85c356297a
* Add logging to logfiles to all snakemake workflow scripts. * Fix missing quotation marks in Snakefile. * Apply suggestions from code review Co-Authored-By: Fabian Neumann <fabian.neumann@outlook.de> * Apply suggestions from code review Co-Authored-By: Fabian Neumann <fabian.neumann@outlook.de> * doc: fix _ec_ filenames in docs * Allow logging message format to be specified in config.yaml. * Add logging for Snakemake rule 'retrieve_databundle '. * Add limited logging to STDERR only for retrieve_*.py scripts. * Import progressbar module only on demand. * Fix logging to file and enable concurrent printing to STDERR for most scripts. * Add new 'logging_format' option to Travis CI test config.yaml. * Add missing parenthesis (bug fix) and cross-os compatible paths. * Fix typos in messages. * Use correct log files for logging (bug fix). * doc: fix line references * config: logging_format in all configs * doc: add doc for logging_format * environment: update to powerplantmatching 0.4.3 * doc: update line references for tutorial.rst * Change logging configuration scheme for config.yaml. * Add helper function for doing basic logging configuration. * Add logpath for prepare_links_p_nom rule. * Outsource basic logging configuration for all scripts to _helper submodule. * Update documentation for changed config.yaml structure. Instead of 'logging_level' and 'logging_format', now 'logging' with subcategories is used. * _helpers: Change configure_logging signature.
116 lines
4.1 KiB
Python
116 lines
4.1 KiB
Python
"""
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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/{network}_s{simpl}_{clusters}.nc``: confer :ref:`cluster`
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- ``results/networks/{network}_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/{network}_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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logger = logging.getLogger(__name__)
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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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import re
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from vresutils.benchmark import memory_logger
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from solve_network import patch_pyomo_tmpdir, solve_network, prepare_network
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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'] = 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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)
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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] = 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'] = 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'] = 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'] = 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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# Detect running outside of snakemake and mock snakemake for testing
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if 'snakemake' not in globals():
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from vresutils.snakemake import MockSnakemake
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snakemake = MockSnakemake(
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wildcards=dict(network='elec', simpl='', clusters='45', lv='1.5', opts='Co2L-3H'),
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input=dict(unprepared="networks/{network}_s{simpl}_{clusters}.nc",
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optimized="results/networks/{network}_s{simpl}_{clusters}_lv{lv}_{opts}.nc"),
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output=["results/networks/{network}_s{simpl}_{clusters}_lv{lv}_{opts}_op.nc"],
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log=dict(solver="logs/s{simpl}_{clusters}_lv{lv}_{opts}_op_solver.log",
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python="logs/s{simpl}_{clusters}_lv{lv}_{opts}_op_python.log")
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)
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tmpdir = snakemake.config['solving'].get('tmpdir')
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if tmpdir is not None:
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patch_pyomo_tmpdir(tmpdir)
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configure_logging(snakemake)
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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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opts = [o
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for o in snakemake.wildcards.opts.split('-')
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if not re.match(r'^\d+h$', o, re.IGNORECASE)]
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with memory_logger(filename=getattr(snakemake.log, 'memory', None), 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=snakemake.config['solving'], 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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