4576494
doi
10.5281/zenodo.4576494
oai:zenodo.org:4576494
Ruedt, Daniel
Technische Universität Berlin
Wu, Qi
Technische Universität Berlin
Held, Maike
Technische Universität Berlin
Verwiebe, Paul
Technische Universität Berlin
Mueller-Kirchenbauer, Joachim
Technische Universität Berlin
Regression-based electricity load profiles of 32 industrial and commercial subsectors in Germany
Seim, Stephan
Technische Universität Berlin
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Long term electric load forecasting
Multiple Regression analysis
Subsector load profiles
Standard load profiles
Industrial and commercial loads
<p>This dataset holds the subsector specific electricity load profiles (German: Branchenlastprofile) of 32 industrial and commercial subsectors in Germany. As a result of the research project DemandRegio, the subsector load profiles are derived from a large number of metered load data using a multiple regression method. The validation of subsector load profiles can be demonstrated within the modelling tool “disaggregator” on GitHub, a Python implementation of the overall results of the research project DemandRegio. Using subsector load profiles in the disaggregator-tool, the accuracy of the model was significantly improved in comparison to the utilization of standard load profiles.</p>
Zenodo
2021-03-04
info:eu-repo/semantics/preprint
4576493
1616079065.301447
152976013
md5:68d48af3de0eb0f2159959a965237633
https://zenodo.org/records/4576494/files/TUB Subsector load profiles (Branchenlastprofile - BLP).zip
585445
md5:cc75e2a4e2a28fb4e2beae712752bd0d
https://zenodo.org/records/4576494/files/Seim et al. (2020) - Regression-based electricity load profiles of 32 industrial and commercial sub-sectors in Germany.pdf
public
10.5281/zenodo.4576493
isVersionOf
doi