A Game-Theoretic Approach for Charging Demand Management of Electric Vehicles During System Overload

Abstract

To manage the charging demand of electric vehicles (EVs) under maximum power limit constraints, a single-leader-multi-follower Stackelberg game theory-based solution approach is proposed in this study. A utility function is formulated for EVs considering the sensitivity of the EV owners to the battery degradation and the current energy level. A pricing mechanism for charging station operators is also devised to incentivize EVs for managing their charging demands locally, without violating the maximum power limit set by the distribution system operator. To this end, a decentralized welfare maximization model is formulated, where EVs do not need to share their private information with the charging station operator. The developed model is solved in a distributed way using the primal-dual subgradient method. The performance of the proposed method is analyzed for different power limits along with different sensitivity and energy levels. Results have shown that the proposed method can manage the charging demand of EVs considering individual sensitivities and maximum power limits of the charging station.