pypsa-eur/scripts/solve_network.py

"""Solve network."""

import pypsa
import numpy as np

from vresutils.benchmark import memory_logger
from helper import override_component_attrs, update_config_with_sector_opts

import logging
logger = logging.getLogger(__name__)
pypsa.pf.logger.setLevel(logging.WARNING)


def add_land_use_constraint(n):

    if 'm' in snakemake.wildcards.clusters:
        _add_land_use_constraint_m(n)
    else:
        _add_land_use_constraint(n)


def _add_land_use_constraint(n):
    #warning: this will miss existing offwind which is not classed AC-DC and has carrier 'offwind'

    for carrier in ['solar', 'onwind', 'offwind-ac', 'offwind-dc']:
        existing = n.generators.loc[n.generators.carrier==carrier,"p_nom"].groupby(n.generators.bus.map(n.buses.location)).sum()
        existing.index += " " + carrier + "-" + snakemake.wildcards.planning_horizons
        n.generators.loc[existing.index,"p_nom_max"] -= existing

    n.generators.p_nom_max.clip(lower=0, inplace=True)


def _add_land_use_constraint_m(n):
    # if generators clustering is lower than network clustering, land_use accounting is at generators clusters

    planning_horizons = snakemake.config["scenario"]["planning_horizons"]
    grouping_years = snakemake.config["existing_capacities"]["grouping_years"]
    current_horizon = snakemake.wildcards.planning_horizons

    for carrier in ['solar', 'onwind', 'offwind-ac', 'offwind-dc']:

        existing = n.generators.loc[n.generators.carrier==carrier,"p_nom"]
        ind = list(set([i.split(sep=" ")[0] + ' ' + i.split(sep=" ")[1] for i in existing.index]))

        previous_years = [
            str(y) for y in
            planning_horizons + grouping_years
            if y < int(snakemake.wildcards.planning_horizons)
        ]

        for p_year in previous_years:
            ind2 = [i for i in ind if i + " " + carrier + "-" + p_year in existing.index]
            sel_current = [i + " " + carrier + "-" + current_horizon for i in ind2]
            sel_p_year = [i + " " + carrier + "-" + p_year for i in ind2]
            n.generators.loc[sel_current, "p_nom_max"] -= existing.loc[sel_p_year].rename(lambda x: x[:-4] + current_horizon)

    n.generators.p_nom_max.clip(lower=0, inplace=True)


def prepare_network(n, solve_opts=None):

    if 'clip_p_max_pu' in solve_opts:
        for df in (n.generators_t.p_max_pu, n.generators_t.p_min_pu, n.storage_units_t.inflow):
            df.where(df>solve_opts['clip_p_max_pu'], other=0., inplace=True)

    if solve_opts.get('load_shedding'):
        # intersect between macroeconomic and surveybased willingness to pay
        # http://journal.frontiersin.org/article/10.3389/fenrg.2015.00055/full
        n.add("Carrier", "Load")
        n.madd("Generator", n.buses.index, " load",
               bus=n.buses.index,
               carrier='load',
               sign=1e-3, # Adjust sign to measure p and p_nom in kW instead of MW
               marginal_cost=1e2, # Eur/kWh
               p_nom=1e9 # kW
        )

    if solve_opts.get('noisy_costs'):
        for t in n.iterate_components():
            #if 'capital_cost' in t.df:
            #    t.df['capital_cost'] += 1e1 + 2.*(np.random.random(len(t.df)) - 0.5)
            if 'marginal_cost' in t.df:
                np.random.seed(174)
                t.df['marginal_cost'] += 1e-2 + 2e-3 * (np.random.random(len(t.df)) - 0.5)

        for t in n.iterate_components(['Line', 'Link']):
            np.random.seed(123)
            t.df['capital_cost'] += (1e-1 + 2e-2 * (np.random.random(len(t.df)) - 0.5)) * t.df['length']

    if solve_opts.get('nhours'):
        nhours = solve_opts['nhours']
        n.set_snapshots(n.snapshots[:nhours])
        n.snapshot_weightings[:] = 8760./nhours

    if snakemake.config['foresight'] == 'myopic':
        add_land_use_constraint(n)

    return n


def add_battery_constraints(n):
    """
    Add constraints to ensure that the ratio between the charger and
    discharger.
    1 * charger_size - efficiency * discharger_size = 0
    """
    nodes = n.buses.index[n.buses.carrier == "battery"]
    if nodes.empty:
        return
    link_p_nom = n.model["Link-p_nom"]
    eff = n.links.efficiency[nodes + " discharger"].values
    lhs = link_p_nom.loc[nodes + ' charger'] - link_p_nom.loc[nodes + ' discharger'] * eff
    n.model.add_constraints(lhs == 0, name="Link-charger_ratio")


def add_chp_constraints(n):

    electric = (n.links.index.str.contains("urban central")
                & n.links.index.str.contains("CHP")
                & n.links.index.str.contains("electric"))
    heat = (n.links.index.str.contains("urban central")
            & n.links.index.str.contains("CHP")
            & n.links.index.str.contains("heat"))

    electric_ext = n.links[electric].query("p_nom_extendable").index
    heat_ext = n.links[heat].query("p_nom_extendable").index

    electric_fix = n.links[electric].query("~p_nom_extendable").index
    heat_fix = n.links[heat].query("~p_nom_extendable").index

    p = n.model["Link-p"] # dimension: [time, link]

    # output ratio between heat and electricity and top_iso_fuel_line for extendable
    if not electric_ext.empty:
        p_nom = n.model["Link-p_nom"]

        lhs = (p_nom.loc[electric_ext] * (n.links.p_nom_ratio * n.links.efficiency)[electric_ext].values -
               p_nom.loc[heat_ext] * n.links.efficiency[heat_ext].values)
        n.model.add_constraints(lhs == 0, name='chplink-fix_p_nom_ratio')

        rename = {"Link-ext": "Link"}
        lhs = p.loc[:, electric_ext] + p.loc[:, heat_ext] - p_nom.rename(rename).loc[electric_ext]
        n.model.add_constraints(lhs <= 0, name='chplink-top_iso_fuel_line_ext')


    # top_iso_fuel_line for fixed
    if not electric_fix.empty:
        lhs = p.loc[:, electric_fix] + p.loc[:, heat_fix]
        rhs = n.links.p_nom[electric_fix]
        n.model.add_constraints(lhs <= rhs, name='chplink-top_iso_fuel_line_fix')

    # back-pressure
    if not electric.empty:
        lhs = (p.loc[:, heat] * (n.links.efficiency[heat] * n.links.c_b[electric].values) -
               p.loc[:, electric] * n.links.efficiency[electric])
        n.model.add_constraints(lhs <= rhs, name='chplink-backpressure')


def add_pipe_retrofit_constraint(n):
    """Add constraint for retrofitting existing CH4 pipelines to H2 pipelines."""
    gas_pipes_i = n.links.query("carrier == 'gas pipeline' and p_nom_extendable").index
    h2_retrofitted_i = n.links.query("carrier == 'H2 pipeline retrofitted' and p_nom_extendable").index

    if h2_retrofitted_i.empty or gas_pipes_i.empty:
        return

    p_nom = n.model["Link-p_nom"]

    CH4_per_H2 = 1 / n.config["sector"]["H2_retrofit_capacity_per_CH4"]
    lhs = p_nom.loc[gas_pipes_i] + CH4_per_H2 * p_nom.loc[h2_retrofitted_i]
    rhs = n.links.p_nom[gas_pipes_i].rename_axis("Link-ext")

    n.model.add_constraints(lhs == rhs, name='Link-pipe_retrofit')



def add_co2_sequestration_limit(n, sns):

    co2_stores = n.stores.loc[n.stores.carrier=='co2 stored'].index

    if co2_stores.empty or 'Store-e' not in n.model.variables:
        return

    limit = n.config["sector"].get("co2_sequestration_potential", 200) * 1e6
    for o in opts:
        if not "seq" in o: continue
        limit = float(o[o.find("seq")+3:]) * 1e6
        break

    n.add("GlobalConstraint", 'co2_sequestration_limit', sense="<=", constant=limit,
          type=np.nan, carrier_attribute="co2 stored")


def extra_functionality(n, snapshots):
    add_battery_constraints(n)
    add_pipe_retrofit_constraint(n)
    # add_co2_sequestration_limit(n, snapshots)


def solve_network(n, config, opts="", **kwargs):
    options = config['solving']['solver']['options']
    solver_options = config['solving']["solver_options"][options] if options else None
    solver_name = config['solving']['solver']['name']
    cf_solving = config["solving"]["options"]
    track_iterations = cf_solving.get("track_iterations", False)
    min_iterations = cf_solving.get("min_iterations", 4)
    max_iterations = cf_solving.get("max_iterations", 6)

    # add to network for extra_functionality
    n.config = config
    n.opts = opts

    skip_iterations = cf_solving.get("skip_iterations", False)
    if not n.lines.s_nom_extendable.any():
        skip_iterations = True
        logger.info("No expandable lines found. Skipping iterative solving.")

    if skip_iterations:
        n.optimize(
            solver_name=solver_name,
            solver_options=solver_options,
            extra_functionality=extra_functionality,
            **kwargs,
        )
    else:
        n.optimize.optimize_transmission_expansion_iteratively(
            solver_name=solver_name,
            solver_options=solver_options,
            track_iterations=track_iterations,
            min_iterations=min_iterations,
            max_iterations=max_iterations,
            extra_functionality=extra_functionality,
            **kwargs,
        )

    return n



if __name__ == "__main__":
    if 'snakemake' not in globals():
        from helper import mock_snakemake
        snakemake = mock_snakemake(
            'solve_network',
            simpl='',
            opts="",
            clusters="45",
            lv=1.0,
            sector_opts='Co2L0-3H-T-H-B-I-A-solar+p3-dist1',
            planning_horizons="2050",
        )

    logging.basicConfig(filename=snakemake.log.python,
                        level=snakemake.config['logging_level'])

    update_config_with_sector_opts(snakemake.config, snakemake.wildcards.sector_opts)

    tmpdir = snakemake.config['solving'].get('tmpdir')
    if tmpdir is not None:
        from pathlib import Path
        Path(tmpdir).mkdir(parents=True, exist_ok=True)
    opts = snakemake.wildcards.sector_opts.split('-')
    solve_opts = snakemake.config['solving']['options']

    fn = getattr(snakemake.log, 'memory', None)
    with memory_logger(filename=fn, interval=30.) as mem:

        overrides = override_component_attrs(snakemake.input.overrides)
        n = pypsa.Network(snakemake.input.network, override_component_attrs=overrides)

        n = prepare_network(n, solve_opts)

        n = solve_network(n, config=snakemake.config, opts=opts,
                          solver_dir=tmpdir,
                          solver_logfile=snakemake.log.solver)

        if "lv_limit" in n.global_constraints.index:
            n.line_volume_limit = n.global_constraints.at["lv_limit", "constant"]
            n.line_volume_limit_dual = n.global_constraints.at["lv_limit", "mu"]

        n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
        n.export_to_netcdf(snakemake.output[0])

    logger.info("Maximum memory usage: {}".format(mem.mem_usage))