Optimal deadline scheduling for electric vehicle charging with energy storage and random supply

Motivated by the potential of utilizing used electric vehicle (EV) batteries as the battery energy storage system (BESS) in EV charging stations, we study the joint scheduling of BESS operation and deferrable EV charging load (with the same deadline) in the presence of random renewable generation, EV arrivals, and electricity prices. We formulate the cost-minimizing scheduling problem faced by an EV charging station operator as a dynamic program. When the number of EVs is large, the formulated dynamic program cannot be exactly solved by brute-force methods due to the curse of dimensionality. We characterize a complete, optimal priority rule on energy allocation among EVs. For an important special case with full charging/discharging efficiency and all EVs available for charging at the initial period, we propose a new methodological approach to establish full characterizations of an optimal scheduling policy that enable the development of scalable computational approaches. The proposed approach achieves close-to-optimal performance in numerical experiments with real-world electricity pricing and solar generation data.