51 lines
1.4 KiB
Python
51 lines
1.4 KiB
Python
# -*- 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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"""
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Solves linear optimal dispatch in hourly resolution using the capacities of
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previous capacity expansion in rule :mod:`solve_network`.
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"""
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import logging
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import numpy as np
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import pypsa
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from _helpers import configure_logging, update_config_from_wildcards
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from solve_network import prepare_network, solve_network
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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(
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"solve_operations_network",
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configfiles="test/config.electricity.yaml",
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simpl="",
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opts="",
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clusters="5",
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ll="v1.5",
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sector_opts="",
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planning_horizons="",
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)
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configure_logging(snakemake)
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update_config_from_wildcards(snakemake.config, snakemake.wildcards)
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solve_opts = snakemake.params.options
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np.random.seed(solve_opts.get("seed", 123))
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n = pypsa.Network(snakemake.input.network)
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n.optimize.fix_optimal_capacities()
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n = prepare_network(n, solve_opts, config=snakemake.config)
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n = solve_network(n, config=snakemake.config, log_fn=snakemake.log.solver)
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n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
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n.export_to_netcdf(snakemake.output[0])
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