A large number of electric vehicles (EVs) operating in cities result in huge charging demands. For a charging station, it is important to balance between the charging cost and the future maintenance cost. In this paper, we present two bi-objective optimization models for optimizing charging cost and maintenance cost. From the perspective of maintenance cost, we consider to smooth the charging rate of the whole charging station and the charging rate of each charging port. Based on the two optimization models, we propose two heuristic online charging coordination algorithms called OCC-CSS (Cost and Station Smooth) and OCC-CPS (Cost and Port Smooth) to schedule the charging rate of EVs respectively. To evaluate their effectiveness, a series of simulations are conducted based on a real-world charging dataset of EVs. The results show that the two algorithms can achieve a nice trade-off between cost and smoothness, while keeping the ratio of service rejection near zero. Meanwhile, OCC-CPS achieves a better trade-off between cost and smoothness than OCC-CSS.

城市中运行的大量电动汽车（EV）导致了巨大的充电需求。对于充电站，重要的是要在充电成本和将来的维护成本之间取得平衡。在本文中，我们提出了两个用于优化充电成本和维护成本的双目标优化模型。从维护成本的角度，我们考虑使整个充电站的充电率和每个充电端口的充电率平滑。基于这两种优化模型，我们提出了两种启发式在线充电协调算法，分别称为OCC-CSS（成本和站点平滑）和OCC-CPS（成本和端口平滑），以分别调度电动汽车的充电率。为了评估其有效性，基于真实世界的电动汽车充电数据集进行了一系列模拟。结果表明，两种算法都可以在成本和平滑度之间取得良好的折衷，同时将服务拒绝的比率保持在零附近。同时，与OCC-CSS相比，OCC-CPS在成本和平滑度之间实现了更好的折衷。