67 lines
2.5 KiB
Python
67 lines
2.5 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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# SPDX-FileCopyrightText: : 2017-2024 The PyPSA-Eur Authors
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#
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# SPDX-License-Identifier: MIT
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import logging
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import pandas as pd
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import pypsa
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from _helpers import configure_logging, set_scenario_config
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from entsoe import EntsoePandasClient
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from entsoe.exceptions import InvalidBusinessParameterError, NoMatchingDataError
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from requests import HTTPError
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logger = logging.getLogger(__name__)
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if __name__ == "__main__":
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if "snakemake" not in globals():
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from _helpers import mock_snakemake
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snakemake = mock_snakemake("build_cross_border_flows")
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configure_logging(snakemake)
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set_scenario_config(snakemake)
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api_key = snakemake.config["private"]["keys"]["entsoe_api"]
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client = EntsoePandasClient(api_key=api_key)
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n = pypsa.Network(snakemake.input.network)
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start = pd.Timestamp(snakemake.params.snapshots["start"], tz="Europe/Brussels")
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end = pd.Timestamp(snakemake.params.snapshots["end"], tz="Europe/Brussels")
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branches = n.branches().query("carrier in ['AC', 'DC']")
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c = n.buses.country
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branch_countries = pd.concat([branches.bus0.map(c), branches.bus1.map(c)], axis=1)
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branch_countries = branch_countries.query("bus0 != bus1")
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branch_countries = branch_countries.apply(sorted, axis=1, result_type="broadcast")
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country_pairs = branch_countries.drop_duplicates().reset_index(drop=True)
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flows = []
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unavailable_borders = []
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for from_country, to_country in country_pairs.values:
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try:
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flow_directed = client.query_crossborder_flows(
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from_country, to_country, start=start, end=end
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)
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flow_reverse = client.query_crossborder_flows(
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to_country, from_country, start=start, end=end
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)
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flow = (flow_directed - flow_reverse).rename(
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f"{from_country} - {to_country}"
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)
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flow = flow.tz_localize(None).resample("1h").mean()
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flow = flow.loc[start.tz_localize(None) : end.tz_localize(None)]
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flows.append(flow)
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except (HTTPError, NoMatchingDataError, InvalidBusinessParameterError):
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unavailable_borders.append(f"{from_country}-{to_country}")
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if unavailable_borders:
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logger.warning(
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"Historical electricity cross-border flows for countries"
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f" {', '.join(unavailable_borders)} not available."
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)
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flows = pd.concat(flows, axis=1)
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flows.to_csv(snakemake.output[0])
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