电动汽车两阶段多目标有序充电策略研究  

Charging control strategy for electric vehicles based on two-stage multi-target optimization

作　　者：陈奎 马子龙 周思宇 沈兴来 蔺华 CHEN Kui;MA Zilong;ZHOU Siyu;SHEN Xinglai;LIN Hua(School of Electrical and Power Engineering,China University of Mining and Technology,Xuzhou 221116,China;State Grid Xuzhou Power Supply Company,Xuzhou 221000,China)

机构地区：[1]中国矿业大学电气与动力工程学院,江苏徐州221116 [2]国网江苏省电力公司徐州供电公司,江苏徐州221000

出　　处：《电力系统保护与控制》2020年第1期65-72,共8页Power System Protection and Control

基　　金：国家杰出青年科学基金项目资助(51707192)~~

摘　　要：大量随机性电动汽车充电负荷的接入会对电网安全经济运行等方面产生不利的影响。在统计电动汽车用户出行规律、起始充电时刻等行为基础上,分析了充电站的充电负荷特性。在考虑配电设备运行安全和用户充电需求的前提下,综合充电负荷和原有负荷的特点,建立了以分时电价为基础、以减小负荷波动率和提高运营商效益为目标的两阶段多目标充电模型。提出了基于多种群遗传算法的两阶段多目标优化模型求解方法和有序充电控制策略。以小区充电站为例,验证了两阶段多目标有序充电控制策略在减小负荷波动率、削峰填谷、降低经济成本提高运营商效益等方面的作用。The access of large number of random electric vehicle charging loads will adversely affect the safe and economic operation of the power grid.Based on the statistics of user travel laws and starting charging time,the charging load characteristics of electric vehicle charging stations are analyzed.Under the premise of considering the operation safety of power distribution equipment and the user's charging demand,multi-target charging model of two stages optimization are established,with the aim of reducing load fluctuation rate and improving operator benefits,based on time-of-use electricity price,the characteristics of integrated charging load and original load.The two-stage and multi-objective optimization model solving method based on multi-population genetic algorithm and the ordered charging strategy are proposed.Taking the residential charging station as an example,the role of the two-stage and multi-objective control strategy in reducing the load volatility,cutting the peaks and filling the valley,reducing the economic cost is verified.

关 键 词：电动汽车 有序充电 两阶段优化 经济成本 负荷波动 

分 类 号：TM73[电气工程—电力系统及自动化]