面向居民区的电动汽车有序充放电优化策略

Orderly Charging and Discharging Optimization Strategy of Electric Vehicles for Residential Areas

为应对未来电动汽车(electric vehicles,EV)无序充电使居民区配网负荷出现“峰上加峰”现象,首先引入充/放电概率与初始荷电状态的对应关系,建立考虑“多日一充”的EV负荷模型,接着根据区域负荷特征划分电价时段,采用“成本补偿”方式建立峰谷时段电价浮动比例关系式,制定面向居民区EV充电桩的峰谷分时电价并得到电价引导后的EV负荷。由于仅通过电价引导则会使EV集中涌入充电,造成新的负荷尖峰问题,因此建立双层优化调度模型;为了提高车主参与度,引入充/放电参与度评价系数并确定奖惩机制。最后采用粒子群算法求解优化模型。结果表明该优化策略缩小了配网负荷峰谷差,保证了车主的利益。

To address the issue of the"peak-on-peak"phenomenon in the distribution network load in residential areas caused by the unregulated charging of electric vehicles(abbr.EVs)in the future,firstly,the corresponding relationship between charging/discharging probability and the initial state of charge was introduced to establish an EV load model considering"Many-days-a-charge".Secondly,based on the load characteristics of the region,the electricity price periods were divided;a fluctuating proportion relationship between peak and valley electricity prices was established by using the"cost compensation"method;the peak-valley time-of-use electricity prices for EV charging stations in residential areas were formulated and the EV loads after price guidance were obtained.Nevertheless,relying solely on price guidance will result in concentrated charging of EVs,leading to new peak load issues.Therefore,a dual-layer optimization scheduling model was established.Meanwhile,to improve the participation of vehicle owners,an evaluation coefficient for charging/discharging participation was introduced and a reward and punishment mechanism was determined.Finally,the proposed optimization model was solved by using the particle swarm algorithm.The results show that this optimization strategy reduces the peak-valley difference in the distribution network load and ensures the interests of vehicle owners.