remove operations rules to reduce amount of simultaneous changes
This commit is contained in:
Fabian Neumann
parent
1ff8321c5e
commit
e6347621f9
@ -828,21 +828,6 @@ solving:
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walltime: "12:00:00"
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operations:
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rolling_horizon:
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window: 10 # days
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overlap: 8 # days
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bidding_prices: # EUR/MW
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H2 Electrolysis: -10
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H2 Fuel Cell: 200
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urban central water tanks charger: -10
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urban central water tanks discharger: 10
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hydro: 70
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solid biomass: 150
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biogas: 100
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co2_price: 500 # EUR/t
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co2_sequestation_limit: 200 # Mt/a
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# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#plotting
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plotting:
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map:
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@ -41,61 +41,3 @@ rule solve_sector_network:
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"../envs/environment.yaml"
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script:
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"../scripts/solve_network.py"
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rule solve_operations_network_other_year:
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input:
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pre=RDIR
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+ "/prenetworks/elec{weather_year}_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_{planning_horizons}.nc",
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post=RDIR
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+ "/postnetworks/elec{capacity_year}_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_{planning_horizons}.nc",
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output:
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RDIR
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+ "/operations/elec{capacity_year}_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_{planning_horizons}_{weather_year}.nc",
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shadow:
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"shallow"
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log:
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solver=RDIR
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+ "/logs/elec{capacity_year}_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_{planning_horizons}_{weather_year}_solver.log",
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python=RDIR
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+ "/logs/elec{capacity_year}_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_{planning_horizons}_{weather_year}_python.log",
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threads: 4
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resources:
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mem_mb=10000,
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benchmark:
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(
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RDIR
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+ "/benchmarks/solve_operations_network/elec{capacity_year}_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_{planning_horizons}_{weather_year}"
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)
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script:
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"../scripts/solve_operations_network_other_year.py"
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# rule solve_operations_network_other_year_myopic:
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# input:
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# overrides="data/override_component_attrs",
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# pre=RDIR
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# + "/prenetworks/elec{weather_year}_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_{planning_horizons}.nc",
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# post=RDIR
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# + "/postnetworks/elec{capacity_year}_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_{planning_horizons}.nc",
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# previous=solved_previous_year,
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# output:
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# RDIR
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# + "/operations/elec{capacity_year}_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_{planning_horizons}_{weather_year}_myopic.nc",
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# shadow:
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# "shallow"
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# log:
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# solver=RDIR
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# + "/logs/elec{capacity_year}_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_{planning_horizons}_{weather_year}_solver.log",
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# python=RDIR
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# + "/logs/elec{capacity_year}_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_{planning_horizons}_{weather_year}_python.log",
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# threads: 4
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# resources:
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# mem_mb=10000,
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# benchmark:
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# (
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# RDIR
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# + "/benchmarks/solve_operations_network_myopic/elec{capacity_year}_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_{planning_horizons}_{weather_year}"
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# )
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# script:
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# "../scripts/solve_operations_network_other_year_myopic.py"
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@ -1,147 +0,0 @@
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# -*- coding: utf-8 -*-
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# SPDX-FileCopyrightText: : 2017-2024 The PyPSA-Eur Authors
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#
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# SPDX-License-Identifier: MIT
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"""
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Solve operations 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 solve_network import prepare_network, solve_network
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logger = logging.getLogger(__name__)
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pypsa.pf.logger.setLevel(logging.WARNING)
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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(
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lines_typed_i, fill_value=0.0
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)
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n.lines.loc[lines_typed_i, "s_nom"] = (
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np.sqrt(3)
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* n.lines["type"].map(n.line_types.i_nom)
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* n.lines.bus0.map(n.buses.v_nom)
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* 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(
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lines_untyped_i, fill_value=0.0
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)
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n.lines["s_nom_extendable"] = False
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links_dc_i = n.links.index[n.links.p_nom_extendable]
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n.links.loc[links_dc_i, "p_nom"] = n_optim.links["p_nom_opt"].reindex(
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links_dc_i, fill_value=0.0
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)
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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(
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gen_extend_i, fill_value=0.0
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)
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n.generators.loc[gen_extend_i, "p_nom_extendable"] = False
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stor_units_extend_i = n.storage_units.index[n.storage_units.p_nom_extendable]
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n.storage_units.loc[stor_units_extend_i, "p_nom"] = n_optim.storage_units[
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"p_nom_opt"
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].reindex(stor_units_extend_i, fill_value=0.0)
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n.storage_units.loc[stor_units_extend_i, "p_nom_extendable"] = False
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stor_extend_i = n.stores.index[n.stores.e_nom_extendable]
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n.stores.loc[stor_extend_i, "e_nom"] = n_optim.stores["e_nom_opt"].reindex(
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stor_extend_i, fill_value=0.0
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)
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n.stores.loc[stor_extend_i, "e_nom_extendable"] = False
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return n
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def remove_unused_components(n, threshold=50):
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logger.info("Remove assets that are barely used to speed things up.")
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for c in n.iterate_components({"Store", "Link", "Generator"}):
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attr = "e_nom" if c.name == "Store" else "p_nom"
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to_remove = c.df.loc[c.df[attr] < threshold].index
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logger.info(f"Removing barely used {c.name}s:\n{to_remove}")
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n.mremove(c.name, to_remove)
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return n
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def add_load_shedding(n, voll=1e4):
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logger.info("Add load shedding to all buses.")
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if "load" in n.generators.carrier.unique():
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to_remove = n.generators.query("carrier == 'load'").index
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logger.info(f"Removing pre-existing load shedding:\n{to_remove}")
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n.mremove("Generator", to_remove)
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n.madd(
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"Generator",
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n.buses.index,
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suffix=" load",
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bus=n.buses.index,
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carrier="load",
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marginal_cost=voll,
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p_nom=1e6,
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)
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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 helper import mock_snakemake
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snakemake = mock_snakemake(
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"solve_operations_network",
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capacity_year=1952,
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simpl="",
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opts="",
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clusters=37,
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lv=2.0,
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sector_opts="Co2L0-25H-T-H-B-I-A",
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planning_horizons=2030,
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weather_year=2013,
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)
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logging.basicConfig(
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filename=snakemake.log.python, level=snakemake.config["logging_level"]
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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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from pathlib import Path
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Path(tmpdir).mkdir(parents=True, exist_ok=True)
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n = pypsa.Network(snakemake.input.pre)
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n_post = pypsa.Network(snakemake.input.post)
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n = set_parameters_from_optimized(n, n_post)
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del n_post
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n = remove_unused_components(n)
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n = add_load_shedding(n)
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opts = snakemake.wildcards.sector_opts.split("-")
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solve_opts = snakemake.config["solving"]["options"]
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solve_opts["skip_iterations"] = True
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n = prepare_network(n, solve_opts)
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n = solve_network(
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n,
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config=snakemake.config,
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opts=opts,
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solver_dir=tmpdir,
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solver_logfile=snakemake.log.solver,
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)
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n.export_to_netcdf(snakemake.output[0])
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@ -1,166 +0,0 @@
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# -*- coding: utf-8 -*-
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# SPDX-FileCopyrightText: : 2017-2024 The PyPSA-Eur Authors
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#
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# SPDX-License-Identifier: MIT
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"""
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Solve myopic operations network.
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"""
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import logging
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import pandas as pd
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import pypsa
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from solve_network import prepare_network, solve_network
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from solve_operations_network import (
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add_load_shedding,
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remove_unused_components,
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set_parameters_from_optimized,
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)
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logger = logging.getLogger(__name__)
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pypsa.pf.logger.setLevel(logging.WARNING)
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def prepare_myopic(n, config, store_soc, storage_unit_soc):
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n.stores.e_cyclic = False
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n.storage_units.cyclic_state_of_charge = False
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biomass_stores = n.stores.carrier.str.isin(["solid biomass", "biogas"])
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biomass_potential = n.stores.loc[biomass_stores, "e_initial"]
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# storage level contiguity across years
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n.stores.e_initial = store_soc
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n.storage_units.state_of_charge_initial = storage_unit_soc
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# replace co2 limit with co2 price
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n.remove("GlobalConstraint", "CO2Limit")
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n.stores.at["co2 atmosphere", "marginal_cost"] = -config["co2_price"]
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# handle co2 sequestration
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assert (
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sum(n.stores.carriers == "co2 stored") == 1
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), "Myopic operation not implemented for spatially resolved CO2 sequestration."
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n.stores.at["co2 stored", "e_nom"] = config["co2_sequestration_limit"] * 1e6 # t/a
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# reset co2 emissions
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n.stores.loc[n.stores.carrier == "co2 stored", "e_initial"] = 0.0
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n.stores.at["co2 atmosphere", "e_initial"] = 0.0
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# replenish fossil gas and oil with 1000 TWh each
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fossil_stores = n.stores.carrier.str.isin(["gas", "oil"])
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n.stores.loc[fossil_stores, "e_initial"] = 1e9
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n.stores.loc[fossil_stores, "e_nom"] = 10e9
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# replenish annual solid biomass and biogas potentials
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n.stores.loc[biomass_stores, "e_initial"] = biomass_potential
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# set storage bidding prices
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bidding_prices = config["bidding_prices"]
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for c in n.iterate_components({"Store", "Link", "StorageUnit"}):
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c.df.marginal_cost.update(c.df.carrier.map(bidding_prices).dropna())
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# deduct industry solid biomass
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assert (
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sum(n.stores.carriers == "solid biomass") == 1
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), "Myopic operation not implemented for spatially resolved solid biomass."
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n.stores.at["EU solid biomass", "e_initial"] -= (
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n.loads.at["solid biomass for industry", "p_set"] * 8760
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)
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n.remove("Load", "solid biomass for industry")
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return n
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def solve_network_myopic(n, config, opts="", **kwargs):
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rolling_horizon = config["operations"]["rolling_horizon"]
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freq = int(pd.infer_freq(n.snapshots)[:-1])
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window = rolling_horizon["window"] * 24 // freq
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overlap = rolling_horizon["overlap"] * 24 // freq
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kept = window - overlap
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length = len(n.snapshots)
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assert (
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kept > 0
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), f"Overlap ({overlap} days) must be smaller than windows ({window} days)."
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for i in range(length // kept):
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snapshots = n.snapshots[i * kept : (i + 1) * kept + overlap]
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logger.info(f"Optimising operations from {snapshots[0]} to {snapshots[-1]}")
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n = solve_network(n, config, opts=opts, snapshots=snapshots, **kwargs)
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last_kept = n.snapshots[(i + 1) * kept - 1]
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logger.info(f"Setting initial SOCs from {last_kept} for next iteration.\n")
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n.stores.e_initial = n.stores_t.e.loc[last_kept]
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n.storage_units.state_of_charge_initial = n.storage_units_t.state_of_charge.loc[
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last_kept
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]
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# final segment until end of year
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snapshots = n.snapshots[(i + 1) * kept :]
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n = solve_network(n, config, opts=opts, snapshots=snapshots, **kwargs)
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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 helper import mock_snakemake
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snakemake = mock_snakemake(
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"solve_operations_network_myopic",
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capacity_year=1952,
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simpl="",
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opts="",
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clusters=37,
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lv=2.0,
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sector_opts="Co2L0-25H-T-H-B-I-A",
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planning_horizons=2030,
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weather_year=2013,
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)
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logging.basicConfig(
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filename=snakemake.log.python, level=snakemake.config["logging_level"]
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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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from pathlib import Path
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Path(tmpdir).mkdir(parents=True, exist_ok=True)
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config = snakemake.config["operations"]
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n = pypsa.Network(snakemake.input.pre)
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n_post = pypsa.Network(snakemake.input.post)
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n = set_parameters_from_optimized(n, n_post)
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del n_post
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n_previous = pypsa.Network(snakemake.input.previous)
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store_soc = n_previous.stores_t.e.iloc[-1]
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storage_unit_soc = n_previous.storage_units_t.state_of_charge.iloc[-1]
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del n_previous
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n = remove_unused_components(n)
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n = add_load_shedding(n)
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n = prepare_myopic(n, config, store_soc, storage_unit_soc)
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opts = snakemake.wildcards.sector_opts.split("-")
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solve_opts = snakemake.config["solving"]["options"]
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solve_opts["skip_iterations"] = True
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n = prepare_network(n, solve_opts)
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n = solve_network_myopic(
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n,
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config=snakemake.config,
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opts=opts,
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solver_dir=tmpdir,
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solver_logfile=snakemake.log.solver,
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)
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n.export_to_netcdf(snakemake.output[0])
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