电力系统保护与控制2025，Vol.53Issue(15)：95-102,8.DOI:10.19783/j.cnki.pspc.241053
基于多目标蜉蝣算法的电动汽车充电站联合储能系统最优规划方法
Optimal planning of electric vehicle charging stations integrated with energy storage systems based on multi-objective mayfly algorithm
摘要
Abstract
The increasing ownership of electric vehicles(EVs)has led to the widespread deployment of electric vehicles charging stations(EVCS).However,the high randomness of EV charging behavior pose significant challenges to the load stability of distribution network.To alleviate the deterioration of distribution network stability caused by EV charging load,this paper proposes a multi-objective optimization planning model of EVCS integrated with battery energy storage systems(BESS)based on EV charging demand.The model aims to minimize the overall cost of the EVCS-BESS system,including economic losses due to network losses,user waiting time costs,and system voltage fluctuation,thus optimizing the installation of EVCS in distribution networks to achieve a win-win outcome for EVCS developers,users,and power grid operators.To verify the validity of the proposed planning model,a simulation experiment based on the extended IEEE33 node test system is designed.The experimental results show that using the multi-objective mayfly algorithm(MOMA)for optimization can effectively improve the stability and economic performance of the distribution network.关键词
电动汽车充电桩/最优规划/储能系统/网损/负荷波动Key words
electric vehicle charging station/optimal planning/energy storage system/network loss/load fluctuation引用本文复制引用
何国彬,杨金新,施铭涛,苏睿,黄元平,李建云,杨瑾..基于多目标蜉蝣算法的电动汽车充电站联合储能系统最优规划方法[J].电力系统保护与控制,2025,53(15):95-102,8.基金项目
This work is supported by the Science and Technology Project of China Southern Power Grid(No.YNKJXM20230337). 南方电网科技项目资助(YNKJXM20230337)"多能互补低碳园区综合能源系统关键技术研究与应用" （No.YNKJXM20230337）
