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.

出于在电动汽车充电站中将使用过的电动汽车（EV）电池用作电池储能系统（BESS）的潜力的动机，我们研究了在存在以下情况的情况下BESS操作和可延期EV充电负荷的联合调度随机可再生能源发电，电动汽车的到来以及电价。我们将电动汽车充电站运营商面临的成本最小化调度问题制定为动态程序。当电动汽车数量很大时，由于维数的诅咒，制定的动态程序无法用蛮力方法精确求解。我们为电动汽车之间的能源分配制定了完整，最佳的优先规则。对于重要的特殊情况，它具有充分的充电/放电效率，并且在初始阶段可以使用所有电动汽车进行充电，我们提出了一种新的方法论方法来建立最佳调度策略的完整特征，从而能够开发可扩展的计算方法。所提出的方法在具有实际电价和太阳能发电数据的数值实验中实现了接近最佳的性能。