Published December 27, 2023 | Version v1
Dataset Open

500 Hourly Synthetic Single-Family Household Heat Pump Load Profiles for Karlsruhe, Germany (2021)

  • 1. ROR icon Karlsruhe Institute of Technology


We created a synthetic dataset of 500 hourly single-family household water-to-water heat pump load profiles based on the weather profile of Karlsruhe, Germany in 2021. We have applied the open-source methodology published in [1], which applies a k-means clustering process to match daily weather profiles with randomly drawn empirical observations from the high-quality heat pump load profile dataset published in [2]. We have selected a number of 5 clusters, for a good balance between variance of profiles and accuracy, as discussed in [1]. The dataset can be used for modeling large numbers of heat pumps in grid sections or energy communities. 

The unit of the measurement is Wh. Through the "SFH" identifier, the underlying, randomly drawn households from [2] can be identified. 

[1] Semmelmann, L., Jaquart, P., & Weinhardt, C. (2023). Generating synthetic load profiles of residential heat pumps: a k-means clustering approach. Energy Informatics6(Suppl 1), 37.

[2] Schlemminger, M., Ohrdes, T., Schneider, E., & Knoop, M. (2022). Dataset on electrical single-family house and heat pump load profiles in Germany. Scientific data9(1), 56.


Files (35.3 MB)

Name Size Download all
35.3 MB Download

Additional details

Related works

Is derived from
Dataset: 10.1038/s41597-022-01156-1 (DOI)