acept.cop_profiles

Module to calculate COP (Coefficient of Performance) profiles.

The COP (Coefficient of Performance) is a measure of the performance of a heat pump or heat exchanger. The COP is calculated based on the temperature difference between the heat source and the heat sink.

Use this module to:

Use the acept.cop_profiles.build_cop_tve_profiles_csv() function to build the COP heat pump data for a given DataFrame of buildings and save it to a CSV file in the acept.acept_constants.TEMP_PATH directory.

Module Contents

Functions

compute_sink_temperature_from_source_temperature(...)

Compute the sink temperature from the source temperature.

cop_calc(→ float)

Calculate the coefficient of performance (COP) for a given temperature difference.

build_cop_df(→ pandas.DataFrame)

Builds a COP (Coefficient of Performance) DataFrame based on the given source temperature DataFrame,

calculate_cop_tve(→ pandas.DataFrame)

Calculate the building specific average coefficients of performance (COP) depending on the room/water heating demands.

build_cop_tve_profiles(→ pandas.DataFrame)

Builds the COP (Coefficient of Performance) heat pump air data for the given buildings.

build_cop_tve_profiles_csv(→ tuple[pandas.DataFrame, str])

Builds the COP (Coefficient of Performance) heat pump air data for the given buildings and saves it to a CSV file

save_heapump_air_to_csv(→ str)

Saves the COP (Coefficient of Performance) heat pump air data to a CSV file in the: py:const:acept.acept_constants.TEMP_PATH directory.

Attributes

COP_PARAMS

COP parameters for air, ground, water.

CORRECTION

Correction factor for the COP values.
acept.cop_profiles.COP_PARAMS[source]

COP parameters for air, ground, water.

type

air

ground

water

0

6,0801

10,288

9,9696

1

-0,0941

-0,2084

-0,2049

2

0,0005

0,0012

0,0012
acept.cop_profiles.CORRECTION = 0.85[source]

Correction factor for the COP values.

acept.cop_profiles.compute_sink_temperature_from_source_temperature(source_temperature: pandas.Series) → pandas.DataFrame[source]

Compute the sink temperature from the source temperature.

Parameters:

source_temperature (pandas.Series) – The source temperature data.

Returns:

The sink temperature data, including the radiator temperature, floor temperature, water temperature for small buildings, and water temperature for large buildings.

Return type:

pandas.DataFrame

acept.cop_profiles.cop_calc(delta_temp: float, heat_source_type: str = 'air') → float[source]

Calculate the coefficient of performance (COP) for a given temperature difference.

Parameters:

  • delta_temp (float) – The temperature difference between the heat source and the heat sink.

  • heat_source_type (str) – The type of heat source being used. Defaults to ‘air’.

Returns:

The calculated coefficient of performance (COP).

Return type:

float

acept.cop_profiles.build_cop_df(source_temperature: pandas.Series, cap_value: int | None = None, heat_source_type: str = 'air') → pandas.DataFrame[source]

Builds a COP (Coefficient of Performance) DataFrame based on the given source temperature DataFrame, cap value, and heat source type.

First calculates the sink temperature from the source temperature, then the COP values are calculated based on the temperature differences between the sink temperature and the source temperature and applying a correction factor.

Parameters:

  • source_temperature (pandas.Series) – The DataFrame containing the source temperature data.

  • cap_value (int | None) – The maximum value to cap the delta temperature. If set, the delta temperature values will be capped at this value. Defaults to None.

  • heat_source_type (str) – The type of heat source. This parameter is used in the calculation of the COP values. Defaults to ‘air’.

Returns:

The COP DataFrame with the calculated COP values.

Return type:

pandas.DataFrame

acept.cop_profiles.calculate_cop_tve(cop_df: pandas.DataFrame, buildings: pandas.DataFrame, space_heat: pandas.DataFrame, water_heat: pandas.DataFrame) → pandas.DataFrame[source]

Calculate the building specific average coefficients of performance (COP) depending on the room/water heating demands.

Parameters:

  • cop_df (pd.DataFrame) – A DataFrame containing the COP values for different heating types.

  • buildings (pd.DataFrame) – A DataFrame containing information about the buildings.

  • space_heat (pd.DataFrame) – A DataFrame containing the space heating values for each building.

  • water_heat (pd.DataFrame) – A DataFrame containing the water heating values for each building.

Returns:

A DataFrame containing the calculated COP profiles for the buildings.

Return type:

pandas.DataFrame

acept.cop_profiles.build_cop_tve_profiles(buildings: pandas.DataFrame, space_heat: pandas.DataFrame, water_heat: pandas.DataFrame, source_temperature: pandas.Series, cap_value: int | None = None, heat_source_type: str = 'air') → pandas.DataFrame[source]

Builds the COP (Coefficient of Performance) heat pump air data for the given buildings.

Parameters:

  • buildings (gpd.GeoDataFrame) – The GeoDataFrame containing the buildings.

  • space_heat (pd.DataFrame) – The DataFrame containing the space heating values.

  • water_heat (pd.DataFrame) – The DataFrame containing the water heating values.

  • source_temperature (pd.Series) – The source temperature data.

  • cap_value (int | None, optional) – The maximum allowed temperature difference between the heat source and the heat sink. If None, the difference is not capped. Defaults to None.

  • heat_source_type (str, optional) – The type of heat source being used. Defaults to ‘air’.

Returns:

DataFrame with the COP heat pump air data.

Return type:

pandas.DataFrame

acept.cop_profiles.build_cop_tve_profiles_csv(area_id: str, buildings: pandas.DataFrame, space_heat: pandas.DataFrame, water_heat: pandas.DataFrame, source_temperature: pandas.Series, cap_value: int | None = None, heat_source_type: str = 'air') → tuple[pandas.DataFrame, str][source]

Builds the COP (Coefficient of Performance) heat pump air data for the given buildings and saves it to a CSV file in the: py:const:acept.acept_constants.TEMP_PATH directory.

Parameters:

  • area_id (str) – The ID of the area COP data belongs to.

  • buildings (gpd.GeoDataFrame) – The GeoDataFrame containing the buildings.

  • space_heat (pd.DataFrame) – The DataFrame containing the space heating values.

  • water_heat (pd.DataFrame) – The DataFrame containing the water heating values.

  • source_temperature (pd.Series) – The source temperature data.

  • cap_value (int | None, optional) – The maximum allowed temperature difference between the heat source and the heat sink. If None, the difference is not capped. Defaults to None.

  • heat_source_type (str, optional) – The type of heat source being used. Defaults to ‘air’.

Returns:

A tuple containing the COP heat pump air data and the path to the saved CSV file.

Return type:

tuple[pandas.DataFrame, str]

acept.cop_profiles.save_heapump_air_to_csv(area_id: str, cop_tve_df: pandas.DataFrame) → str[source]

Saves the COP (Coefficient of Performance) heat pump air data to a CSV file in the: py:const:acept.acept_constants.TEMP_PATH directory.

Parameters:

  • area_id (str) – The ID of the area COP data belongs to.

  • cop_tve_df (pd.DataFrame) – The DataFrame containing the heat pump air data.

Returns:

The path to the saved CSV file.

Return type:

str