摘要
考虑到电动汽车充电行为的不确定性以及其对配电网的影响,从用户和实际问题的角度出发,分析电动汽车充电行为进行,建立一个配电网的多阶段多目标优化模型。对非支配排序遗传算法进行改进,假设3个调度场景进行模拟仿真,结果显示,优化后的调度方案可以降低配电网的峰谷差,提高能源的利用率,从而提高了电网的经济性。
Considering the uncertainty of electric vehicle charging behavior and its impact on the distribution network,the charging behavior of electric vehicles was analyzed from the perspectives of users and practical problems,and a multi-stage and multi-objective optimization model was established for the distribution network.Improvements were made to the non-dominated sorting genetic algorithm.The simulation of three hypothetical scheduling scenarios were conducted,and the results showed that the optimized scheduling scheme can reduce the peak valley difference in the distribution network,improve energy utilization,and thus enhance the economic efficiency of the power grid.
作者
闫丽梅
张睿格
YAN Limei;ZHANG Ruige(School of Electrical and Information Engineering,Northeast Petroleum University,Daqing 163318,China)
出处
《微特电机》
2024年第11期74-79,共6页
Small & Special Electrical Machines
基金
黑龙江省科学基金项目(LH2019E016)。
关键词
电动汽车
非支配排序遗传算法
不确定性
优化调度
electric vehicles
non-dominated sorting genetic algorithm
uncertainty
optimal scheduling
