Abstract

The objective of this study was to develop a structured framework for identifying suitable locations for battery energy storage systems (BESS) in Germany. The framework was constructed using insights from literature, German grid information and expert dialogs. The framework combines technical, economic and spatial factors relevant for BESS siting. To test the practical use of the framework, a case study was conducted based on the 110 kV grid in northeast Germany. A simplified power grid model was constructed in Python using PandaPower and included wind power injection, regional demand and three potential BESS locations.

The framework focused on evaluating how relevant each identified siting factor is and how the factor could be applied using publicly available open data. By mapping the importance of each factor against its data availability, a four-field analysis was performed to determine which factors are most suitable for inclusion in an initial screening tool. The result of the framework shows that residual energy, proximity to substations and land suitability was the factors with the highest relevance and most available data. The case study shows that Lubmin and Greifswald perform similarly well as BESS sites, while Wolgast shows significantly lower total usage and is less suitable for BESS placement.

The study concludes that the framework enables initial BESS siting selection based on the identified factors and open data. Further development could integrate economic factors, larger regional data set of Germany and automated decision making.