275 lines
9.8 KiB
Python
275 lines
9.8 KiB
Python
"""Solve network."""
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import pypsa
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import numpy as np
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import pandas as pd
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from pypsa.linopt import get_var, linexpr, define_constraints
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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 helper import override_component_attrs
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import logging
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logger = logging.getLogger(__name__)
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pypsa.pf.logger.setLevel(logging.WARNING)
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def add_land_use_constraint(n):
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if 'm' in snakemake.wildcards.clusters:
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_add_land_use_constraint_m(n)
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else:
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_add_land_use_constraint(n)
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def _add_land_use_constraint(n):
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#warning: this will miss existing offwind which is not classed AC-DC and has carrier 'offwind'
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for carrier in ['solar', 'onwind', 'offwind-ac', 'offwind-dc']:
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existing = n.generators.loc[n.generators.carrier==carrier,"p_nom"].groupby(n.generators.bus.map(n.buses.location)).sum()
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existing.index += " " + carrier + "-" + snakemake.wildcards.planning_horizons
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n.generators.loc[existing.index,"p_nom_max"] -= existing
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n.generators.p_nom_max.clip(lower=0, inplace=True)
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def _add_land_use_constraint_m(n):
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# if generators clustering is lower than network clustering, land_use accounting is at generators clusters
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planning_horizons = snakemake.config["scenario"]["planning_horizons"]
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grouping_years = snakemake.config["existing_capacities"]["grouping_years"]
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current_horizon = snakemake.wildcards.planning_horizons
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for carrier in ['solar', 'onwind', 'offwind-ac', 'offwind-dc']:
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existing = n.generators.loc[n.generators.carrier==carrier,"p_nom"]
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ind = list(set([i.split(sep=" ")[0] + ' ' + i.split(sep=" ")[1] for i in existing.index]))
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previous_years = [
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str(y) for y in
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planning_horizons + grouping_years
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if y < int(snakemake.wildcards.planning_horizons)
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]
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for p_year in previous_years:
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ind2 = [i for i in ind if i + " " + carrier + "-" + p_year in existing.index]
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sel_current = [i + " " + carrier + "-" + current_horizon for i in ind2]
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sel_p_year = [i + " " + carrier + "-" + p_year for i in ind2]
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n.generators.loc[sel_current, "p_nom_max"] -= existing.loc[sel_p_year].rename(lambda x: x[:-4] + current_horizon)
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n.generators.p_nom_max.clip(lower=0, inplace=True)
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def prepare_network(n, solve_opts=None):
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if 'clip_p_max_pu' in solve_opts:
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for df in (n.generators_t.p_max_pu, n.generators_t.p_min_pu, n.storage_units_t.inflow):
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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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n.add("Carrier", "Load")
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n.madd("Generator", n.buses.index, " load",
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bus=n.buses.index,
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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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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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)
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if solve_opts.get('noisy_costs'):
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for t in n.iterate_components():
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#if 'capital_cost' in t.df:
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# t.df['capital_cost'] += 1e1 + 2.*(np.random.random(len(t.df)) - 0.5)
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if 'marginal_cost' in t.df:
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np.random.seed(174)
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t.df['marginal_cost'] += 1e-2 + 2e-3 * (np.random.random(len(t.df)) - 0.5)
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for t in n.iterate_components(['Line', 'Link']):
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np.random.seed(123)
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t.df['capital_cost'] += (1e-1 + 2e-2 * (np.random.random(len(t.df)) - 0.5)) * t.df['length']
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if solve_opts.get('nhours'):
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nhours = solve_opts['nhours']
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n.set_snapshots(n.snapshots[:nhours])
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n.snapshot_weightings[:] = 8760./nhours
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if snakemake.config['foresight'] == 'myopic':
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add_land_use_constraint(n)
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return n
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def add_battery_constraints(n):
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chargers_b = n.links.carrier.str.contains("battery charger")
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chargers = n.links.index[chargers_b & n.links.p_nom_extendable]
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dischargers = chargers.str.replace("charger", "discharger")
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if chargers.empty or ('Link', 'p_nom') not in n.variables.index:
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return
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link_p_nom = get_var(n, "Link", "p_nom")
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lhs = linexpr((1,link_p_nom[chargers]),
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(-n.links.loc[dischargers, "efficiency"].values,
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link_p_nom[dischargers].values))
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define_constraints(n, lhs, "=", 0, 'Link', 'charger_ratio')
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def add_chp_constraints(n):
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electric_bool = (n.links.index.str.contains("urban central")
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& n.links.index.str.contains("CHP")
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& n.links.index.str.contains("electric"))
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heat_bool = (n.links.index.str.contains("urban central")
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& n.links.index.str.contains("CHP")
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& n.links.index.str.contains("heat"))
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electric = n.links.index[electric_bool]
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heat = n.links.index[heat_bool]
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electric_ext = n.links.index[electric_bool & n.links.p_nom_extendable]
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heat_ext = n.links.index[heat_bool & n.links.p_nom_extendable]
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electric_fix = n.links.index[electric_bool & ~n.links.p_nom_extendable]
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heat_fix = n.links.index[heat_bool & ~n.links.p_nom_extendable]
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link_p = get_var(n, "Link", "p")
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if not electric_ext.empty:
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link_p_nom = get_var(n, "Link", "p_nom")
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#ratio of output heat to electricity set by p_nom_ratio
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lhs = linexpr((n.links.loc[electric_ext, "efficiency"]
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*n.links.loc[electric_ext, "p_nom_ratio"],
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link_p_nom[electric_ext]),
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(-n.links.loc[heat_ext, "efficiency"].values,
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link_p_nom[heat_ext].values))
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define_constraints(n, lhs, "=", 0, 'chplink', 'fix_p_nom_ratio')
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#top_iso_fuel_line for extendable
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lhs = linexpr((1,link_p[heat_ext]),
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(1,link_p[electric_ext].values),
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(-1,link_p_nom[electric_ext].values))
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define_constraints(n, lhs, "<=", 0, 'chplink', 'top_iso_fuel_line_ext')
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if not electric_fix.empty:
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#top_iso_fuel_line for fixed
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lhs = linexpr((1,link_p[heat_fix]),
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(1,link_p[electric_fix].values))
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rhs = n.links.loc[electric_fix, "p_nom"].values
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define_constraints(n, lhs, "<=", rhs, 'chplink', 'top_iso_fuel_line_fix')
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if not electric.empty:
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#backpressure
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lhs = linexpr((n.links.loc[electric, "c_b"].values
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*n.links.loc[heat, "efficiency"],
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link_p[heat]),
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(-n.links.loc[electric, "efficiency"].values,
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link_p[electric].values))
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define_constraints(n, lhs, "<=", 0, 'chplink', 'backpressure')
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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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if co2_stores.empty or ('Store', 'e') not in n.variables.index:
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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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rhs = n.config["sector"].get("co2_sequestration_potential", 200) * 1e6
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name = 'co2_sequestration_limit'
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define_constraints(n, lhs, "<=", rhs, '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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add_battery_constraints(n)
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add_co2_sequestration_limit(n, snapshots)
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def solve_network(n, config, opts='', **kwargs):
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solver_options = config['solving']['solver'].copy()
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solver_name = solver_options.pop('name')
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cf_solving = config['solving']['options']
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track_iterations = cf_solving.get('track_iterations', False)
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min_iterations = cf_solving.get('min_iterations', 4)
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max_iterations = cf_solving.get('max_iterations', 6)
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# add to network for extra_functionality
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n.config = config
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n.opts = opts
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if cf_solving.get('skip_iterations', False):
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network_lopf(n, solver_name=solver_name, solver_options=solver_options,
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extra_functionality=extra_functionality, **kwargs)
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else:
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ilopf(n, solver_name=solver_name, solver_options=solver_options,
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track_iterations=track_iterations,
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min_iterations=min_iterations,
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max_iterations=max_iterations,
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extra_functionality=extra_functionality, **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_network',
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simpl='',
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clusters=48,
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lv=1.0,
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sector_opts='Co2L0-168H-T-H-B-I-solar3-dist1',
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planning_horizons=2050,
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)
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logging.basicConfig(filename=snakemake.log.python,
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level=snakemake.config['logging_level'])
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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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opts = snakemake.wildcards.opts.split('-')
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solve_opts = snakemake.config['solving']['options']
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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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overrides = override_component_attrs(snakemake.input.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 = solve_network(n, config=snakemake.config, opts=opts,
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solver_dir=tmpdir,
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solver_logfile=snakemake.log.solver)
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if "lv_limit" in n.global_constraints.index:
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n.line_volume_limit = n.global_constraints.at["lv_limit", "constant"]
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n.line_volume_limit_dual = n.global_constraints.at["lv_limit", "mu"]
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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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