Nowadays, much attention has been drawn to environmental protection. Traveling by electric vehicles (EVs) instead of conventional fuel cars is strongly supported by national governments for the sustainable development of urban transportation. However, the increasing EV charging load in residential areas have brought a heavy burden to the distribution transformer. Therefore, coordinated charging of EVs in the residential charging station (RCS) is essential to relieve the power supply pressure. In this paper, an optimal charging strategy based on dynamic spike pricing (DSP) policy is proposed to reduce the charging cost of EVs and ensure the normal operation of the distribution transformer. First of all, the load model of EVs on four kinds of typical days is established with consideration of the seasonal and holiday characteristics of EV charging demands. Then, a new DSP policy based on Time-of-Use (TOU) mechanism is designed with an additional spike time period and a spike price to transfer peak loads in rush hours. To protect EV users from financial losses and prevent transformer overload, an optimal charging model is formulated to minimize the charging cost of EVs with considering the power margin of the distribution transformer. Ultimately, the genetic algorithm (GA) is used to solve the model. The simulation results show that the optimal charging strategy proposed in this paper is effective in peak shaving and reducing charging cost.

如今，已经引起了人们对环境保护的广泛关注。各国政府大力支持以电动汽车（EV）代替传统的燃料汽车出行，以实现城市交通的可持续发展。但是，居民区不断增加的电动汽车充电负荷给配电变压器带来了沉重的负担。因此，在住宅充电站（RCS）中对电动汽车进行协调充电对于缓解电源压力至关重要。本文提出了一种基于动态尖峰定价策略的最优充电策略，以降低电动汽车的充电成本，确保配电变压器的正常运行。首先，考虑到电动汽车充电需求的季节性和假日特征，建立了四种典型日电动汽车的负荷模型。然后，设计了基于使用时间（TOU）机制的新DSP策略，并增加了峰值时间段和峰值价格，以在高峰时段转移高峰负载。为了保护电动汽车用户免受经济损失并防止变压器过载，考虑了配电变压器的功率裕度，制定了一种最佳充电模型，以使电动汽车的充电成本降至最低。最终，遗传算法（GA）用于求解模型。仿真结果表明，本文提出的最优充电策略在削峰降噪方面是有效的。一种新的基于使用时间（TOU）机制的DSP策略被设计为具有额外的峰值时间段和峰值价格，以在高峰时段转移峰值负载。为了保护电动汽车用户免受经济损失并防止变压器过载，考虑了配电变压器的功率裕度，制定了一种最佳充电模型，以使电动汽车的充电成本降至最低。最终，遗传算法（GA）用于求解模型。仿真结果表明，本文提出的最优充电策略在削峰降噪方面是有效的。一种新的基于使用时间（TOU）机制的DSP策略被设计为具有额外的峰值时间段和峰值价格，以在高峰时段转移峰值负载。为了保护电动汽车用户免受经济损失并防止变压器过载，考虑了配电变压器的功率裕度，制定了一种最佳充电模型，以使电动汽车的充电成本降至最低。最终，遗传算法（GA）用于求解模型。仿真结果表明，本文提出的最优充电策略在削峰降噪方面是有效的。考虑到配电变压器的功率裕度，制定了一个最佳充电模型，以使电动汽车的充电成本降至最低。最终，遗传算法（GA）用于求解模型。仿真结果表明，本文提出的最优充电策略在削峰降噪方面是有效的。考虑到配电变压器的功率裕度，制定了一个最佳充电模型，以使电动汽车的充电成本降至最低。最终，遗传算法（GA）用于求解模型。仿真结果表明，本文提出的最优充电策略在削峰降噪方面是有效的。