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AmosSchledorn 2024-07-24 15:03:44 +02:00
parent 0e6a7377ea
commit 3fac27ff27
5 changed files with 228 additions and 148 deletions
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10
rules/build_sector.smk
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@ -220,16 +220,16 @@ rule build_cop_profiles:
heat_pump_sink_T_decentral_heating=config_provider(
"sector", "heat_pump_sink_T_individual_heating"
),
forward_temperature_district_heating=config_provider(
forward_temperature_central_heating=config_provider(
"sector", "district_heating", "forward_temperature"
),
return_temperature_district_heating=config_provider(
return_temperature_central_heating=config_provider(
"sector", "district_heating", "return_temperature"
),
heat_source_cooling_district_heating=config_provider(
heat_source_cooling_central_heating=config_provider(
"sector", "district_heating", "heat_source_cooling"
),
heat_pump_cop_approximation_district_heating=config_provider(
heat_pump_cop_approximation_central_heating=config_provider(
"sector", "district_heating", "heat_pump_cop_approximation"
),
input:
@ -257,7 +257,7 @@ rule build_cop_profiles:
conda:
"../envs/environment.yaml"
script:
"../scripts/build_cop_profiles.py"
"../scripts/build_cop_profiles/__main__.py"
def solar_thermal_cutout(wildcards):

61
scripts/build_cop_profiles/BaseCopApproximator.py Normal file
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@ -0,0 +1,61 @@
from abc import ABC, abstractmethod
from typing import Union
import xarray as xr
import numpy as np
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.
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).
Returns:
-------
Union[xr.DataArray, np.array]
The calculated COP values.
"""
pass
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?")
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]:
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]:
if (np.asarray(t_celsius) > 200).any():
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]:
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)

180
scripts/build_cop_profiles.py → scripts/build_cop_profiles/CentralHeatingCopApproximator.py
View File

@ -1,78 +1,17 @@
# -*- coding: utf-8 -*-
# SPDX-FileCopyrightText: : 2020-2024 The PyPSA-Eur Authors
#
# SPDX-License-Identifier: MIT
"""
Build coefficient of performance (COP) time series for air- or ground-sourced
heat pumps.
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.
For district (central) heating, the COP is approximated based on Jensen et al. 2018 and parameters from Pieper et al. 2020.
This rule is executed in ``build_sector.smk``.
Relevant Settings
-----------------
.. code:: yaml
heat_pump_sink_T:
Inputs:
-------
- ``resources/<run_name>/temp_soil_total_elec_s<simpl>_<clusters>.nc``: Soil temperature (total) time series.
- ``resources/<run_name>/temp_air_total_elec_s<simpl>_<clusters>.nc``: Ambient air temperature (total) time series.
Outputs:
--------
- ``resources/cop_air_decentral_heating_elec_s<simpl>_<clusters>.nc``: COP (air-sourced) time series (decentral heating).
- ``resources/cop_soil_decentral_heating_elec_s<simpl>_<clusters>.nc``: COP (ground-sourced) time series (decentral heating).
- ``resources/cop_air_central_heating_elec_s<simpl>_<clusters>.nc``: COP (air-sourced) time series (central heating).
- ``resources/cop_soil_central_heating_elec_s<simpl>_<clusters>.nc``: COP (ground-sourced) time series (central heating).
References
----------
[1] Staffell et al., Energy & Environmental Science 11 (2012): A review of domestic heat pumps, https://doi.org/10.1039/C2EE22653G.
[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
[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
"""
from enum import Enum
from typing import Union
import numpy as np
import xarray as xr
from _helpers import set_scenario_config
import numpy as np
from BaseCopApproximator import BaseCopApproximator
def coefficient_of_performance_individual_heating(delta_T, source="air"):
if source == "air":
return 6.81 - 0.121 * delta_T + 0.000630 * delta_T**2
elif source == "soil":
return 8.77 - 0.150 * delta_T + 0.000734 * delta_T**2
else:
raise NotImplementedError("'source' must be one of ['air', 'soil']")
class CentralHeatingCopApproximator(BaseCopApproximator):
"""
Approximate the coefficient of performance (COP) for a heat pump in a central heating system (district heating).
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?")
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]:
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)
class CopDistrictHeating:
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__(
self,
@ -85,7 +24,6 @@ class CopDistrictHeating:
heat_loss: float = 0.0,
) -> None:
"""
Initialize the COPProfileBuilder object.
Parameters:
----------
@ -104,17 +42,17 @@ class CopDistrictHeating:
heat_loss : float, optional
The heat loss, by default 0.0.
"""
self.t_source_in = celsius_to_kelvin(source_inlet_temperature_celsius)
self.t_sink_out = 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 = celsius_to_kelvin(return_temperature_celsius)
self.t_source_out = 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 = isentropic_compressor_efficiency
self.isentropic_efficiency_compressor_kelvin = isentropic_compressor_efficiency
self.heat_loss = heat_loss
self.delta_t_pinch = delta_t_pinch_point
def cop(self) -> Union[xr.DataArray, np.array]:
def approximate_cop(self) -> Union[xr.DataArray, np.array]:
"""
Calculate the coefficient of performance (COP) for the system.
@ -127,7 +65,7 @@ class CopDistrictHeating:
(
1
+ (self.delta_t_refrigerant_sink + self.delta_t_pinch)
/ self.t_sink_mean
/ self.t_sink_mean_kelvin
)
/ (
1
@ -139,28 +77,27 @@ class CopDistrictHeating:
/ self.delta_t_lift
)
)
* self.isentropic_efficiency_compressor
* self.isentropic_efficiency_compressor_kelvin
* (1 - self.ratio_evaporation_compression_work)
+ 1
- self.isentropic_efficiency_compressor
- self.isentropic_efficiency_compressor_kelvin
- self.heat_loss
)
@property
def t_sink_mean(self) -> Union[xr.DataArray, np.array]:
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 logarithmic_mean(t_cold=self.t_sink_in, t_hot=self.t_sink_out)
return BaseCopApproximator.logarithmic_mean(t_cold=self.t_sink_in_kelvin, t_hot=self.t_sink_out_kelvin)
@property
def t_source_mean(self) -> Union[xr.DataArray, np.array]:
def t_source_mean_kelvin(self) -> Union[xr.DataArray, np.array]:
"""
Calculate the logarithmic mean temperature of the heat source.
@ -169,20 +106,19 @@ class CopDistrictHeating:
Union[xr.DataArray, np.array]
The mean temperature of the heat source.
"""
return logarithmic_mean(t_hot=self.t_source_in, 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
-------
Union[xr.DataArray, np.array]
The temperature difference between the sink and source.
"""
return self.t_sink_mean - self.t_source_mean
return self.t_sink_mean_kelvin - self.t_source_mean_kelvin
@property
def ideal_lorenz_cop(self) -> Union[xr.DataArray, np.array]:
@ -196,14 +132,14 @@ class CopDistrictHeating:
-------
np.array
The ideal Lorenz COP.
"""
return self.t_sink_mean / self.delta_t_lift
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
-------
@ -211,14 +147,13 @@ class CopDistrictHeating:
The temperature difference between the refrigerant source inlet and outlet.
"""
return self._approximate_delta_t_refrigerant_source(
delta_t_source=self.t_source_in - self.t_source_out
delta_t_source=self.t_source_in_kelvin - self.t_source_out
)
@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
-------
@ -230,8 +165,7 @@ class CopDistrictHeating:
@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
-------
@ -250,14 +184,13 @@ class CopDistrictHeating:
Union[xr.DataArray, np.array]
The temperature difference at the sink.
"""
return self.t_sink_out - self.t_sink_in
return self.t_sink_out_kelvin - self.t_sink_in_kelvin
def _approximate_delta_t_refrigerant_source(
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
----------
@ -267,7 +200,7 @@ class CopDistrictHeating:
Returns
-------
Union[xr.DataArray, np.array]
The approximate temperature difference for the refrigerant source.
The approximate temperature difference between the refrigerant and heat source.
"""
return delta_t_source / 2
@ -279,7 +212,7 @@ class CopDistrictHeating:
c: float = {"ammonia": 0.016, "isobutane": 2.4},
) -> Union[xr.DataArray, np.array]:
"""
Approximates the temperature difference at the refrigerant sink.
Approximates the temperature difference between the refrigerant and heat sink.
Parameters:
----------
@ -295,7 +228,7 @@ class CopDistrictHeating:
Returns:
-------
Union[xr.DataArray, np.array]
The approximate temperature difference at the refrigerant sink.
The approximate temperature difference between the refrigerant and heat sink.
Notes:
------
@ -303,6 +236,7 @@ class CopDistrictHeating:
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(
@ -310,7 +244,7 @@ class CopDistrictHeating:
)
return (
a[refrigerant]
* (self.t_sink_out - self.t_source_out + 2 * self.delta_t_pinch)
* (self.t_sink_out_kelvin - self.t_source_out + 2 * self.delta_t_pinch)
+ b[refrigerant] * self.delta_t_sink
+ c[refrigerant]
)
@ -339,7 +273,7 @@ class CopDistrictHeating:
Returns:
-------
Union[xr.DataArray, np.array]
The calculated ratio of evaporation to compression work.
The approximated ratio of evaporation to compression work.
Notes:
------
@ -354,44 +288,8 @@ class CopDistrictHeating:
)
return (
a[refrigerant]
* (self.t_sink_out - self.t_source_out + 2 * self.delta_t_pinch)
* (self.t_sink_out_kelvin - self.t_source_out + 2 * self.delta_t_pinch)
+ b[refrigerant] * self.delta_t_sink
+ c[refrigerant]
)
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 in ["air", "soil"]:
source_T = xr.open_dataarray(snakemake.input[f"temp_{source}_total"])
delta_T = snakemake.params.heat_pump_sink_T_decentral_heating - source_T
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"]
)

79
scripts/build_cop_profiles/DecentralHeatingCopApproximator.py Normal file
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@ -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
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@ -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"])