update config and script
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@ -410,18 +410,13 @@ sector:
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2045: 0.8
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2050: 1.0
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district_heating_loss: 0.15
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# check these numbers!
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forward_temperature:
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default: 90
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DK: 70
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SE: 70
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NO: 70
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FI: 70
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DE: 90 #C
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DK: 60 #C
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return_temperature:
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default: 50
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DK: 40
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SE: 40
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NO: 40
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FI: 40
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DE: 50 #C
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DK: 40 #C
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heat_source_cooling: 6 #K
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heat_pump_cop_approximation:
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refrigerant: ammonia
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@ -242,9 +242,11 @@ rule build_cop_profiles:
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"sector", "district_heating", "heat_pump_cop_approximation"
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),
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heat_pump_sources=config_provider("sector", "heat_pump_sources"),
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snapshots=config_provider("snapshots"),
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input:
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temp_soil_total=resources("temp_soil_total_elec_s{simpl}_{clusters}.nc"),
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temp_air_total=resources("temp_air_total_elec_s{simpl}_{clusters}.nc"),
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regions_onshore=resources("regions_onshore_elec_s{simpl}_{clusters}.geojson"),
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output:
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cop_profiles=resources("cop_profiles_elec_s{simpl}_{clusters}.nc"),
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resources:
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@ -8,6 +8,7 @@ import sys
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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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import geopandas as gpd
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from _helpers import get_country_from_node_name, set_scenario_config
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from CentralHeatingCopApproximator import CentralHeatingCopApproximator
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from DecentralHeatingCopApproximator import DecentralHeatingCopApproximator
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@ -17,8 +18,8 @@ from scripts.definitions.heat_system_type import HeatSystemType
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def map_temperature_dict_to_onshore_regions(
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supply_temperature_by_country: dict,
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onshore_regions: xr.DataArray,
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snapshots: xr.DataArray,
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regions_onshore: pd.Index,
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snapshots: pd.DatetimeIndex,
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) -> xr.DataArray:
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"""
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Map dictionary of temperatures to onshore regions.
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@ -27,8 +28,10 @@ def map_temperature_dict_to_onshore_regions(
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----------
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supply_temperature_by_country : dictionary
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Dictionary with temperatures as values and country keys as keys. One key must be named "default"
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onshore_regions : xr.DataArray
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regions_onshore : pd.Index
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Names of onshore regions
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snapshots : pd.DatetimeIndex
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Time stamps
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Returns:
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-------
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@ -44,13 +47,13 @@ def map_temperature_dict_to_onshore_regions(
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in supply_temperature_by_country.keys()
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else supply_temperature_by_country["default"]
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)
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for node_name in onshore_regions["name"].values
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for node_name in regions_onshore.values
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]
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# pass both nodes and snapshots as dimensions to preserve correct data structure
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for _ in snapshots["time"].values
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for _ in snapshots
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],
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dims=["time", "name"],
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coords={"time": snapshots["time"], "name": onshore_regions["name"]},
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coords={"time": snapshots, "name": regions_onshore},
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)
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@ -108,19 +111,20 @@ if __name__ == "__main__":
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set_scenario_config(snakemake)
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# map forward and return temperatures specified on country-level to onshore regions
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onshore_regions: xr.DataArray = source_inlet_temperature_celsius["name"]
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regions_onshore = gpd.read_file(snakemake.input.regions_onshore)["name"]
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snapshots = pd.date_range(freq="h", **snakemake.params.snapshots)
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forward_temperature_central_heating_by_node_and_time: xr.DataArray = (
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map_temperature_dict_to_onshore_regions(
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temperature_dict=snakemake.params.forward_temperature_central_heating,
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onshore_regions=onshore_regions,
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snapshots=source_inlet_temperature_celsius["time"],
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supply_temperature_by_country=snakemake.params.forward_temperature_central_heating,
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regions_onshore=regions_onshore,
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snapshots=snapshots,
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)
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)
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return_temperature_central_heating_by_node_and_time: xr.DataArray = (
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map_temperature_dict_to_onshore_regions(
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temperature_dict=snakemake.params.return_temperature_central_heating,
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onshore_regions=onshore_regions,
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snapshots=source_inlet_temperature_celsius["time"],
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supply_temperature_by_country=snakemake.params.return_temperature_central_heating,
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regions_onshore=regions_onshore,
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snapshots=snapshots,
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)
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)
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cop_all_system_types = []
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