[pre-commit.ci] auto fixes from pre-commit.com hooks
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@ -589,7 +589,7 @@ sector:
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biogas_upgrading_cc: false
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conventional_generation:
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OCGT: gas
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solar_utility_singla_axis_tracking : true
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solar_utility_singla_axis_tracking: true
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biomass_to_liquid: false
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biosng: false
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limit_max_growth:
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@ -235,7 +235,7 @@ def load_costs(tech_costs, config, max_hours, Nyears=1.0):
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+ (1 - config["rooftop_share"]) * costs.at["solar-utility", "capital_cost"]
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)
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costs= costs.rename({'solar-utility single-axis tracking':'solar-hsat'})
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costs = costs.rename({"solar-utility single-axis tracking": "solar-hsat"})
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def costs_for_storage(store, link1, link2=None, max_hours=1.0):
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capital_cost = link1["capital_cost"] + max_hours * store["capital_cost"]
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@ -3319,11 +3319,12 @@ def remove_h2_network(n):
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if "EU H2 Store" in n.stores.index:
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n.stores.drop("EU H2 Store", inplace=True)
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def remove_solar_tracking(n):
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for tech in ['solar-hsat']:
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print('removing '+tech)
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n.mremove("Generator" , n.generators.index[n.generators.carrier==tech])
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for tech in ["solar-hsat"]:
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print("removing " + tech)
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n.mremove("Generator", n.generators.index[n.generators.carrier == tech])
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def limit_individual_line_extension(n, maxext):
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@ -31,6 +31,7 @@ import logging
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import os
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import re
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import sys
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from functools import reduce
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import numpy as np
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import pandas as pd
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@ -43,7 +44,6 @@ from _helpers import (
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set_scenario_config,
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update_config_from_wildcards,
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)
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from functools import reduce
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from pypsa.descriptors import get_activity_mask
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from pypsa.descriptors import get_switchable_as_dense as get_as_dense
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@ -124,7 +124,14 @@ def add_land_use_constraint_perfect(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", "solar rooftop", "solar-hsat", "onwind", "offwind-ac", "offwind-dc"]:
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for carrier in [
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"solar",
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"solar rooftop",
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"solar-hsat",
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"onwind",
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"offwind-ac",
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"offwind-dc",
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]:
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extendable_i = (n.generators.carrier == carrier) & n.generators.p_nom_extendable
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n.generators.loc[extendable_i, "p_nom_min"] = 0
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@ -159,7 +166,14 @@ def _add_land_use_constraint_m(n, planning_horizons, config):
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grouping_years = config["existing_capacities"]["grouping_years_power"]
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current_horizon = snakemake.wildcards.planning_horizons
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for carrier in ["solar", "solar rooftop", "solar-hsat", "onwind", "offwind-ac", "offwind-dc"]:
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for carrier in [
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"solar",
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"solar rooftop",
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"solar-hsat",
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"onwind",
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"offwind-ac",
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"offwind-dc",
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]:
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extendable_i = (n.generators.carrier == carrier) & n.generators.p_nom_extendable
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n.generators.loc[extendable_i, "p_nom_min"] = 0
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@ -199,6 +213,7 @@ def _add_land_use_constraint_m(n, planning_horizons, config):
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n.generators.p_nom_max.clip(lower=0, inplace=True)
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def add_solar_potential_constraints(n, config):
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"""
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Add constraint to make sure the sum capacity of all solar technologies (fixed, tracking, ets. ) is below the region potential.
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@ -209,52 +224,82 @@ def add_solar_potential_constraints(n, config):
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The constraint ensures that:
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solar_p_nom + solar_hsat_p_nom * 1.13 <= 10 GW
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"""
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land_use_factors= {
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'solar-hsat' : config['renewable']['solar']['capacity_per_sqkm']/config['renewable']['solar-hsat']['capacity_per_sqkm'] ,
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land_use_factors = {
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"solar-hsat": config["renewable"]["solar"]["capacity_per_sqkm"]
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/ config["renewable"]["solar-hsat"]["capacity_per_sqkm"],
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}
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gen_index = n.generators[n.generators.p_nom_extendable].index
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filters = [("solar", True), ("thermal", False), ("rooftop", False)] ## filter all utility solar generation except solar thermal
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solar = reduce(lambda gen_index, f: gen_index[gen_index.str.contains(f[0]) == f[1]], filters, gen_index)
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solar_today = n.generators[(n.generators.carrier=='solar') & (n.generators.p_nom_extendable)].index
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solar_hsat = n.generators[(n.generators.carrier=='solar-hsat') ].index
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land_use = pd.DataFrame(1, index=solar, columns=['land_use_factor'])
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filters = [
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("solar", True),
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("thermal", False),
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("rooftop", False),
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] ## filter all utility solar generation except solar thermal
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solar = reduce(
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lambda gen_index, f: gen_index[gen_index.str.contains(f[0]) == f[1]],
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filters,
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gen_index,
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)
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solar_today = n.generators[
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(n.generators.carrier == "solar") & (n.generators.p_nom_extendable)
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].index
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solar_hsat = n.generators[(n.generators.carrier == "solar-hsat")].index
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land_use = pd.DataFrame(1, index=solar, columns=["land_use_factor"])
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for key in land_use_factors.keys():
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land_use = land_use.apply(lambda x: (x*land_use_factors[key]) if key in x.name else x, axis=1)
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land_use = land_use.apply(
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lambda x: (x * land_use_factors[key]) if key in x.name else x, axis=1
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)
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rename = {"Generator-ext": "Generator"}
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if "m" in snakemake.wildcards.clusters:
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location = (
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pd.Series([' '.join(i.split(' ')[:2]) for i in n.generators.index], index=n.generators.index)
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location = pd.Series(
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[" ".join(i.split(" ")[:2]) for i in n.generators.index],
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index=n.generators.index,
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)
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ggrouper= pd.Series(n.generators.loc[solar].index.rename('bus').map(location), index=n.generators.loc[solar].index,).to_xarray()
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rhs = (n.generators.loc[solar_today,"p_nom_max"]
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.groupby(n.generators.loc[solar_today].index.rename('bus').map(location)).sum() -
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n.generators.loc[solar_hsat,"p_nom_opt"]
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.groupby(n.generators.loc[solar_hsat].index.rename('bus').map(location)).sum() * land_use_factors['solar-hsat'] ).clip(lower=0)
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ggrouper = pd.Series(
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n.generators.loc[solar].index.rename("bus").map(location),
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index=n.generators.loc[solar].index,
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).to_xarray()
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rhs = (
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n.generators.loc[solar_today, "p_nom_max"]
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.groupby(n.generators.loc[solar_today].index.rename("bus").map(location))
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.sum()
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- n.generators.loc[solar_hsat, "p_nom_opt"]
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.groupby(n.generators.loc[solar_hsat].index.rename("bus").map(location))
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.sum()
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* land_use_factors["solar-hsat"]
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).clip(lower=0)
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else :
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else:
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location = (
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n.buses.location
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if "location" in n.buses.columns
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else pd.Series(n.buses.index, index=n.buses.index)
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)
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ggrouper= (n.generators.loc[solar].bus)
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rhs = (n.generators.loc[solar_today,"p_nom_max"]
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.groupby(n.generators.loc[solar_today].bus.map(location)).sum() -
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n.generators.loc[solar_hsat,"p_nom_opt"]
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.groupby(n.generators.loc[solar_hsat].bus.map(location)).sum() * land_use_factors['solar-hsat'] ).clip(lower=0)
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ggrouper = n.generators.loc[solar].bus
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rhs = (
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n.generators.loc[solar_today, "p_nom_max"]
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.groupby(n.generators.loc[solar_today].bus.map(location))
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.sum()
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- n.generators.loc[solar_hsat, "p_nom_opt"]
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.groupby(n.generators.loc[solar_hsat].bus.map(location))
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.sum()
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* land_use_factors["solar-hsat"]
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).clip(lower=0)
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lhs = (
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(n.model["Generator-p_nom"].rename(rename).loc[solar]
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*land_use.squeeze().values)
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(
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n.model["Generator-p_nom"].rename(rename).loc[solar]
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* land_use.squeeze().values
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)
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.groupby(ggrouper)
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.sum()
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)
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print('adding solar rooftop constraints...')
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print("adding solar rooftop constraints...")
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n.model.add_constraints(lhs <= rhs, name="solar_potential")
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def add_co2_sequestration_limit(n, limit=200):
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"""
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Add a global constraint on the amount of Mt CO2 that can be sequestered.
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@ -918,8 +963,7 @@ def extra_functionality(n, snapshots):
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if EQ_o := constraints["EQ"]:
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add_EQ_constraints(n, EQ_o.replace("EQ", ""))
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if config["sector"]['solar_utility_singla_axis_tracking']:
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if config["sector"]["solar_utility_singla_axis_tracking"]:
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add_solar_potential_constraints(n, config)
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add_battery_constraints(n)
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