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