2fc1ea0255
* some refactoring and code cleaning
* execute pre-commit
* pre-commit: limit large files
* add license to .pre-commit
* add pre-commit to env
* solve: tidy memory logger
* travis: add conda list for easier debugging
* undo config test/tutorial without plotting, rm matplotlibrc, .licenses
* remove {networks} wildcard
* unadd pre-commit config
* add release notes
* restore REUSE compliance
* fix docs environment python version
* env: remove gurobi from dependencies
* fix unclean merge block
* fix elif to if
* lighter rtd style
* lighter rtd style II
119 lines
3.8 KiB
Python
119 lines
3.8 KiB
Python
# SPDX-FileCopyrightText: : 2017-2020 The PyPSA-Eur Authors
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#
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# SPDX-License-Identifier: GPL-3.0-or-later
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"""
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Solves linear optimal dispatch in hourly resolution
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using the capacities of previous capacity expansion in rule :mod:`solve_network`.
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Relevant Settings
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-----------------
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.. code:: yaml
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solving:
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tmpdir:
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options:
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formulation:
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clip_p_max_pu:
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load_shedding:
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noisy_costs:
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nhours:
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min_iterations:
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max_iterations:
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solver:
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name:
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(solveroptions):
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.. seealso::
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Documentation of the configuration file ``config.yaml`` at
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:ref:`solving_cf`
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Inputs
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------
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- ``networks/elec_s{simpl}_{clusters}.nc``: confer :ref:`cluster`
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- ``results/networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc``: confer :ref:`solve`
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Outputs
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-------
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- ``results/networks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_op.nc``: Solved PyPSA network for optimal dispatch including optimisation results
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Description
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-----------
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"""
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import logging
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from _helpers import configure_logging
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import pypsa
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import numpy as np
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from pathlib import Path
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from vresutils.benchmark import memory_logger
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from solve_network import solve_network, prepare_network
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logger = logging.getLogger(__name__)
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def set_parameters_from_optimized(n, n_optim):
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lines_typed_i = n.lines.index[n.lines.type != '']
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n.lines.loc[lines_typed_i, 'num_parallel'] = \
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n_optim.lines['num_parallel'].reindex(lines_typed_i, fill_value=0.)
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n.lines.loc[lines_typed_i, 's_nom'] = (
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np.sqrt(3) * n.lines['type'].map(n.line_types.i_nom) *
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n.lines.bus0.map(n.buses.v_nom) * n.lines.num_parallel)
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lines_untyped_i = n.lines.index[n.lines.type == '']
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for attr in ('s_nom', 'r', 'x'):
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n.lines.loc[lines_untyped_i, attr] = \
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n_optim.lines[attr].reindex(lines_untyped_i, fill_value=0.)
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n.lines['s_nom_extendable'] = False
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links_dc_i = n.links.index[n.links.carrier == 'DC']
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n.links.loc[links_dc_i, 'p_nom'] = \
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n_optim.links['p_nom_opt'].reindex(links_dc_i, fill_value=0.)
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n.links.loc[links_dc_i, 'p_nom_extendable'] = False
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gen_extend_i = n.generators.index[n.generators.p_nom_extendable]
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n.generators.loc[gen_extend_i, 'p_nom'] = \
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n_optim.generators['p_nom_opt'].reindex(gen_extend_i, fill_value=0.)
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n.generators.loc[gen_extend_i, 'p_nom_extendable'] = False
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stor_extend_i = n.storage_units.index[n.storage_units.p_nom_extendable]
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n.storage_units.loc[stor_extend_i, 'p_nom'] = \
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n_optim.storage_units['p_nom_opt'].reindex(stor_extend_i, fill_value=0.)
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n.storage_units.loc[stor_extend_i, 'p_nom_extendable'] = False
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return n
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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('solve_operations_network', network='elec',
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simpl='', clusters='5', ll='copt', opts='Co2L-BAU-24H')
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configure_logging(snakemake)
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tmpdir = snakemake.config['solving'].get('tmpdir')
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if tmpdir is not None:
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Path(tmpdir).mkdir(parents=True, exist_ok=True)
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n = pypsa.Network(snakemake.input.unprepared)
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n_optim = pypsa.Network(snakemake.input.optimized)
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n = set_parameters_from_optimized(n, n_optim)
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del n_optim
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config = snakemake.config
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opts = snakemake.wildcards.opts.split('-')
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config['solving']['options']['skip_iterations'] = False
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fn = getattr(snakemake.log, 'memory', None)
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with memory_logger(filename=fn, interval=30.) as mem:
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n = prepare_network(n, solve_opts=snakemake.config['solving']['options'])
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n = solve_network(n, config, solver_dir=tmpdir,
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solver_log=snakemake.log.solver, opts=opts)
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n.export_to_netcdf(snakemake.output[0])
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logger.info("Maximum memory usage: {}".format(mem.mem_usage))
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