基于交替方向乘子法的电动汽车分散式充电控制

大规模电动汽车的无序接入会对电力系统的安全、经济运行产生诸多不利影响。针对这些问题,建立了用户收益最大化及系统有功网损最小化的实时充电控制多目标凸优化模型。引入交替方向乘子算法,将集中式充电优化问题转换为分散式以设备为单位的子优化问题求解。每次迭代设备与相邻的交互信息点之间仅需交互少量信息,利于保护用户的信息安全,并能有效解决集中式控制策略引起通信要求高、计算开销大的问题。IEEE 33节点、实际的119节点配电网系统的仿真结果表明:所提模型与集中式优化模型的计算结果一致,所提算法计算效率高、通信开销小,适用于滚动式实时调度。

Decentralized Charging Control of Electric Vehicles Based on Alternate Direction Method of Multiplier

The random charging of electric vehicles(EVs)will cause many adverse effects on the security and economical operation of a power system. A multi-objective optimization model is proposed for real-time charging control aimed at maximization of the EV owners'' benefit and minimization of the active power loss. By using the alternate direction method of multiplier(ADMM), the centralized optimization model of charging can be converted into individual sub-problems in the decentralized optimization model with the device as the unit. For each iteration of ADMM, only a bit of information is exchanged between the device and the adjacent interactive information points, which is conducive to protecting user information security. Meanwhile, some disadvantages due to centralized optimization can be overcome, such as high communication requirements and high computational overhead. Simulations for IEEE 33-bus and actual 119-bus network systems show that the results of the decentralized optimization model and the centralized model are conformable. Moreover, the proposed algorithm shows high computing efficiency, low communication cost and good applicability to the rolling scheduling schema in real-time. This work is supported by National Basic Research Program of China(973 Program)(No. 2013CB228205)and National Natural Science Foundation of China(No. 51367004).