摘要
针对现有住宅小区的配电变压器供电容量限制问题,提出了一种双目标优化的电动汽车有序控制策略。由电动汽车充电负荷的影响因素入手建立充电需求模型,在峰谷分时电价的基础上构建用户充电费用支出最少和小区负荷峰谷差最小双目标优化函数;采用遍历寻优算法及结合精英策略和自适应策略的改进遗传算法设计了电动汽车有序充电控制策略。仿真结果表明,基于双目标优化的有序充电策略的有序充电模式下,用户充电费用降低了30%,小区变压器负载率为92.31%,负荷的峰谷差率从42.5%降至24.2%,负荷波动降低,满足变压器安全稳定运行需求。
A dual-objective control strategy for optimized electric vehicle chargingorder was proposed aiming at improving the power supply limitation of distribution transformers in serving the residential quarters.A charging demand model was establishedtaking into consideration the influencing factors of electric vehicle charging load,and,based on the peak-valley electricity price,two optimization objective functions were constructed for minimum users charging expense and minimumload-to-valley difference.Then the control strategy of the electric vehicle charging planwas designed using the traversal optimization algorithm and the elite strategy-adaptive strategy improved genetic algorithm.Simulation results show that,under the orderly charging mode of the ordered charging strategy on dual-objective optimization,the user charging cost has a 30% reduce,the transformer load rateis92.31%,and the peak-valley difference is reduced from 42.5%to 24.2%,producing the reduced load fluctuation that meets the criteriafor safe and stable operation of the transformer.
作者
郑雪钦
吴景丽
熊军
ZHENG Xueqin,WU Jingli,XIONG Jun(School of Electrical Engineering Automation,Xiamen University of Technology,Xiamen 361024,China)
出处
《厦门理工学院学报》
2018年第5期12-18,共7页
Journal of Xiamen University of Technology
基金
厦门市科技计划项目(3502Z20179026)
关键词
电动汽车
有序充电
控制策略
目标优化
遍历算法
遗传算法
electric vehicle
ordered charging
charging strategy
objective optimization
traversal algorithm
genetic algorithm
