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prepare: move build_heat_demand closer to add_heat

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Fabian Neumann 2022-04-03 18:55:53 +02:00
parent b112da0565
commit 95d5d8f889
1 changed files with 41 additions and 44 deletions
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85
scripts/prepare_sector_network.py
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@ -573,48 +573,6 @@ def cycling_shift(df, steps=1):
def build_heat_demand(n):
# copy forward the daily average heat demand into each hour, so it can be multipled by the intraday profile
daily_space_heat_demand = xr.open_dataarray(snakemake.input.heat_demand_total).to_pandas().reindex(index=n.snapshots, method="ffill")
intraday_profiles = pd.read_csv(snakemake.input.heat_profile, index_col=0)
sectors = ["residential", "services"]
uses = ["water", "space"]
heat_demand = {}
electric_heat_supply = {}
for sector, use in product(sectors, uses):
weekday = list(intraday_profiles[f"{sector} {use} weekday"])
weekend = list(intraday_profiles[f"{sector} {use} weekend"])
weekly_profile = weekday * 5 + weekend * 2
intraday_year_profile = generate_periodic_profiles(
daily_space_heat_demand.index.tz_localize("UTC"),
nodes=daily_space_heat_demand.columns,
weekly_profile=weekly_profile
)
if use == "space":
heat_demand_shape = daily_space_heat_demand * intraday_year_profile
else:
heat_demand_shape = intraday_year_profile
heat_demand[f"{sector} {use}"] = (heat_demand_shape/heat_demand_shape.sum()).multiply(pop_weighted_energy_totals[f"total {sector} {use}"]) * 1e6
electric_heat_supply[f"{sector} {use}"] = (heat_demand_shape/heat_demand_shape.sum()).multiply(pop_weighted_energy_totals[f"electricity {sector} {use}"]) * 1e6
heat_demand = pd.concat(heat_demand, axis=1)
electric_heat_supply = pd.concat(electric_heat_supply, axis=1)
# subtract from electricity load since heat demand already in heat_demand
electric_nodes = n.loads.index[n.loads.carrier == "electricity"]
n.loads_t.p_set[electric_nodes] = n.loads_t.p_set[electric_nodes] - electric_heat_supply.groupby(level=1, axis=1).sum()[electric_nodes]
return heat_demand
# TODO checkout PyPSA-Eur script # TODO checkout PyPSA-Eur script
def prepare_costs(cost_file, USD_to_EUR, discount_rate, Nyears, lifetime): def prepare_costs(cost_file, USD_to_EUR, discount_rate, Nyears, lifetime):
@ -1294,12 +1252,53 @@ def add_land_transport(n, costs):
) )
def build_heat_demand(n):
# copy forward the daily average heat demand into each hour, so it can be multipled by the intraday profile
daily_space_heat_demand = xr.open_dataarray(snakemake.input.heat_demand_total).to_pandas().reindex(index=n.snapshots, method="ffill")
intraday_profiles = pd.read_csv(snakemake.input.heat_profile, index_col=0)
sectors = ["residential", "services"]
uses = ["water", "space"]
heat_demand = {}
electric_heat_supply = {}
for sector, use in product(sectors, uses):
weekday = list(intraday_profiles[f"{sector} {use} weekday"])
weekend = list(intraday_profiles[f"{sector} {use} weekend"])
weekly_profile = weekday * 5 + weekend * 2
intraday_year_profile = generate_periodic_profiles(
daily_space_heat_demand.index.tz_localize("UTC"),
nodes=daily_space_heat_demand.columns,
weekly_profile=weekly_profile
)
if use == "space":
heat_demand_shape = daily_space_heat_demand * intraday_year_profile
else:
heat_demand_shape = intraday_year_profile
heat_demand[f"{sector} {use}"] = (heat_demand_shape/heat_demand_shape.sum()).multiply(pop_weighted_energy_totals[f"total {sector} {use}"]) * 1e6
electric_heat_supply[f"{sector} {use}"] = (heat_demand_shape/heat_demand_shape.sum()).multiply(pop_weighted_energy_totals[f"electricity {sector} {use}"]) * 1e6
heat_demand = pd.concat(heat_demand, axis=1)
electric_heat_supply = pd.concat(electric_heat_supply, axis=1)
# subtract from electricity load since heat demand already in heat_demand
electric_nodes = n.loads.index[n.loads.carrier == "electricity"]
n.loads_t.p_set[electric_nodes] = n.loads_t.p_set[electric_nodes] - electric_heat_supply.groupby(level=1, axis=1).sum()[electric_nodes]
return heat_demand
def add_heat(n, costs): def add_heat(n, costs):
logger.info("Add heat sector") logger.info("Add heat sector")
sectors = ["residential", "services"] sectors = ["residential", "services"]
heat_demand = build_heat_demand(n)
nodes, dist_fraction, urban_fraction = create_nodes_for_heat_sector() nodes, dist_fraction, urban_fraction = create_nodes_for_heat_sector()
@ -2330,8 +2329,6 @@ if __name__ == "__main__":
if o == "biomasstransport": if o == "biomasstransport":
options["biomass_transport"] = True options["biomass_transport"] = True
heat_demand = build_heat_demand(n)
if "nodistrict" in opts: if "nodistrict" in opts:
options["district_heating"]["progress"] = 0.0 options["district_heating"]["progress"] = 0.0