Individual EV load profiling and smart charging to flatten total electrical demand

Abstract

The rapid growth of electric vehicles (EVs) is stimulating their integration into the existing power grid to reduce power peaks and avoid grid congestion using smart charging strategies. Specifically, at commercial buildings, most EVs charge simultaneously in the morning resulting in large power peaks. This uncoordinated EV charging is changing the existing building load profile, which already fluctuates due to HVAC operations and PV fluctuations, significantly with their dominant charging load by amplifying power peaks. The changed building load profile of a single building does not influence the grid significantly, but the cumulative power peaks at commercial buildings can cause grid congestion. Smart charging can solve this problem by regulating power rates of charging sessions to anticipate the electrical building load. Therefore, this research aims to evaluate individual EV charging load profiles, based on real-world data, and the smart charging potential to flatten the total electrical load of a case study. Daily charging load profiles are constituted with k-means data clustering techniques to obtain the general charging profiles of individual EVs for deploying smart charging strategies. Additionally, the HVAC load flexibility potential is explored to complement smart charging with load flattening. The smart charging potential showed promising results with individual power peak reductions up to 37.8% and an average power peak reduction of the total EV load of approximately 60%.