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2
doc/configtables/sector.csv
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@ -160,4 +160,4 @@ enhanced_geothermal,,,
#NAME?,--,int,The maximum hours the reservoir can be charged under flexible operation
#NAME?,--,float,The maximum boost in power output under flexible operation
#NAME?,--,"{true, false}",Add option for variable capacity factor (see Ricks et al. 2024)
#NAME?,--,float,Share of sourced heat that is replenished by the earth's core (see details in `build_egs_potentials.py <https://github.com/PyPSA/pypsa-eur-sec/blob/master/scripts/build_egs_potentials.py>`_)
#NAME?,--,float,Share of sourced heat that is replenished by the earth's core (see details in `build_egs_potentials.py <https://github.com/PyPSA/pypsa-eur-sec/blob/master/scripts/build_egs_potentials.py>`_)

1 Unit Values Description
160 #NAME? -- int The maximum hours the reservoir can be charged under flexible operation
161 #NAME? -- float The maximum boost in power output under flexible operation
162 #NAME? -- {true, false} Add option for variable capacity factor (see Ricks et al. 2024)
163 #NAME? -- float Share of sourced heat that is replenished by the earth's core (see details in `build_egs_potentials.py <https://github.com/PyPSA/pypsa-eur-sec/blob/master/scripts/build_egs_potentials.py>`_)

76
scripts/build_cop_profiles/BaseCopApproximator.py
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@ -1,32 +1,39 @@
# -*- coding: utf-8 -*-
from abc import ABC, abstractmethod
from typing import Union
import xarray as xr
import numpy as np
import xarray as xr
class BaseCopApproximator(ABC):
"""
Abstract class for approximating the coefficient of performance (COP) of a heat pump."""
def __init__(
self,
forward_temperature_celsius: Union[xr.DataArray, np.array],
source_inlet_temperature_celsius: Union[xr.DataArray, np.array],
):
"""
Initialize CopApproximator.
Abstract class for approximating the coefficient of performance (COP) of a
heat pump.
"""
def __init__(
self,
forward_temperature_celsius: Union[xr.DataArray, np.array],
source_inlet_temperature_celsius: Union[xr.DataArray, np.array],
):
"""
Initialize CopApproximator.
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.
"""
pass
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.
"""
pass
@abstractmethod
def approximate_cop(self) -> Union[xr.DataArray, np.array]:
"""Approximate heat pump coefficient of performance (COP).
"""
Approximate heat pump coefficient of performance (COP).
Returns:
-------
@ -34,28 +41,39 @@ class BaseCopApproximator(ABC):
The calculated COP values.
"""
pass
def celsius_to_kelvin(t_celsius: Union[float, xr.DataArray, np.array]) -> Union[float, xr.DataArray, np.array]:
def celsius_to_kelvin(
t_celsius: Union[float, xr.DataArray, np.array]
) -> Union[float, xr.DataArray, np.array]:
if (np.asarray(t_celsius) > 200).any():
raise ValueError("t_celsius > 200. Are you sure you are using the right units?")
raise ValueError(
"t_celsius > 200. Are you sure you are using the right units?"
)
return t_celsius + 273.15
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]:
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]:
if (np.asarray(t_hot <= t_cold)).any():
raise ValueError("t_hot must be greater than t_cold")
return (t_hot - t_cold) / np.log(t_hot / t_cold)
@staticmethod
def celsius_to_kelvin(t_celsius: Union[float, xr.DataArray, np.array]) -> Union[float, xr.DataArray, np.array]:
def celsius_to_kelvin(
t_celsius: Union[float, xr.DataArray, np.array]
) -> Union[float, xr.DataArray, np.array]:
if (np.asarray(t_celsius) > 200).any():
raise ValueError("t_celsius > 200. Are you sure you are using the right units?")
raise ValueError(
"t_celsius > 200. Are you sure you are using the right units?"
)
return t_celsius + 273.15
@staticmethod
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]:
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]:
if (np.asarray(t_hot <= t_cold)).any():
raise ValueError("t_hot must be greater than t_cold")
return (t_hot - t_cold) / np.log(t_hot / t_cold)

67
scripts/build_cop_profiles/CentralHeatingCopApproximator.py
View File

@ -1,16 +1,21 @@
# -*- coding: utf-8 -*-
from typing import Union
import xarray as xr
import numpy as np
import numpy as np
import xarray as xr
from BaseCopApproximator import BaseCopApproximator
class CentralHeatingCopApproximator(BaseCopApproximator):
"""
Approximate the coefficient of performance (COP) for a heat pump in a central heating system (district heating).
Uses an approximation method proposed by Jensen et al. (2018) and default parameters from Pieper et al. (2020).
The method is based on a thermodynamic heat pump model with some hard-to-know parameters being approximated.
Approximate the coefficient of performance (COP) for a heat pump in a
central heating system (district heating).
Uses an approximation method proposed by Jensen et al. (2018) and
default parameters from Pieper et al. (2020). The method is based on
a thermodynamic heat pump model with some hard-to-know parameters
being approximated.
"""
def __init__(
@ -42,11 +47,19 @@ class CentralHeatingCopApproximator(BaseCopApproximator):
heat_loss : float, optional
The heat loss, by default 0.0.
"""
self.t_source_in_kelvin = BaseCopApproximator.celsius_to_kelvin(source_inlet_temperature_celsius)
self.t_sink_out_kelvin = BaseCopApproximator.celsius_to_kelvin(forward_temperature_celsius)
self.t_source_in_kelvin = BaseCopApproximator.celsius_to_kelvin(
source_inlet_temperature_celsius
)
self.t_sink_out_kelvin = BaseCopApproximator.celsius_to_kelvin(
forward_temperature_celsius
)
self.t_sink_in_kelvin = BaseCopApproximator.celsius_to_kelvin(return_temperature_celsius)
self.t_source_out = BaseCopApproximator.celsius_to_kelvin(source_outlet_temperature_celsius)
self.t_sink_in_kelvin = BaseCopApproximator.celsius_to_kelvin(
return_temperature_celsius
)
self.t_source_out = BaseCopApproximator.celsius_to_kelvin(
source_outlet_temperature_celsius
)
self.isentropic_efficiency_compressor_kelvin = isentropic_compressor_efficiency
self.heat_loss = heat_loss
@ -87,14 +100,17 @@ class CentralHeatingCopApproximator(BaseCopApproximator):
@property
def t_sink_mean_kelvin(self) -> Union[xr.DataArray, np.array]:
"""
Calculate the logarithmic mean temperature difference between the cold and hot sinks.
Calculate the logarithmic mean temperature difference between the cold
and hot sinks.
Returns
-------
Union[xr.DataArray, np.array]
The mean temperature difference.
"""
return BaseCopApproximator.logarithmic_mean(t_cold=self.t_sink_in_kelvin, t_hot=self.t_sink_out_kelvin)
return BaseCopApproximator.logarithmic_mean(
t_cold=self.t_sink_in_kelvin, t_hot=self.t_sink_out_kelvin
)
@property
def t_source_mean_kelvin(self) -> Union[xr.DataArray, np.array]:
@ -106,12 +122,15 @@ class CentralHeatingCopApproximator(BaseCopApproximator):
Union[xr.DataArray, np.array]
The mean temperature of the heat source.
"""
return BaseCopApproximator.logarithmic_mean(t_hot=self.t_source_in_kelvin, t_cold=self.t_source_out)
return BaseCopApproximator.logarithmic_mean(
t_hot=self.t_source_in_kelvin, t_cold=self.t_source_out
)
@property
def delta_t_lift(self) -> Union[xr.DataArray, np.array]:
"""
Calculate the temperature lift as the difference between the logarithmic sink and source temperatures.
Calculate the temperature lift as the difference between the
logarithmic sink and source temperatures.
Returns
-------
@ -132,14 +151,14 @@ class CentralHeatingCopApproximator(BaseCopApproximator):
-------
np.array
The ideal Lorenz COP.
"""
return self.t_sink_mean_kelvin / self.delta_t_lift
@property
def delta_t_refrigerant_source(self) -> Union[xr.DataArray, np.array]:
"""
Calculate the temperature difference between the refrigerant source inlet and outlet.
Calculate the temperature difference between the refrigerant source
inlet and outlet.
Returns
-------
@ -153,7 +172,8 @@ class CentralHeatingCopApproximator(BaseCopApproximator):
@property
def delta_t_refrigerant_sink(self) -> Union[xr.DataArray, np.array]:
"""
Temperature difference between the refrigerant and the sink based on approximation.
Temperature difference between the refrigerant and the sink based on
approximation.
Returns
-------
@ -165,7 +185,8 @@ class CentralHeatingCopApproximator(BaseCopApproximator):
@property
def ratio_evaporation_compression_work(self) -> Union[xr.DataArray, np.array]:
"""
Calculate the ratio of evaporation to compression work based on approximation.
Calculate the ratio of evaporation to compression work based on
approximation.
Returns
-------
@ -173,7 +194,7 @@ class CentralHeatingCopApproximator(BaseCopApproximator):
The calculated ratio of evaporation to compression work.
"""
return self._ratio_evaporation_compression_work_approximation()
@property
def delta_t_sink(self) -> Union[xr.DataArray, np.array]:
"""
@ -190,7 +211,8 @@ class CentralHeatingCopApproximator(BaseCopApproximator):
self, delta_t_source: Union[xr.DataArray, np.array]
) -> Union[xr.DataArray, np.array]:
"""
Approximates the temperature difference between the refrigerant and the source.
Approximates the temperature difference between the refrigerant and the
source.
Parameters
----------
@ -212,7 +234,8 @@ class CentralHeatingCopApproximator(BaseCopApproximator):
c: float = {"ammonia": 0.016, "isobutane": 2.4},
) -> Union[xr.DataArray, np.array]:
"""
Approximates the temperature difference between the refrigerant and heat sink.
Approximates the temperature difference between the refrigerant and
heat sink.
Parameters:
----------
@ -236,7 +259,6 @@ class CentralHeatingCopApproximator(BaseCopApproximator):
The approximate temperature difference at the refrigerant sink is calculated using the following formula:
a * (t_sink_out - t_source_out + 2 * delta_t_pinch) + b * delta_t_sink + c
"""
if refrigerant not in a.keys():
raise ValueError(
@ -292,4 +314,3 @@ class CentralHeatingCopApproximator(BaseCopApproximator):
+ b[refrigerant] * self.delta_t_sink
+ c[refrigerant]
)

43
scripts/build_cop_profiles/DecentralHeatingCopApproximator.py
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@ -1,16 +1,18 @@
# -*- coding: utf-8 -*-
from typing import Union
import xarray as xr
import numpy as np
import numpy as np
import xarray as xr
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).
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
@ -22,7 +24,7 @@ class DecentralHeatingCopApproximator(BaseCopApproximator):
self,
forward_temperature_celsius: Union[xr.DataArray, np.array],
source_inlet_temperature_celsius: Union[xr.DataArray, np.array],
source_type: str
source_type: str,
):
"""
Initialize the COPProfileBuilder object.
@ -36,18 +38,20 @@ class DecentralHeatingCopApproximator(BaseCopApproximator):
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`."""
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":
@ -56,24 +60,25 @@ class DecentralHeatingCopApproximator(BaseCopApproximator):
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."""
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."""
The calculated COP values.
"""
return 8.77 - 0.150 * self.delta_t + 0.000734 * self.delta_t**2

26
scripts/build_cop_profiles/run.py
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@ -1,10 +1,11 @@
# -*- coding: utf-8 -*-
import xarray as xr
import numpy as np
import xarray as xr
from _helpers import set_scenario_config
from CentralHeatingCopApproximator import CentralHeatingCopApproximator
from DecentralHeatingCopApproximator import DecentralHeatingCopApproximator
from _helpers import set_scenario_config
if __name__ == "__main__":
if "snakemake" not in globals():
@ -19,24 +20,29 @@ if __name__ == "__main__":
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"])
# 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
source_type=source_type,
).approximate_cop()
cop_individual_heating.to_netcdf(snakemake.output[f"cop_{source_type}_decentral_heating"])
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,
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"])
cop_central_heating.to_netcdf(
snakemake.output[f"cop_{source_type}_central_heating"]
)