Plug-in Electric Vehicles (PEVs) keep on penetrating the automobile market. However, uncoordinated PEV charging can impair the reliability of power grid. In this paper, an interesting problem of PEV charging power allocation is investigated, in which both power distribution and transportation constraints are considered. A novel approach for PEV charging management based on optimal power flow (OPF) analysis is proposed to optimize PEV charging energy in a power distribution system. Firstly, spatial and temporal PEV demand scheduling is introduced to maximize PEV charging service capacity while considering the maximum traveling distance of PEVs. Secondly, to ensure the scalability of the OPF analysis, a distributed optimization technique, i.e., proximal Jacobian alternating direction multiplier method, is applied to attain the optimal power allocation in a decentralized manner. The resulting PEV charging service capacity in the power distribution system is improved without violating power distribution and transportation constraints. Furthermore, kernel density estimation method is adopted to identify the PEV range anxiety constraint without the PEV battery information. Simulation results are presented to validate the effectiveness of our approach with high PEV penetration.

中文翻译：

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具有配电和运输约束的分散式 PEV 功率分配

插电式电动汽车 (PEV) 继续渗透汽车市场。然而，不协调的电动汽车充电会损害电网的可靠性。在本文中，研究了 PEV 充电功率分配的一个有趣问题，其中考虑了功率分配和运输约束。提出了一种基于优化潮流 (OPF) 分析的 PEV 充电管理新方法，以优化配电系统中的 PEV 充电能量。首先，引入空间和时间的 PEV 需求调度，以在考虑 PEV 最大行驶距离的同时最大化 PEV 充电服务能力。其次，为了保证OPF分析的可扩展性，采用分布式优化技术，即近端雅可比交替方向乘法器法，用于以分散的方式实现最佳功率分配。在不违反配电和运输约束的情况下，配电系统中由此产生的 PEV 充电服务能力得到提高。此外，采用核密度估计方法在没有PEV电池信息的情况下识别PEV里程焦虑约束。提供仿真结果以验证我们的方法在高 PEV 渗透率下的有效性。