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Real-world energy data of 200 feeders from low-voltage grids with metadata in Germany over two years

Treutlein, Manuel ORCID iD icon 1; Bothe, Pascal; Schmidt, Marc; Hahn, Roman; Neumann, Oliver; Mikut, Ralf ORCID iD icon 1; Hagenmeyer, Veit ORCID iD icon 1
1 Institut für Automation und angewandte Informatik (IAI), Karlsruher Institut für Technologie (KIT)

Abstract:

The last mile of the distribution grid is crucial for a successful energy transition, as more low-carbon technology like photovoltaic systems, heat pumps, and electric vehicle chargers connect to the low-voltage grid. Despite considerable challenges in operation and planning, researchers often lack access to suitable low-voltage grid data. To address this, we present the FeederBW dataset with data recorded by the German distribution system operator Netze BW. It offers real-world energy data from 200 low-voltage feeders over two years (2023-2025) with weather information and detailed metadata, including changes in low-carbon technology installations. The dataset includes feeder-specific details such as the number of housing units, installed power of low-carbon technology, and aggregated industrial energy data. Furthermore, high photovoltaic feed-in and one-minute temporal resolution makes the dataset unique. FeederBW supports various applications, including machine learning for load forecasting, conducting non-intrusive load monitoring, generating synthetic data, and analyzing the interplay between weather, feeder measurements, and metadata. ... mehr


Volltext §
DOI: 10.5445/IR/1000190242
Veröffentlicht am 05.02.2026
Originalveröffentlichung
DOI: 10.48550/arXiv.2602.03521
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Publikationstyp Forschungsbericht/Preprint
Publikationsjahr 2026
Sprache Englisch
Identifikator KITopen-ID: 1000190242
HGF-Programm 37.12.02 (POF IV, LK 01) Design,Operation & Digitalization of the Future Energy Grids
Verlag arxiv
Vorab online veröffentlicht am 04.02.2026
Schlagwörter Systems and Control (eess.SY)
Nachgewiesen in arXiv
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