53 lines
1.6 KiB
Python
53 lines
1.6 KiB
Python
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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# SPDX-FileCopyrightText: : 2017-2023 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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from _helpers import configure_logging
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from entsoe import EntsoePandasClient
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from entsoe.exceptions import NoMatchingDataError
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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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api_key = snakemake.config["private"]["keys"]["entsoe_api"]
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client = EntsoePandasClient(api_key=api_key)
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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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countries = snakemake.params.countries
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prices = []
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unavailable_countries = []
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for country in countries:
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country_code = country
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try:
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gen = client.query_day_ahead_prices(country, start=start, end=end)
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gen = gen.tz_localize(None).resample("1h").mean()
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gen = gen.loc[start.tz_localize(None) : end.tz_localize(None)]
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prices.append(gen)
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except NoMatchingDataError:
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unavailable_countries.append(country)
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if unavailable_countries:
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logger.warning(
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f"Historical electricity prices for countries {', '.join(unavailable_countries)} not available."
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)
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keys = [c for c in countries if c not in unavailable_countries]
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prices = pd.concat(prices, keys=keys, axis=1)
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prices.to_csv(snakemake.output[0])
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