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Dynamic central heating temperatures (#1206)

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* feat: Add rule to build central heating temperature profiles, adjust build_cop_profiles accordingly

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* style: make new config settings prettier

* docs: add file headers

* docs: update configtables and module docstring

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* docs: update release notes

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* chore: use smooth ambient temperature through rolling window; remove default vals in class

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* Update doc/configtables/sector.csv

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Amos Schledorn <a.schledorn@tu-berlin.de>
Co-authored-by: Fabian Neumann <fabian.neumann@outlook.de>
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33
config/config.default.yaml
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@ -449,19 +449,26 @@ sector:
2045: 0.8
2050: 1.0
district_heating_loss: 0.15
# check these numbers!
forward_temperature:
default: 90
DK: 70
SE: 70
NO: 70
FI: 70
return_temperature:
default: 50
DK: 40
SE: 40
NO: 40
FI: 40
supply_temperature_approximation:
max_forward_temperature:
default: 90
DK: 70
SE: 70
NO: 70
min_forward_temperature:
default: 68
DK: 54
SE: 54
NO: 54
return_temperature:
default: 50
DK: 40
SE: 40
NO: 40
FI: 40
lower_threshold_ambient_temperature: 0
upper_threshold_ambient_temperature: 10
rolling_window_ambient_temperature: 72
heat_source_cooling: 6 #K
heat_pump_cop_approximation:
refrigerant: ammonia

9
doc/configtables/sector.csv
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@ -9,8 +9,13 @@ district_heating,--,,`prepare_sector_network.py <https://github.com/PyPSA/pypsa-
-- potential,--,float,maximum fraction of urban demand which can be supplied by district heating
-- progress,--,Dictionary with planning horizons as keys., Increase of today's district heating demand to potential maximum district heating share. Progress = 0 means today's district heating share. Progress = 1 means maximum fraction of urban demand is supplied by district heating
-- district_heating_loss,--,float,Share increase in district heat demand in urban central due to heat losses
-- forward_temperature,°C,Dictionary with country codes as keys. One key must be 'default'.,Forward temperature in district heating
-- return_temperature,°C,Dictionary with country codes as keys. One key must be 'default'.,Return temperature in district heating. Must be lower than forward temperature
-- supply_temperature_approximation,,,
-- -- max_forward_temperature,°C,Dictionary with country codes as keys. One key must be 'default'., Max. forward temperature in district heating (if ambient temperature lower-or-equal `lower_threshold_ambient_temperature`)
-- -- min_forward_temperature,°C,Dictionary with country codes as keys. One key must be 'default'., Min. forward temperature in district heating (if ambient temperature higher-or-equal `upper_threshold_ambient_temperature`)
-- -- return_temperature,°C,Dictionary with country codes as keys. One key must be 'default'.,Return temperature in district heating. Must be lower than forward temperature
-- -- lower_threshold_ambient_temperature,°C,float, Assume `max_forward_temperature` if ambient temperature is below this threshold
-- -- upper_threshold_ambient_temperature,°C,float, Assume `min_forward_temperature` if ambient temperature is above this threshold
-- -- rolling_window_ambient_temperature, h, int, Rolling window size for averaging ambient temperature when approximating supply temperature
-- heat_source_cooling,K,float,Cooling of heat source for heat pumps
-- heat_pump_cop_approximation,,,
-- -- refrigerant,--,"{ammonia, isobutane}",Heat pump refrigerant assumed for COP approximation

1 Unit Values Description
9 -- potential -- float maximum fraction of urban demand which can be supplied by district heating
10 -- progress -- Dictionary with planning horizons as keys. Increase of today's district heating demand to potential maximum district heating share. Progress = 0 means today's district heating share. Progress = 1 means maximum fraction of urban demand is supplied by district heating
11 -- district_heating_loss -- float Share increase in district heat demand in urban central due to heat losses
12 -- forward_temperature -- supply_temperature_approximation °C Dictionary with country codes as keys. One key must be 'default'. Forward temperature in district heating
13 -- return_temperature -- -- max_forward_temperature °C Dictionary with country codes as keys. One key must be 'default'. Return temperature in district heating. Must be lower than forward temperature Max. forward temperature in district heating (if ambient temperature lower-or-equal `lower_threshold_ambient_temperature`)
14 -- -- min_forward_temperature °C Dictionary with country codes as keys. One key must be 'default'. Min. forward temperature in district heating (if ambient temperature higher-or-equal `upper_threshold_ambient_temperature`)
15 -- -- return_temperature °C Dictionary with country codes as keys. One key must be 'default'. Return temperature in district heating. Must be lower than forward temperature
16 -- -- lower_threshold_ambient_temperature °C float Assume `max_forward_temperature` if ambient temperature is below this threshold
17 -- -- upper_threshold_ambient_temperature °C float Assume `min_forward_temperature` if ambient temperature is above this threshold
18 -- -- rolling_window_ambient_temperature h int Rolling window size for averaging ambient temperature when approximating supply temperature
19 -- heat_source_cooling K float Cooling of heat source for heat pumps
20 -- heat_pump_cop_approximation
21 -- -- refrigerant -- {ammonia, isobutane} Heat pump refrigerant assumed for COP approximation

2
doc/release_notes.rst
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@ -61,6 +61,8 @@ Upcoming Release
* Update JRC-IDEES-2015 to `JRC-IDEES-2021 <https://publications.jrc.ec.europa.eu/repository/handle/JRC137809>`__. The reference year is changed from 2015 to 2019.
* Made central heating supply temperatures dynamic based on an adaptation of a reference curve from Pieper et al. (2019) (https://www.sciencedirect.com/science/article/pii/S0360544219305857?via%3Dihub).
* Added option to use country-specific district heating forward and return temperatures. Defaults to lower temperatures in Scandinavia.
* Added unsustainable biomass potentials for solid, gaseous, and liquid biomass. The potentials can be phased-out and/or

73
rules/build_sector.smk
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@ -212,17 +212,72 @@ rule build_temperature_profiles:
"../scripts/build_temperature_profiles.py"
rule build_central_heating_temperature_profiles:
params:
max_forward_temperature_central_heating=config_provider(
"sector",
"district_heating",
"supply_temperature_approximation",
"max_forward_temperature",
),
min_forward_temperature_central_heating=config_provider(
"sector",
"district_heating",
"supply_temperature_approximation",
"min_forward_temperature",
),
return_temperature_central_heating=config_provider(
"sector",
"district_heating",
"supply_temperature_approximation",
"return_temperature",
),
snapshots=config_provider("snapshots"),
lower_threshold_ambient_temperature=config_provider(
"sector",
"district_heating",
"supply_temperature_approximation",
"lower_threshold_ambient_temperature",
),
upper_threshold_ambient_temperature=config_provider(
"sector",
"district_heating",
"supply_temperature_approximation",
"upper_threshold_ambient_temperature",
),
rolling_window_ambient_temperature=config_provider(
"sector",
"district_heating",
"supply_temperature_approximation",
"rolling_window_ambient_temperature",
),
input:
temp_air_total=resources("temp_air_total_elec_s{simpl}_{clusters}.nc"),
regions_onshore=resources("regions_onshore_elec_s{simpl}_{clusters}.geojson"),
output:
central_heating_forward_temperature_profiles=resources(
"central_heating_forward_temperature_profiles_elec_s{simpl}_{clusters}.nc"
),
central_heating_return_temperature_profiles=resources(
"central_heating_return_temperature_profiles_elec_s{simpl}_{clusters}.nc"
),
resources:
mem_mb=20000,
log:
logs("build_central_heating_temperature_profiles_s{simpl}_{clusters}.log"),
benchmark:
benchmarks("build_central_heating_temperature_profiles/s{simpl}_{clusters}")
conda:
"../envs/environment.yaml"
script:
"../scripts/build_central_heating_temperature_profiles/run.py"
rule build_cop_profiles:
params:
heat_pump_sink_T_decentral_heating=config_provider(
"sector", "heat_pump_sink_T_individual_heating"
),
forward_temperature_central_heating=config_provider(
"sector", "district_heating", "forward_temperature"
),
return_temperature_central_heating=config_provider(
"sector", "district_heating", "return_temperature"
),
heat_source_cooling_central_heating=config_provider(
"sector", "district_heating", "heat_source_cooling"
),
@ -232,6 +287,12 @@ rule build_cop_profiles:
heat_pump_sources=config_provider("sector", "heat_pump_sources"),
snapshots=config_provider("snapshots"),
input:
central_heating_forward_temperature_profiles=resources(
"central_heating_forward_temperature_profiles_elec_s{simpl}_{clusters}.nc"
),
central_heating_return_temperature_profiles=resources(
"central_heating_return_temperature_profiles_elec_s{simpl}_{clusters}.nc"
),
temp_soil_total=resources("temp_soil_total_elec_s{simpl}_{clusters}.nc"),
temp_air_total=resources("temp_air_total_elec_s{simpl}_{clusters}.nc"),
regions_onshore=resources("regions_onshore_elec_s{simpl}_{clusters}.geojson"),

218
scripts/build_central_heating_temperature_profiles/central_heating_temperature_approximator.py Normal file
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@ -0,0 +1,218 @@
# -*- coding: utf-8 -*-
# SPDX-FileCopyrightText: : 2020-2024 The PyPSA-Eur Authors
#
# SPDX-License-Identifier: MIT
import pandas as pd
import xarray as xr
class CentralHeatingTemperatureApproximator:
"""
A class to approximate central heating temperatures based on ambient
temperature.
Attributes
----------
ambient_temperature : xr.DataArray
The ambient temperature data.
max_forward_temperature : xr.DataArray
The maximum forward temperature.
min_forward_temperature : xr.DataArray
The minimum forward temperature.
fixed_return_temperature : xr.DataArray
The fixed return temperature.
lower_threshold_ambient_temperature : float
Forward temperature is `max_forward_temperature` for ambient temperatures lower-or-equal this threshold.
upper_threshold_ambient_temperature : float
Forward temperature is `min_forward_temperature` for ambient temperatures higher-or-equal this threshold.
"""
def __init__(
self,
ambient_temperature: xr.DataArray,
max_forward_temperature: float,
min_forward_temperature: float,
fixed_return_temperature: float,
lower_threshold_ambient_temperature: float,
upper_threshold_ambient_temperature: float,
rolling_window_ambient_temperature: int,
) -> None:
"""
Initialize the CentralHeatingTemperatureApproximator.
Parameters
----------
ambient_temperature : xr.DataArray
The ambient temperature data.
max_forward_temperature : xr.DataArray
The maximum forward temperature.
min_forward_temperature : xr.DataArray
The minimum forward temperature.
fixed_return_temperature : xr.DataArray
The fixed return temperature.
lower_threshold_ambient_temperature : float
Forward temperature is `max_forward_temperature` for ambient temperatures lower-or-equal this threshold.
upper_threshold_ambient_temperature : float
Forward temperature is `min_forward_temperature` for ambient temperatures higher-or-equal this threshold.
rolling_window_ambient_temperature : int
Rolling window size for averaging ambient temperature.
"""
self._ambient_temperature = ambient_temperature
self.max_forward_temperature = max_forward_temperature
self.min_forward_temperature = min_forward_temperature
self.fixed_return_temperature = fixed_return_temperature
self.lower_threshold_ambient_temperature = lower_threshold_ambient_temperature
self.upper_threshold_ambient_temperature = upper_threshold_ambient_temperature
self.rolling_window_ambient_temperature = rolling_window_ambient_temperature
def ambient_temperature_rolling_mean(self) -> xr.DataArray:
"""
Property to get ambient temperature.
Returns
-------
xr.DataArray
Rolling mean of ambient temperature input.
"""
# bfill to avoid NAs in the beginning
return (
self._ambient_temperature.rolling(
time=self.rolling_window_ambient_temperature
)
.mean(skip_na=True)
.bfill(dim="time")
)
@property
def forward_temperature(self) -> xr.DataArray:
"""
Property to get dynamic forward temperature.
Returns
-------
xr.DataArray
Dynamic forward temperatures
"""
return self._approximate_forward_temperature()
@property
def return_temperature(self) -> float:
"""
Property to get return temperature.
Returns
-------
float
Return temperature.
"""
return self._approximate_return_temperature()
def _approximate_forward_temperature(self) -> xr.DataArray:
"""
Approximate dynamic forward temperature based on reference curve. Adapted from [Pieper et al. (2019)](https://doi.org/10.1016/j.energy.2019.03.165).
Returns
-------
xr.DataArray
Dynamic forward temperatures.
"""
forward_temperature = xr.where(
self.ambient_temperature_rolling_mean()
<= self.lower_threshold_ambient_temperature,
self.max_forward_temperature,
xr.where(
self.ambient_temperature_rolling_mean()
>= self.upper_threshold_ambient_temperature,
self.min_forward_temperature,
self.min_forward_temperature
+ (self.max_forward_temperature - self.min_forward_temperature)
* (
self.upper_threshold_ambient_temperature
- self.ambient_temperature_rolling_mean()
)
/ (
self.upper_threshold_ambient_temperature
- self.lower_threshold_ambient_temperature
),
),
)
return forward_temperature
def _approximate_return_temperature(self) -> float:
"""
Approximate return temperature.
Returns
-------
float
Return temperature.
"""
return self.fixed_return_temperature
@property
def forward_temperature(self) -> xr.DataArray:
"""
Property to get dynamic forward temperature.
Returns
-------
xr.DataArray
Dynamic forward temperatures.
"""
return self._approximate_forward_temperature()
@property
def return_temperature(self) -> float:
"""
Property to get return temperature.
Returns
-------
float
Return temperature.
"""
return self._approximate_return_temperature()
def _approximate_forward_temperature(self) -> xr.DataArray:
"""
Approximate dynamic forward temperature.
Returns
-------
xr.DataArray
Dynamic forward temperatures.
"""
forward_temperature = xr.where(
self.ambient_temperature_rolling_mean()
<= self.lower_threshold_ambient_temperature,
self.max_forward_temperature,
xr.where(
self.ambient_temperature_rolling_mean()
>= self.upper_threshold_ambient_temperature,
self.min_forward_temperature,
self.min_forward_temperature
+ (self.max_forward_temperature - self.min_forward_temperature)
* (
self.upper_threshold_ambient_temperature
- self.ambient_temperature_rolling_mean()
)
/ (
self.upper_threshold_ambient_temperature
- self.lower_threshold_ambient_temperature
),
),
)
return forward_temperature
def _approximate_return_temperature(self) -> float:
"""
Approximate return temperature.
Returns
-------
float
Return temperature.
"""
return self.fixed_return_temperature

147
scripts/build_central_heating_temperature_profiles/run.py Normal file
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@ -0,0 +1,147 @@
# -*- coding: utf-8 -*-
# SPDX-FileCopyrightText: : 2020-2024 The PyPSA-Eur Authors
#
# SPDX-License-Identifier: MIT
"""
Approximate district heating forward and return temperature profiles based on
ambient temperature. The method is based on a reference curve from Pieper et
al. 2019, where for ambient temperatures below 0C, the highest possible forward
temperature is assumed and vice versa for temperatures above 10C. Between these
threshold levels, forward temperatures are linearly interpolated.
By default, temperature levels are increased for non-Scandinavian countries.
The default ratios between min. and max. forward temperatures is based on AGFW-Hauptbericht 2022.
Relevant Settings
-----------------
.. code:: yaml
sector:
district_heating:
max_forward_temperature:
min_forward_temperature:
return_temperature:
Inputs
------
- `resources/<run_name>/temp_air_total`: Air temperature
Outputs
-------
- `resources/<run_name>/central_heating_temperature_profiles.nc`:
References
----------
- Pieper, et al. (2019): "Assessment of a combination of three heat sources for heat pumps to supply district heating" (https://doi.org/10.1016/j.energy.2019.03.165).
- AGFW (2022): "Hauptbericht 2022" (https://www.agfw.de/zahlen-und-statistiken/agfw-hauptbericht)
"""
import sys
import geopandas as gpd
import numpy as np
import pandas as pd
import xarray as xr
from _helpers import set_scenario_config
from central_heating_temperature_approximator import (
CentralHeatingTemperatureApproximator,
)
def get_country_from_node_name(node_name: str) -> str:
return node_name[:2]
def map_temperature_dict_to_onshore_regions(
supply_temperature_by_country: dict,
regions_onshore: pd.Index,
snapshots: pd.DatetimeIndex,
) -> xr.DataArray:
"""
Map dictionary of temperatures to onshore regions.
Parameters:
----------
supply_temperature_by_country : dictionary
Dictionary with temperatures as values and country keys as keys. One key must be named "default"
regions_onshore : pd.Index
Names of onshore regions
snapshots : pd.DatetimeIndex
Time stamps
Returns:
-------
xr.DataArray
The dictionary values mapped to onshore regions with onshore regions as coordinates.
"""
return xr.DataArray(
[
[
(
supply_temperature_by_country[get_country_from_node_name(node_name)]
if get_country_from_node_name(node_name)
in supply_temperature_by_country.keys()
else supply_temperature_by_country["default"]
)
for node_name in regions_onshore.values
]
# pass both nodes and snapshots as dimensions to preserve correct data structure
for _ in snapshots
],
dims=["time", "name"],
coords={"time": snapshots, "name": regions_onshore},
)
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)
# map forward and return temperatures specified on country-level to onshore regions
regions_onshore = gpd.read_file(snakemake.input.regions_onshore)["name"]
snapshots = pd.date_range(freq="h", **snakemake.params.snapshots)
max_forward_temperature_central_heating_by_node_and_time: xr.DataArray = (
map_temperature_dict_to_onshore_regions(
supply_temperature_by_country=snakemake.params.max_forward_temperature_central_heating,
regions_onshore=regions_onshore,
snapshots=snapshots,
)
)
min_forward_temperature_central_heating_by_node_and_time: xr.DataArray = (
map_temperature_dict_to_onshore_regions(
supply_temperature_by_country=snakemake.params.min_forward_temperature_central_heating,
regions_onshore=regions_onshore,
snapshots=snapshots,
)
)
return_temperature_central_heating_by_node_and_time: xr.DataArray = (
map_temperature_dict_to_onshore_regions(
supply_temperature_by_country=snakemake.params.return_temperature_central_heating,
regions_onshore=regions_onshore,
snapshots=snapshots,
)
)
central_heating_temperature_approximator = CentralHeatingTemperatureApproximator(
ambient_temperature=xr.open_dataarray(snakemake.input.temp_air_total),
max_forward_temperature=max_forward_temperature_central_heating_by_node_and_time,
min_forward_temperature=min_forward_temperature_central_heating_by_node_and_time,
fixed_return_temperature=return_temperature_central_heating_by_node_and_time,
lower_threshold_ambient_temperature=snakemake.params.lower_threshold_ambient_temperature,
upper_threshold_ambient_temperature=snakemake.params.upper_threshold_ambient_temperature,
rolling_window_ambient_temperature=snakemake.params.rolling_window_ambient_temperature,
)
central_heating_temperature_approximator.forward_temperature.to_netcdf(
snakemake.output.central_heating_forward_temperature_profiles
)
central_heating_temperature_approximator.return_temperature.to_netcdf(
snakemake.output.central_heating_return_temperature_profiles
)

62
scripts/build_cop_profiles/run.py
View File

@ -53,47 +53,6 @@ from DecentralHeatingCopApproximator import DecentralHeatingCopApproximator
from scripts.definitions.heat_system_type import HeatSystemType
def map_temperature_dict_to_onshore_regions(
supply_temperature_by_country: dict,
regions_onshore: pd.Index,
snapshots: pd.DatetimeIndex,
) -> xr.DataArray:
"""
Map dictionary of temperatures to onshore regions.
Parameters:
----------
supply_temperature_by_country : dictionary
Dictionary with temperatures as values and country keys as keys. One key must be named "default"
regions_onshore : pd.Index
Names of onshore regions
snapshots : pd.DatetimeIndex
Time stamps
Returns:
-------
xr.DataArray
The dictionary values mapped to onshore regions with onshore regions as coordinates.
"""
return xr.DataArray(
[
[
(
supply_temperature_by_country[get_country_from_node_name(node_name)]
if get_country_from_node_name(node_name)
in supply_temperature_by_country.keys()
else supply_temperature_by_country["default"]
)
for node_name in regions_onshore.values
]
# pass both nodes and snapshots as dimensions to preserve correct data structure
for _ in snapshots
],
dims=["time", "name"],
coords={"time": snapshots, "name": regions_onshore},
)
def get_cop(
heat_system_type: str,
heat_source: str,
@ -154,20 +113,13 @@ if __name__ == "__main__":
# map forward and return temperatures specified on country-level to onshore regions
regions_onshore = gpd.read_file(snakemake.input.regions_onshore)["name"]
snapshots = pd.date_range(freq="h", **snakemake.params.snapshots)
forward_temperature_central_heating_by_node_and_time: xr.DataArray = (
map_temperature_dict_to_onshore_regions(
supply_temperature_by_country=snakemake.params.forward_temperature_central_heating,
regions_onshore=regions_onshore,
snapshots=snapshots,
)
central_heating_forward_temperature: xr.DataArray = xr.open_dataarray(
snakemake.input.central_heating_forward_temperature_profiles
)
return_temperature_central_heating_by_node_and_time: xr.DataArray = (
map_temperature_dict_to_onshore_regions(
supply_temperature_by_country=snakemake.params.return_temperature_central_heating,
regions_onshore=regions_onshore,
snapshots=snapshots,
)
central_heating_return_temperature: xr.DataArray = xr.open_dataarray(
snakemake.input.central_heating_return_temperature_profiles
)
cop_all_system_types = []
for heat_system_type, heat_sources in snakemake.params.heat_pump_sources.items():
cop_this_system_type = []
@ -179,8 +131,8 @@ if __name__ == "__main__":
heat_system_type=heat_system_type,
heat_source=heat_source,
source_inlet_temperature_celsius=source_inlet_temperature_celsius,
forward_temperature_by_node_and_time=forward_temperature_central_heating_by_node_and_time,
return_temperature_by_node_and_time=return_temperature_central_heating_by_node_and_time,
forward_temperature_by_node_and_time=central_heating_forward_temperature,
return_temperature_by_node_and_time=central_heating_return_temperature,
)
cop_this_system_type.append(cop_da)
cop_all_system_types.append(