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

TL;DR

The paper introduces FeederBW, a comprehensive real-world dataset of 200 low-voltage feeders in Germany over two years, enabling advanced research on energy transition impacts and grid management.

Contribution

It provides the first detailed, high-resolution, real-world low-voltage grid dataset with extensive metadata, supporting diverse applications like load forecasting and analysis of low-carbon technology effects.

Findings

Reveals patterns of low-carbon technology integration

Highlights the impact of weather on grid load

Demonstrates dataset's utility for machine learning applications

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. The dataset reveals insightful patterns and clearly reflects the growing impact of low-carbon technology on low-voltage grids.