RenewBench combines open renewable energy generation data with meteorological weather data to provide the first global benchmark for energy-meteorological applications. While a vast amount of open-source data already exists, it is often not immediately accessible for data-driven applications due to varying standards and incompatible data types. RenewBench aggregates data from around the globe within a standardized and efficient storage infrastructure. As a result, we establish the groundwork for the development, as well as the reproducible and scalable evaluation of modern data-driven models. A central focus is the integration of meteorological data: one of the greatest challenges of the energy transition is managing the fluctuating feed-in from decentralized renewable energy sources, directly affecting grid stability. Since these sources are highly weather-dependent, RenewBench enables the modeling of energy generation in direct correlation with meteorological factors, paving the way for a new generation of energy-meteorological models. Through standardized metadata, machine-learning-optimized storage solutions, and accompanying software tools, data access is streamlined, allowing RenewBench to foster interdisciplinary collaboration and enable new research questions and solutions at the interface of meteorology and energy systems.
The project is conducted by SCC and the Institute for Automation and Applied Informatics (IAI) of the Karlsruhe Institute of Technology and the Helmholtz Center Hereon, with support from the University of Cologne and the Karlsruhe-based energy company EnBW.
Further information: helmholtz-imaging.de/project/renewbench-a-global-benchmark-for-renewable-energy-generation
Contact at SCC: Dr.-Ing.Kaleb Phipps