电动汽车大规模接入电网后,有序充电优化控制具有便于集中管理、抑制负荷波动、降低峰谷差和充电费用等优势,但同时也带来换电站电池冗余度增大的问题。文中针对换电模式,以抑制电网总体负荷波动为有序充电主要目标,采用自适应遗传算法,建立有序充电模式下换电站电池冗余度模型,并使用蒙特卡洛方法模拟电动汽车用户的用车需求。对比分析无序充电和有序充电模式下换电站电池冗余度仿真结果,表明该有序充电策略能够有效削减负荷波动,减小峰谷差,但也相应提升了换电站电池冗余度。
Coordinated charging by large-scale application of electric vehicles will bring benefits such as facilitating centralized management,inhibiting load fluctuation and reducing the charging cost.Despite the positive effects,it will bring about disadvantages of battery redundancy to swapping station. For the sake of concentrating on battery redundancy under coordinated charging,a load fluctuation optimization model is developed in battery swapping modes using the adaptive genetic algorithm,with the power demand of electric vehicles analyzed through Monte Carlo method.Calculation results show that compared to the uncoordinated charging scenario,the coordinated charging model can not only restrain load fluctuation and peak-valley,but,as a result,increase battery redundancy.