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 16 European countries from 2008 to 2018 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 2012, 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.

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.