With the rapid acceleration of transportation electrification, public charging stations are becoming vital infrastructure in a smart sustainable city to provide on-demand electric vehicle (EV) charging services. As more consumers seek to utilize public charging services, the pricing and scheduling of such services will become vital, complementary tools to mediate competition for charging resources. However, determining the right prices to charge is difficult due to the online nature of EV arrivals. This paper studies a joint pricing and scheduling problem for the operator of EV charging networks with limited charging capacity and time-varying energy cost. Upon receiving a charging request, the operator offers a price, and the EV decides whether to admit the offer based on its own value and the posted price. The operator then schedules the real-time charging process to satisfy the charging request if the EV admits the offer. We propose an online pricing algorithm that can determine the posted price and EV charging schedule to maximize social welfare, i.e., the total value of EVs minus the energy cost of charging stations. Theoretically, we prove the devised algorithm can achieve the order-optimal competitive ratio under the competitive analysis framework. Practically, we show the empirical performance of our algorithm outperforms other benchmark algorithms in experiments using real EV charging data.

翻译：随着交通电气化的快速加速，公共充电站正成为智慧可持续城市中提供按需电动汽车充电服务的关键基础设施。随着更多消费者寻求使用公共充电服务，这些服务的定价与调度将成为调节充电资源竞争的关键互补工具。然而，由于电动汽车到达的在线特性，确定合适的充电价格十分困难。本文研究了充电容量有限且能源成本随时间变化的电动汽车充电网络运营商的联合定价与调度问题。收到充电请求后，运营商提供价格，电动汽车根据自身价值和报价决定是否接受该报价。若电动汽车接受报价，运营商则调度实时充电过程以满足充电请求。我们提出了一种在线定价算法，该算法能够确定报价和电动汽车充电调度，以最大化社会福利，即电动汽车总价值减去充电站能源成本。理论上，我们证明了所设计算法在竞争分析框架下能够达到阶最优竞争比。实践中，我们展示了基于真实电动汽车充电数据的实验中，该算法的实证性能优于其他基准算法。