77 lines
2.7 KiB
Python
77 lines
2.7 KiB
Python
# -*- coding: utf-8 -*-
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# SPDX-FileCopyrightText: : 2020-2024 The PyPSA-Eur Authors
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#
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# SPDX-License-Identifier: MIT
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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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from _helpers import set_scenario_config
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from CentralHeatingCopApproximator import CentralHeatingCopApproximator
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from DecentralHeatingCopApproximator import DecentralHeatingCopApproximator
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def get_cop(
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heat_system_type: str,
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heat_source: str,
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source_inlet_temperature_celsius: xr.DataArray,
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) -> xr.DataArray:
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if heat_system_type == "decentral":
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return DecentralHeatingCopApproximator(
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forward_temperature_celsius=snakemake.params.heat_pump_sink_T_decentral_heating,
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source_inlet_temperature_celsius=source_inlet_temperature_celsius,
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source_type=heat_source,
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).approximate_cop()
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elif heat_system_type == "central":
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return CentralHeatingCopApproximator(
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forward_temperature_celsius=snakemake.params.forward_temperature_central_heating,
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return_temperature_celsius=snakemake.params.return_temperature_central_heating,
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source_inlet_temperature_celsius=source_inlet_temperature_celsius,
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source_outlet_temperature_celsius=source_inlet_temperature_celsius
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- snakemake.params.heat_source_cooling_central_heating,
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).approximate_cop()
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else:
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raise ValueError(
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f"Invalid heat system type '{heat_system_type}'. Must be one of ['decentral', 'central']"
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)
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if __name__ == "__main__":
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if "snakemake" not in globals():
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from _helpers import mock_snakemake
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snakemake = mock_snakemake(
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"build_cop_profiles",
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simpl="",
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clusters=48,
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)
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set_scenario_config(snakemake)
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cop_all_system_types = []
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for heat_system_type, heat_sources in snakemake.params.heat_pump_sources.items():
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cop_this_system_type = []
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for heat_source in heat_sources:
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source_inlet_temperature_celsius = xr.open_dataarray(
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snakemake.input[f"temp_{heat_source.replace('ground', 'soil')}_total"]
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)
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cop_da = get_cop(
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heat_system_type=heat_system_type,
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heat_source=heat_source,
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source_inlet_temperature_celsius=source_inlet_temperature_celsius,
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)
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cop_this_system_type.append(cop_da)
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cop_all_system_types.append(
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xr.concat(
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cop_this_system_type, dim=pd.Index(heat_sources, name="heat_source")
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)
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)
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cop_dataarray = xr.concat(
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cop_all_system_types,
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dim=pd.Index(snakemake.params.heat_pump_sources.keys(), name="heat_system"),
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)
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cop_dataarray.to_netcdf(snakemake.output.cop_profiles)
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