses.index)-set(n.generators.query("carrier in @carriers").bus))
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n, busmap_hac = aggregate_to_substations(n, buses_i)
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busmaps.append(busmap_hac)
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# conduct clustering
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n, cluster_map = cluster(n, int(snakemake.wildcards.simpl), snakemake.config,
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algorithm=cluster_config.get('algorithm', 'hac'),
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feature=cluster_config.get('feature', None))
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