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Information on geo-locations of renewable energy installations is very useful to investigate spatial, social or environmental questions on their impact at local and national level. However, existing data sets do not provide a sufficiently accurate representation of these installations in Germany over space and time. This work provides a valid approach on how a data set of wind power plants, photovoltaic field systems, bioenergy plants and hydropower plants can be created for Germany based on a data extract from the Core Energy Market Data Register (CEMDR) and publicly available data. Established methods were used (e.g., random forest, image recognition), but new techniques were also developed to fill data gaps or locate misplaced renewable energy installations. In this way, a substantial part of the CEMDR data could be corrected and processed in such a way that it can be freely used in a GIS software by any scientific and non-scientific discipline.

The expansion of renewable energy technologies, accompanied by an increasingly decentralized supply structure, raises many research questions regarding the structure, dimension, and impacts of the electricity supply network. In this context, information on renewable energy plants, particularly their spatial distribution and key parameters—e.g., installed capacity, total size, and required space—are more and more important for public decision makers and different scientific domains, such as energy system analysis and impact assessment. The dataset described in this paper covers the spatial distribution, installed capacity, and commissioning year of wind turbines, photovoltaic field systems, and bio- and river hydro power plants in Germany. Collected from different online sources and authorities, the data have been thoroughly cross-checked, cleaned, and merged to generate validated and complete datasets. The paper concludes with notes on the practical use of the dataset in an environmental impact monitoring framework and other potential research or policy settings.