1 dataset found
  1. O

    When2Heat Heating Profiles

    • data.open-power-system-data.org
    csv, sqlite, xlsx
    Updated Jul 27, 2023
    + more versions
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    Oliver Ruhnau; Jarusch Muessel (2023). When2Heat Heating Profiles [Dataset]. http://doi.org/10.25832/when2heat/2023-07-27
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    sqlite, xlsx, csvAvailable download formats
    Dataset updated
    Jul 27, 2023
    Dataset provided by
    Open Power System Data
    Authors
    Oliver Ruhnau; Jarusch Muessel
    Time period covered
    Dec 31, 2007 - Dec 31, 2022
    Variables measured
    utc_timestamp, AT_COP_ASHP_floor, AT_COP_ASHP_water, AT_COP_GSHP_floor, AT_COP_GSHP_water, AT_COP_WSHP_floor, AT_COP_WSHP_water, BE_COP_ASHP_floor, BE_COP_ASHP_water, BE_COP_GSHP_floor, and 646 more
    Description

    Simulated hourly country-aggregated heat demand and COP time series. This dataset comprises national time series for representing building heat pumps in power system models. The heat demand of buildings and the coefficient of performance (COP) of heat pumps is calculated for 28 European countries from 2008 to 2022 in an hourly resolution. Heat demand time series for space and water heating are computed by combining gas standard load profiles with spatial temperature and wind speed reanalysis data as well as population geodata. The profiles are year-wise scaled to 1 TWh each. For the years 2008 to 2015, the data is additionally scaled with annual statistics on the final energy consumption for heating. COP time series for different heat sources – air, ground, and groundwater – and different heat sinks – floor heating, radiators, and water heating – are calculated based on COP and heating curves using reanalysis temperature data, spatially aggregated with respect to the heat demand, and corrected based on field measurements. All data processing as well as the download of relevant input data is conducted in python and pandas and has been documented in the Jupyter notebooks linked below. Please also consider and cite our Data Descriptor of the original dataset as well as our Working Paper at on recent updates and extensions of the dataset.

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Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Oliver Ruhnau; Jarusch Muessel (2023). When2Heat Heating Profiles [Dataset]. http://doi.org/10.25832/when2heat/2023-07-27

When2Heat Heating Profiles

Explore at:
22 scholarly articles cite this dataset (View in Google Scholar)
sqlite, xlsx, csvAvailable download formats
Dataset updated
Jul 27, 2023
Dataset provided by
Open Power System Data
Authors
Oliver Ruhnau; Jarusch Muessel
Time period covered
Dec 31, 2007 - Dec 31, 2022
Variables measured
utc_timestamp, AT_COP_ASHP_floor, AT_COP_ASHP_water, AT_COP_GSHP_floor, AT_COP_GSHP_water, AT_COP_WSHP_floor, AT_COP_WSHP_water, BE_COP_ASHP_floor, BE_COP_ASHP_water, BE_COP_GSHP_floor, and 646 more
Description

Simulated hourly country-aggregated heat demand and COP time series. This dataset comprises national time series for representing building heat pumps in power system models. The heat demand of buildings and the coefficient of performance (COP) of heat pumps is calculated for 28 European countries from 2008 to 2022 in an hourly resolution. Heat demand time series for space and water heating are computed by combining gas standard load profiles with spatial temperature and wind speed reanalysis data as well as population geodata. The profiles are year-wise scaled to 1 TWh each. For the years 2008 to 2015, the data is additionally scaled with annual statistics on the final energy consumption for heating. COP time series for different heat sources – air, ground, and groundwater – and different heat sinks – floor heating, radiators, and water heating – are calculated based on COP and heating curves using reanalysis temperature data, spatially aggregated with respect to the heat demand, and corrected based on field measurements. All data processing as well as the download of relevant input data is conducted in python and pandas and has been documented in the Jupyter notebooks linked below. Please also consider and cite our Data Descriptor of the original dataset as well as our Working Paper at on recent updates and extensions of the dataset.

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