use module structure
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@ -220,16 +220,16 @@ rule build_cop_profiles:
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heat_pump_sink_T_decentral_heating=config_provider(
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"sector", "heat_pump_sink_T_individual_heating"
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),
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forward_temperature_district_heating=config_provider(
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forward_temperature_central_heating=config_provider(
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"sector", "district_heating", "forward_temperature"
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),
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return_temperature_district_heating=config_provider(
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return_temperature_central_heating=config_provider(
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"sector", "district_heating", "return_temperature"
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),
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heat_source_cooling_district_heating=config_provider(
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heat_source_cooling_central_heating=config_provider(
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"sector", "district_heating", "heat_source_cooling"
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),
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heat_pump_cop_approximation_district_heating=config_provider(
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heat_pump_cop_approximation_central_heating=config_provider(
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"sector", "district_heating", "heat_pump_cop_approximation"
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),
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input:
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@ -257,7 +257,7 @@ rule build_cop_profiles:
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conda:
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"../envs/environment.yaml"
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script:
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"../scripts/build_cop_profiles.py"
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"../scripts/build_cop_profiles/__main__.py"
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def solar_thermal_cutout(wildcards):
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61
scripts/build_cop_profiles/BaseCopApproximator.py
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61
scripts/build_cop_profiles/BaseCopApproximator.py
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@ -0,0 +1,61 @@
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from abc import ABC, abstractmethod
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from typing import Union
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import xarray as xr
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import numpy as np
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class BaseCopApproximator(ABC):
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"""
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Abstract class for approximating the coefficient of performance (COP) of a heat pump."""
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def __init__(
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self,
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forward_temperature_celsius: Union[xr.DataArray, np.array],
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source_inlet_temperature_celsius: Union[xr.DataArray, np.array],
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):
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"""
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Initialize CopApproximator.
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Parameters:
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----------
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forward_temperature_celsius : Union[xr.DataArray, np.array]
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The forward temperature in Celsius.
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return_temperature_celsius : Union[xr.DataArray, np.array]
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The return temperature in Celsius.
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"""
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pass
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@abstractmethod
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def approximate_cop(self) -> Union[xr.DataArray, np.array]:
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"""Approximate heat pump coefficient of performance (COP).
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Returns:
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-------
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Union[xr.DataArray, np.array]
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The calculated COP values.
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"""
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pass
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def celsius_to_kelvin(t_celsius: Union[float, xr.DataArray, np.array]) -> Union[float, xr.DataArray, np.array]:
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if (np.asarray(t_celsius) > 200).any():
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raise ValueError("t_celsius > 200. Are you sure you are using the right units?")
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return t_celsius + 273.15
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def logarithmic_mean(t_hot: Union[float, xr.DataArray, np.ndarray], t_cold: Union[float, xr.DataArray, np.ndarray]) -> Union[float, xr.DataArray, np.ndarray]:
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if (np.asarray(t_hot <= t_cold)).any():
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raise ValueError("t_hot must be greater than t_cold")
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return (t_hot - t_cold) / np.log(t_hot / t_cold)
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@staticmethod
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def celsius_to_kelvin(t_celsius: Union[float, xr.DataArray, np.array]) -> Union[float, xr.DataArray, np.array]:
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if (np.asarray(t_celsius) > 200).any():
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raise ValueError("t_celsius > 200. Are you sure you are using the right units?")
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return t_celsius + 273.15
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@staticmethod
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def logarithmic_mean(t_hot: Union[float, xr.DataArray, np.ndarray], t_cold: Union[float, xr.DataArray, np.ndarray]) -> Union[float, xr.DataArray, np.ndarray]:
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if (np.asarray(t_hot <= t_cold)).any():
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raise ValueError("t_hot must be greater than t_cold")
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return (t_hot - t_cold) / np.log(t_hot / t_cold)
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@ -1,78 +1,17 @@
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# -*- 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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For individual (decentral) heat pumps, the COP is approximated as a quatratic function of the temperature difference between source and sink, based on Staffell et al. 2012.
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For district (central) heating, the COP is approximated based on Jensen et al. 2018 and parameters from Pieper et al. 2020.
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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_air_total_elec_s<simpl>_<clusters>.nc``: Ambient air temperature (total) time series.
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Outputs:
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--------
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- ``resources/cop_air_decentral_heating_elec_s<simpl>_<clusters>.nc``: COP (air-sourced) time series (decentral heating).
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- ``resources/cop_soil_decentral_heating_elec_s<simpl>_<clusters>.nc``: COP (ground-sourced) time series (decentral heating).
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- ``resources/cop_air_central_heating_elec_s<simpl>_<clusters>.nc``: COP (air-sourced) time series (central heating).
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- ``resources/cop_soil_central_heating_elec_s<simpl>_<clusters>.nc``: COP (ground-sourced) time series (central heating).
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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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[2] Jensen et al., Proceedings of the13th IIR-Gustav Lorentzen Conference on Natural Refrigerants (2018): Heat pump COP, part 2: Generalized COP estimation of heat pump processes, https://doi.org/10.18462/iir.gl.2018.1386
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[3] Pieper et al., Energy 205 (2020): Comparison of COP estimation methods for large-scale heat pumps used in energy planning, https://doi.org/10.1016/j.energy.2020.117994
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"""
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from enum import Enum
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from typing import Union
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import numpy as np
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import xarray as xr
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from _helpers import set_scenario_config
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import numpy as np
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from BaseCopApproximator import BaseCopApproximator
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def coefficient_of_performance_individual_heating(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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def celsius_to_kelvin(
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t_celsius: Union[float, xr.DataArray, np.array]
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) -> Union[float, xr.DataArray, np.array]:
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if (np.asarray(t_celsius) > 200).any():
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raise ValueError("t_celsius > 200. Are you sure you are using the right units?")
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return t_celsius + 273.15
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def logarithmic_mean(
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t_hot: Union[float, xr.DataArray, np.ndarray],
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t_cold: Union[float, xr.DataArray, np.ndarray],
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) -> Union[float, xr.DataArray, np.ndarray]:
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if (np.asarray(t_hot <= t_cold)).any():
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raise ValueError("t_hot must be greater than t_cold")
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return (t_hot - t_cold) / np.log(t_hot / t_cold)
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class CopDistrictHeating:
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class CentralHeatingCopApproximator(BaseCopApproximator):
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"""
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Approximate the coefficient of performance (COP) for a heat pump in a central heating system (district heating).
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Uses an approximation method proposed by Jensen et al. (2018) and default parameters from Pieper et al. (2020).
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The method is based on a thermodynamic heat pump model with some hard-to-know parameters being approximated.
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"""
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def __init__(
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self,
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@ -85,7 +24,6 @@ class CopDistrictHeating:
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heat_loss: float = 0.0,
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) -> None:
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"""
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Initialize the COPProfileBuilder object.
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Parameters:
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----------
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@ -104,17 +42,17 @@ class CopDistrictHeating:
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heat_loss : float, optional
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The heat loss, by default 0.0.
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"""
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self.t_source_in = celsius_to_kelvin(source_inlet_temperature_celsius)
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self.t_sink_out = celsius_to_kelvin(forward_temperature_celsius)
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self.t_source_in_kelvin = BaseCopApproximator.celsius_to_kelvin(source_inlet_temperature_celsius)
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self.t_sink_out_kelvin = BaseCopApproximator.celsius_to_kelvin(forward_temperature_celsius)
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self.t_sink_in = celsius_to_kelvin(return_temperature_celsius)
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self.t_source_out = celsius_to_kelvin(source_outlet_temperature_celsius)
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self.t_sink_in_kelvin = BaseCopApproximator.celsius_to_kelvin(return_temperature_celsius)
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self.t_source_out = BaseCopApproximator.celsius_to_kelvin(source_outlet_temperature_celsius)
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self.isentropic_efficiency_compressor = isentropic_compressor_efficiency
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self.isentropic_efficiency_compressor_kelvin = isentropic_compressor_efficiency
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self.heat_loss = heat_loss
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self.delta_t_pinch = delta_t_pinch_point
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def cop(self) -> Union[xr.DataArray, np.array]:
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def approximate_cop(self) -> Union[xr.DataArray, np.array]:
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"""
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Calculate the coefficient of performance (COP) for the system.
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@ -127,7 +65,7 @@ class CopDistrictHeating:
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(
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1
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+ (self.delta_t_refrigerant_sink + self.delta_t_pinch)
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/ self.t_sink_mean
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/ self.t_sink_mean_kelvin
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)
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/ (
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1
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@ -139,28 +77,27 @@ class CopDistrictHeating:
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/ self.delta_t_lift
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)
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)
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* self.isentropic_efficiency_compressor
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* self.isentropic_efficiency_compressor_kelvin
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* (1 - self.ratio_evaporation_compression_work)
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+ 1
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- self.isentropic_efficiency_compressor
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- self.isentropic_efficiency_compressor_kelvin
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- self.heat_loss
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)
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@property
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def t_sink_mean(self) -> Union[xr.DataArray, np.array]:
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def t_sink_mean_kelvin(self) -> Union[xr.DataArray, np.array]:
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"""
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Calculate the logarithmic mean temperature difference between the cold
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and hot sinks.
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Calculate the logarithmic mean temperature difference between the cold and hot sinks.
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Returns
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-------
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Union[xr.DataArray, np.array]
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The mean temperature difference.
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"""
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return logarithmic_mean(t_cold=self.t_sink_in, t_hot=self.t_sink_out)
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return BaseCopApproximator.logarithmic_mean(t_cold=self.t_sink_in_kelvin, t_hot=self.t_sink_out_kelvin)
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@property
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def t_source_mean(self) -> Union[xr.DataArray, np.array]:
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def t_source_mean_kelvin(self) -> Union[xr.DataArray, np.array]:
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"""
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Calculate the logarithmic mean temperature of the heat source.
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@ -169,20 +106,19 @@ class CopDistrictHeating:
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Union[xr.DataArray, np.array]
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The mean temperature of the heat source.
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"""
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return logarithmic_mean(t_hot=self.t_source_in, t_cold=self.t_source_out)
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return BaseCopApproximator.logarithmic_mean(t_hot=self.t_source_in_kelvin, t_cold=self.t_source_out)
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@property
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def delta_t_lift(self) -> Union[xr.DataArray, np.array]:
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"""
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Calculate the temperature lift as the difference between the
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logarithmic sink and source temperatures.
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Calculate the temperature lift as the difference between the logarithmic sink and source temperatures.
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Returns
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-------
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Union[xr.DataArray, np.array]
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The temperature difference between the sink and source.
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"""
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return self.t_sink_mean - self.t_source_mean
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return self.t_sink_mean_kelvin - self.t_source_mean_kelvin
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@property
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def ideal_lorenz_cop(self) -> Union[xr.DataArray, np.array]:
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@ -196,14 +132,14 @@ class CopDistrictHeating:
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-------
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np.array
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The ideal Lorenz COP.
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"""
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return self.t_sink_mean / self.delta_t_lift
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return self.t_sink_mean_kelvin / self.delta_t_lift
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@property
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def delta_t_refrigerant_source(self) -> Union[xr.DataArray, np.array]:
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"""
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Calculate the temperature difference between the refrigerant source
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inlet and outlet.
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Calculate the temperature difference between the refrigerant source inlet and outlet.
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Returns
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-------
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@ -211,14 +147,13 @@ class CopDistrictHeating:
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The temperature difference between the refrigerant source inlet and outlet.
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"""
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return self._approximate_delta_t_refrigerant_source(
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delta_t_source=self.t_source_in - self.t_source_out
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delta_t_source=self.t_source_in_kelvin - self.t_source_out
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)
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@property
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def delta_t_refrigerant_sink(self) -> Union[xr.DataArray, np.array]:
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"""
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Temperature difference between the refrigerant and the sink based on
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approximation.
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Temperature difference between the refrigerant and the sink based on approximation.
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Returns
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-------
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@ -230,8 +165,7 @@ class CopDistrictHeating:
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@property
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def ratio_evaporation_compression_work(self) -> Union[xr.DataArray, np.array]:
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"""
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Calculate the ratio of evaporation to compression work based on
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approximation.
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Calculate the ratio of evaporation to compression work based on approximation.
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Returns
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-------
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@ -239,7 +173,7 @@ class CopDistrictHeating:
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The calculated ratio of evaporation to compression work.
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"""
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return self._ratio_evaporation_compression_work_approximation()
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@property
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def delta_t_sink(self) -> Union[xr.DataArray, np.array]:
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"""
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@ -250,14 +184,13 @@ class CopDistrictHeating:
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Union[xr.DataArray, np.array]
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The temperature difference at the sink.
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"""
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return self.t_sink_out - self.t_sink_in
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return self.t_sink_out_kelvin - self.t_sink_in_kelvin
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def _approximate_delta_t_refrigerant_source(
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self, delta_t_source: Union[xr.DataArray, np.array]
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) -> Union[xr.DataArray, np.array]:
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"""
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Approximates the temperature difference between the refrigerant and the
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source.
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Approximates the temperature difference between the refrigerant and the source.
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Parameters
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----------
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@ -267,7 +200,7 @@ class CopDistrictHeating:
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Returns
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-------
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Union[xr.DataArray, np.array]
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The approximate temperature difference for the refrigerant source.
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The approximate temperature difference between the refrigerant and heat source.
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"""
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return delta_t_source / 2
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@ -279,7 +212,7 @@ class CopDistrictHeating:
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c: float = {"ammonia": 0.016, "isobutane": 2.4},
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) -> Union[xr.DataArray, np.array]:
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"""
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Approximates the temperature difference at the refrigerant sink.
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Approximates the temperature difference between the refrigerant and heat sink.
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Parameters:
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----------
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@ -295,7 +228,7 @@ class CopDistrictHeating:
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Returns:
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-------
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Union[xr.DataArray, np.array]
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The approximate temperature difference at the refrigerant sink.
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The approximate temperature difference between the refrigerant and heat sink.
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Notes:
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------
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@ -303,6 +236,7 @@ class CopDistrictHeating:
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The approximate temperature difference at the refrigerant sink is calculated using the following formula:
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a * (t_sink_out - t_source_out + 2 * delta_t_pinch) + b * delta_t_sink + c
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"""
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if refrigerant not in a.keys():
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raise ValueError(
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@ -310,7 +244,7 @@ class CopDistrictHeating:
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)
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return (
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a[refrigerant]
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* (self.t_sink_out - self.t_source_out + 2 * self.delta_t_pinch)
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* (self.t_sink_out_kelvin - self.t_source_out + 2 * self.delta_t_pinch)
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+ b[refrigerant] * self.delta_t_sink
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+ c[refrigerant]
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)
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@ -339,7 +273,7 @@ class CopDistrictHeating:
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Returns:
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-------
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Union[xr.DataArray, np.array]
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The calculated ratio of evaporation to compression work.
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The approximated ratio of evaporation to compression work.
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Notes:
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------
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@ -354,44 +288,8 @@ class CopDistrictHeating:
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)
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return (
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a[refrigerant]
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* (self.t_sink_out - self.t_source_out + 2 * self.delta_t_pinch)
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* (self.t_sink_out_kelvin - self.t_source_out + 2 * self.delta_t_pinch)
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+ b[refrigerant] * self.delta_t_sink
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+ c[refrigerant]
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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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for source in ["air", "soil"]:
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source_T = xr.open_dataarray(snakemake.input[f"temp_{source}_total"])
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delta_T = snakemake.params.heat_pump_sink_T_decentral_heating - source_T
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|
||||
cop_individual_heating = coefficient_of_performance_individual_heating(
|
||||
delta_T, source
|
||||
)
|
||||
cop_individual_heating.to_netcdf(
|
||||
snakemake.output[f"cop_{source}_decentral_heating"]
|
||||
)
|
||||
|
||||
cop_district_heating = CopDistrictHeating(
|
||||
forward_temperature_celsius=snakemake.params.forward_temperature_district_heating,
|
||||
return_temperature_celsius=snakemake.params.return_temperature_district_heating,
|
||||
source_inlet_temperature_celsius=source_T,
|
||||
source_outlet_temperature_celsius=source_T
|
||||
- snakemake.params.heat_source_cooling_district_heating,
|
||||
).cop()
|
||||
|
||||
cop_district_heating.to_netcdf(
|
||||
snakemake.output[f"cop_{source}_central_heating"]
|
||||
)
|
@ -0,0 +1,79 @@
|
||||
|
||||
|
||||
|
||||
from typing import Union
|
||||
import xarray as xr
|
||||
import numpy as np
|
||||
|
||||
from BaseCopApproximator import BaseCopApproximator
|
||||
|
||||
class DecentralHeatingCopApproximator(BaseCopApproximator):
|
||||
"""
|
||||
Approximate the coefficient of performance (COP) for a heat pump in a decentral heating system (individual/household heating).
|
||||
|
||||
Uses a quadratic regression on the temperature difference between the source and sink based on empirical data proposed by Staffell et al. 2012 .
|
||||
|
||||
References
|
||||
----------
|
||||
[1] Staffell et al., Energy & Environmental Science 11 (2012): A review of domestic heat pumps, https://doi.org/10.1039/C2EE22653G.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
forward_temperature_celsius: Union[xr.DataArray, np.array],
|
||||
source_inlet_temperature_celsius: Union[xr.DataArray, np.array],
|
||||
source_type: str
|
||||
):
|
||||
"""
|
||||
Initialize the COPProfileBuilder object.
|
||||
|
||||
Parameters:
|
||||
----------
|
||||
forward_temperature_celsius : Union[xr.DataArray, np.array]
|
||||
The forward temperature in Celsius.
|
||||
return_temperature_celsius : Union[xr.DataArray, np.array]
|
||||
The return temperature in Celsius.
|
||||
source: str
|
||||
The source of the heat pump. Must be either 'air' or 'soil'
|
||||
"""
|
||||
|
||||
self.delta_t = forward_temperature_celsius - source_inlet_temperature_celsius
|
||||
if source_type not in ["air", "soil"]:
|
||||
raise ValueError("'source' must be one of ['air', 'soil']")
|
||||
else:
|
||||
self.source_type = source_type
|
||||
|
||||
def approximate_cop(self) -> Union[xr.DataArray, np.array]:
|
||||
"""
|
||||
Compute output of quadratic regression for air-/ground-source heat pumps.
|
||||
|
||||
Calls the appropriate method depending on `source`."""
|
||||
if self.source_type == "air":
|
||||
return self._approximate_cop_air_source()
|
||||
elif self.source_type == "soil":
|
||||
return self._approximate_cop_ground_source()
|
||||
|
||||
def _approximate_cop_air_source(self) -> Union[xr.DataArray, np.array]:
|
||||
"""
|
||||
Evaluate quadratic regression for an air-sourced heat pump.
|
||||
|
||||
COP = 6.81 - 0.121 * delta_T + 0.000630 * delta_T^2
|
||||
|
||||
Returns
|
||||
-------
|
||||
Union[xr.DataArray, np.array]
|
||||
The calculated COP values."""
|
||||
return 6.81 - 0.121 * self.delta_t + 0.000630 * self.delta_t**2
|
||||
|
||||
def _approximate_cop_ground_source(self) -> Union[xr.DataArray, np.array]:
|
||||
"""
|
||||
Evaluate quadratic regression for a ground-sourced heat pump.
|
||||
|
||||
COP = 8.77 - 0.150 * delta_T + 0.000734 * delta_T^2
|
||||
|
||||
Returns
|
||||
-------
|
||||
Union[xr.DataArray, np.array]
|
||||
The calculated COP values."""
|
||||
return 8.77 - 0.150 * self.delta_t + 0.000734 * self.delta_t**2
|
||||
|
42
scripts/build_cop_profiles/__main__.py
Normal file
42
scripts/build_cop_profiles/__main__.py
Normal file
@ -0,0 +1,42 @@
|
||||
|
||||
|
||||
import xarray as xr
|
||||
import numpy as np
|
||||
from CentralHeatingCopApproximator import CentralHeatingCopApproximator
|
||||
from DecentralHeatingCopApproximator import DecentralHeatingCopApproximator
|
||||
from _helpers import set_scenario_config
|
||||
|
||||
if __name__ == "__main__":
|
||||
if "snakemake" not in globals():
|
||||
from _helpers import mock_snakemake
|
||||
|
||||
snakemake = mock_snakemake(
|
||||
"build_cop_profiles",
|
||||
simpl="",
|
||||
clusters=48,
|
||||
)
|
||||
|
||||
set_scenario_config(snakemake)
|
||||
|
||||
for source_type in ["air", "soil"]:
|
||||
# source inlet temperature (air/soil) is based on weather data
|
||||
source_inlet_temperature_celsius = xr.open_dataarray(snakemake.input[f"temp_{source_type}_total"])
|
||||
|
||||
# Approximate COP for decentral (individual) heating
|
||||
cop_individual_heating = DecentralHeatingCopApproximator(
|
||||
forward_temperature_celsius=snakemake.params.heat_pump_sink_T_decentral_heating,
|
||||
source_inlet_temperature_celsius=source_inlet_temperature_celsius,
|
||||
source_type=source_type
|
||||
).approximate_cop()
|
||||
cop_individual_heating.to_netcdf(snakemake.output[f"cop_{source_type}_decentral_heating"])
|
||||
|
||||
# Approximate COP for central (district) heating
|
||||
cop_central_heating = CentralHeatingCopApproximator(
|
||||
forward_temperature_celsius=snakemake.params.forward_temperature_central_heating,
|
||||
return_temperature_celsius=snakemake.params.return_temperature_central_heating,
|
||||
source_inlet_temperature_celsius=source_inlet_temperature_celsius,
|
||||
source_outlet_temperature_celsius=source_inlet_temperature_celsius - snakemake.params.heat_source_cooling_central_heating,
|
||||
).approximate_cop()
|
||||
cop_central_heating.to_netcdf(snakemake.output[f"cop_{source_type}_central_heating"])
|
||||
|
||||
|
Loading…
Reference in New Issue
Block a user