计及多种充电模式的电动汽车充电站有序充电双层优化策略

A bi-layer optimal strategy for coordinated charging of electric vehicle chargingstation considering multiple charging modes

大规模电动汽车无序接入充电站不仅会引起配电网负荷“峰上加峰”,还会造成充电拥堵,延长电动汽车排队等待时间。建立了计及多种充电模式的电动汽车充电站有序充电双层优化模型。在上层模型中,以配电网负荷方差和上下层调度计划偏差综合最小为目标实现系统负荷“削峰填谷”,使负荷曲线更平坦。在下层模型中,建立基于多队列多服务台的充电站排队系统,减少电动汽车出行时间和充电费用。采用遗传算法和蚁群算法分层迭代求解模型,以含有4个充电站的IEEE 33节点配网系统为例进行仿真,结果通过与无序充电、Active Scheduling(AS)模型对比表明:所提模型在优化配电网系统负荷、减少电动汽车出行时间和充电费用等方面具有一定的有效性。

Large-scale electric vehicles(EVs)integration into charging station disorderly will not only cause"peak load overlap"in distribution network,but also cause charging congestion and increase the waiting time of EV.A bi-layer optimization model for coordinated charging of EV charging station considering multiple charging modes is established in this paper.In the upper model,the objective is to minimize the variance of load and dispatch plan deviation between upper and lower levels,so as to achieve peak load shifting,and make the load curve flatter.In the lower model,a charging station queuing system based on multi-queue and multi-server is established to minimize the travel time and charging cost of EV.This paper proposes genetic algorithm(GA)and ant colony optimization(ACO)to solve this problem by hierarchical iterative,the simulation is carried out in IEEE 33-node distribution system with four charging stations.By comparing with un-coordinated charging and active scheduling(AS)model,the results show that the proposed model is effective in optimizing distribution system load,reducing travel time and charging cost of EV.