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scripts/conservation_checks.py

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+# -*- coding: utf-8 -*-
+# SPDX-FileCopyrightText:  PyPSA-Earth and PyPSA-Eur Authors
+#
+# SPDX-License-Identifier: AGPL-3.0-or-later
+
+# -*- coding: utf-8 -*-
+
+import glob
+import os
+import pathlib
+
+import pandas as pd
+import pypsa
+from _helpers import configure_logging, create_logger, mock_snakemake
+
+
+def extract_gen_sum(n, variable_id):
+
+    vals = n.generators.groupby("carrier").sum()[variable_id].to_list()
+    crrs = n.generators.groupby("carrier").sum()[variable_id].index.to_list()
+
+    return (vals, [variable_id] * len(vals), crrs)
+
+
+def collect_statistics(n, network_id):
+    values = []
+    variables = []
+    carriers = []
+
+    overall_load = [n.loads_t.p_set.copy().sum().sum().tolist()]
+    values.extend(overall_load)
+    variables.extend(["p_set"] * len(overall_load))
+    carriers.extend(["physical_load"] * len(overall_load))
+
+    for var in ["p_set", "p_nom_max", "weight"]:
+        values.extend(extract_gen_sum(n, var)[0])
+        variables.extend(extract_gen_sum(n, var)[1])
+        carriers.extend(extract_gen_sum(n, var)[2])
+
+    network_carriers = list(n.generators.carrier.unique())
+    for carr in network_carriers:
+        p_max_pu_cols = n.generators_t.p_max_pu.columns
+        carr_cols = p_max_pu_cols[p_max_pu_cols.str.contains(carr)]
+        p_max_pu_vals = [n.generators_t.p_max_pu[carr_cols].sum().sum().copy().tolist()]
+
+        p_nm = n.generators.query("carrier in @carr")["p_nom_max"]
+        tech_pot_vals = [
+            (p_nm * n.generators_t.p_max_pu[carr_cols]).sum().sum().copy().tolist()
+        ]
+
+        values.extend(p_max_pu_vals)
+        variables.extend(["p_max_pu"] * len(p_max_pu_vals))
+        carriers.extend([carr] * len(p_max_pu_vals))
+
+        values.extend(tech_pot_vals)
+        variables.extend(["tech_potential"] * len(tech_pot_vals))
+        carriers.extend([carr] * len(tech_pot_vals))
+
+    # print(values)
+    # print(variables)
+    # print(carriers)
+
+    res_df = pd.DataFrame(
+        data={"values": values, "variables": variables, "carriers": carriers}
+    )
+    res_df["network_id"] = network_id + ".nc"
+
+    return res_df
+
+
+if __name__ == "__main__":
+    if "snakemake" not in globals():
+        from _helpers import mock_snakemake
+
+        snakemake = mock_snakemake("conservancy_checks")
+
+    configure_logging(snakemake)
+
+    data_folder = snakemake.input.network_folder
+
+    for fl in list(pathlib.Path(data_folder).glob("*.nc")):
+        n = pypsa.Network(fl)
+
+        network_data_df = collect_statistics(n, fl.stem)
+
+        network_data_df.to_csv(data_folder + "/" + fl.stem + "_invar_check.csv")
+        # network_data_df.to_csv(data_folder + "/conservation_checks/" + network_id + "_invar_check.csv")