Predictive modeling of vehicle-to-grid flexibility: A bottom-up approach demonstrated for a case-study in Germany

Abstract

Germany’s energy transition requires substantial energy storage capacity to manage grid stability and renewable energy integration. Conventional storage technologies may face limitations in meeting the projected demand, while the growing battery electric vehicle (BEV) fleet represents a potential distributed storage resource with uncertain vehicle-to-grid (V2G) capacity currently. In order to bridge this uncertainty, this study develops a bottom-up approach to calculate the gross battery capacity that passenger vehicle fleets could provide for grid services. The approach is demonstrated through application to the German market, identifying key factors that influence realistic V2G deployment scenarios. We enhanced our bottom-up vehicle technology scenario model by integrating different battery technologies and vehicle models offering bidirectional charging. In the reference scenario, considering annual benefits of 150 to 270 Euro for different bidirectional charging use cases and costs of 900 Euro for a dedicated wallbox, our simulations indicate up to 18.3 million bidirectional-capable BEVs by 2045, resulting in nearly 1300 GWh of gross battery capacity. Even with more conservative estimates from our sensitivity analyses, the potential battery capacity of the bidirectional BEV fleet would exceed Germany’s future energy storage capacity by a factor of four, demonstrating the considerable potential of passenger vehicles as distributed grid storage resources.