79 lines
2.9 KiB
Python
79 lines
2.9 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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"""
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Build coefficient of performance (COP) time series for air- or ground-sourced
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heat pumps.
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The COP is approximated as a quatratic function of the temperature difference between source and
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sink, based on Staffell et al. 2012.
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This rule is executed in ``build_sector.smk``.
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Relevant Settings
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-----------------
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.. code:: yaml
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heat_pump_sink_T:
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Inputs:
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-------
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- ``resources/<run_name>/temp_soil_total_elec_s<simpl>_<clusters>.nc``: Soil temperature (total) time series.
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- ``resources/<run_name>/temp_soil_rural_elec_s<simpl>_<clusters>.nc``: Soil temperature (rural) time series.
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- ``resources/<run_name>/temp_soil_urban_elec_s<simpl>_<clusters>.nc``: Soil temperature (urban) time series.
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- ``resources/<run_name>/temp_air_total_elec_s<simpl>_<clusters>.nc``: Ambient air temperature (total) time series.
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- ``resources/<run_name>/temp_air_rural_elec_s<simpl>_<clusters>.nc``: Ambient air temperature (rural) time series.
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- ``resources/<run_name>/temp_air_urban_elec_s<simpl>_<clusters>.nc``: Ambient air temperature (urban) time series.
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Outputs:
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--------
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- ``resources/cop_soil_total_elec_s<simpl>_<clusters>.nc``: COP (ground-sourced) time series (total).
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- ``resources/cop_soil_rural_elec_s<simpl>_<clusters>.nc``: COP (ground-sourced) time series (rural).
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- ``resources/cop_soil_urban_elec_s<simpl>_<clusters>.nc``: COP (ground-sourced) time series (urban).
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- ``resources/cop_air_total_elec_s<simpl>_<clusters>.nc``: COP (air-sourced) time series (total).
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- ``resources/cop_air_rural_elec_s<simpl>_<clusters>.nc``: COP (air-sourced) time series (rural).
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- ``resources/cop_air_urban_elec_s<simpl>_<clusters>.nc``: COP (air-sourced) time series (urban).
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References
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----------
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[1] Staffell et al., Energy & Environmental Science 11 (2012): A review of domestic heat pumps, https://doi.org/10.1039/C2EE22653G.
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"""
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import xarray as xr
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from _helpers import set_scenario_config
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def coefficient_of_performance(delta_T, source="air"):
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if source == "air":
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return 6.81 - 0.121 * delta_T + 0.000630 * delta_T**2
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elif source == "soil":
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return 8.77 - 0.150 * delta_T + 0.000734 * delta_T**2
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else:
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raise NotImplementedError("'source' must be one of ['air', 'soil']")
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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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for area in ["total", "urban", "rural"]:
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for source in ["air", "soil"]:
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source_T = xr.open_dataarray(snakemake.input[f"temp_{source}_{area}"])
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delta_T = snakemake.params.heat_pump_sink_T - source_T
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cop = coefficient_of_performance(delta_T, source)
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cop.to_netcdf(snakemake.output[f"cop_{source}_{area}"])
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