solve_network.py: switch to linopy interface
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@ -1,18 +1,9 @@
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"""Solve network."""
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"""Solve network."""
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import pypsa
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import pypsa
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import numpy as np
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import numpy as np
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import pandas as pd
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import xarray as xr
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from pypsa.linopt import get_var, linexpr, define_constraints
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from linopy import merge
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from pypsa.linopf import network_lopf, ilopf
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from vresutils.benchmark import memory_logger
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from vresutils.benchmark import memory_logger
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from helper import override_component_attrs, update_config_with_sector_opts
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from helper import override_component_attrs, update_config_with_sector_opts
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import logging
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import logging
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@ -73,15 +64,14 @@ def prepare_network(n, solve_opts=None):
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df.where(df>solve_opts['clip_p_max_pu'], other=0., inplace=True)
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df.where(df>solve_opts['clip_p_max_pu'], other=0., inplace=True)
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if solve_opts.get('load_shedding'):
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if solve_opts.get('load_shedding'):
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# intersect between macroeconomic and surveybased willingness to pay
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# http://journal.frontiersin.org/article/10.3389/fenrg.2015.00055/full
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n.add("Carrier", "Load")
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n.add("Carrier", "Load")
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n.madd("Generator", n.buses.index, " load",
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n.madd("Generator", n.buses.index, " load",
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bus=n.buses.index,
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bus=n.buses.index,
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carrier='load',
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carrier='load',
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sign=1e-3, # Adjust sign to measure p and p_nom in kW instead of MW
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sign=1e-3, # Adjust sign to measure p and p_nom in kW instead of MW
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marginal_cost=1e2, # Eur/kWh
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marginal_cost=1e2, # Eur/kWh
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# intersect between macroeconomic and surveybased
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# willingness to pay
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# http://journal.frontiersin.org/article/10.3389/fenrg.2015.00055/full
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p_nom=1e9 # kW
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p_nom=1e9 # kW
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)
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)
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@ -188,27 +178,17 @@ def add_co2_sequestration_limit(n, sns):
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co2_stores = n.stores.loc[n.stores.carrier=='co2 stored'].index
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co2_stores = n.stores.loc[n.stores.carrier=='co2 stored'].index
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if co2_stores.empty or ('Store', 'e') not in n.variables.index:
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if co2_stores.empty or 'Store-e' not in n.model.variables:
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return
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return
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vars_final_co2_stored = get_var(n, 'Store', 'e').loc[sns[-1], co2_stores]
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lhs = linexpr((1, vars_final_co2_stored)).sum()
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limit = n.config["sector"].get("co2_sequestration_potential", 200) * 1e6
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limit = n.config["sector"].get("co2_sequestration_potential", 200) * 1e6
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for o in opts:
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for o in opts:
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if not "seq" in o: continue
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if not "seq" in o: continue
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limit = float(o[o.find("seq")+3:]) * 1e6
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limit = float(o[o.find("seq")+3:]) * 1e6
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break
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break
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name = 'co2_sequestration_limit'
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n.add("GlobalConstraint", 'co2_sequestration_limit', sense="<=", constant=limit,
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sense = "<="
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type=np.nan, carrier_attribute="co2 stored")
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n.add("GlobalConstraint", name, sense=sense, constant=limit,
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type=np.nan, carrier_attribute=np.nan)
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define_constraints(n, lhs, sense, limit, 'GlobalConstraint',
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'mu', axes=pd.Index([name]), spec=name)
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def extra_functionality(n, snapshots):
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def extra_functionality(n, snapshots):
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@ -288,7 +268,6 @@ if __name__ == "__main__":
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n = pypsa.Network(snakemake.input.network, override_component_attrs=overrides)
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n = pypsa.Network(snakemake.input.network, override_component_attrs=overrides)
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n = prepare_network(n, solve_opts)
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n = prepare_network(n, solve_opts)
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n.snapshots = n.snapshots[:20]
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n = solve_network(n, config=snakemake.config, opts=opts,
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n = solve_network(n, config=snakemake.config, opts=opts,
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solver_dir=tmpdir,
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solver_dir=tmpdir,
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