电动汽车有序充电多目标优化方法  

Multi-objective Optimization Method for Orderly Charging of Electric Vehicles

作　　者：洪祥 黄建刚 钱科军 郑众 HONG Xiang;HUANG Jiangang;QIAN Kejun;ZHENG Zhong(Nanjing Daqo Electric Research Institute Co.,Ltd.,Nanjing 211000,China;Suzhou Power Supply Branch of State Grid Jiangsu Electric Power Co.,Ltd.,Suzhou 215000,China;State Grid Suzhou Electric Vehicle Service Co.,Ltd.,Suzhou 215000,China)

机构地区：[1]南京大全电气研究院有限公司,江苏南京211000 [2]国网江苏省电力有限公司苏州供电分公司,江苏苏州215000 [3]国网苏州电动汽车服务有限公司,江苏苏州215000

出　　处：《微型电脑应用》2023年第11期5-9,共5页Microcomputer Applications

基　　金：国家自然科学基金(52107005)。

摘　　要：电动汽车大规模无序充电会导致电网负荷波动过大、电压偏移量大,因此,需要对电动汽车充电行为进行多目标优化。通过对电动汽车驾驶人员驾驶行为与充电习惯的分析,建立电动汽车充电负荷模型;在粒子群优化算法的基础上,引入二进制编码对优化函数展开求解,实现有序充电策略的优化。测试表明,利用所提方法对车辆充电行为展开有序优化后,充电桩的负荷在2000~2500 kW区间波动,波动情况趋于平缓,电压偏移量在3.00%以内,网损率在2%左右,有效降低了电网的损耗率,为电力系统的平稳运行提供保障。A large scale of unregulated charging of electric vehicles can lead to excessive fluctuation in grid load and significant voltage deviation.Therefore,it is necessary to optimize the charging behavior of electric vehicles in a multi-objective manner.By analyzing the driving behavior and charging habits of electric vehicle drivers,an electric vehicle charging load model is established.Based on the particle swarm optimization algorithm,binary coding is introduced to solve the optimization function and achieve the optimization of orderly charging strategies.Tests show that by utilizing the proposed method to optimize the charging behavior of vehicles in an orderly manner,the load on charging stations fluctuates within the range of 2000 kW to 2500 kW,with a tendency towards smoother fluctuations,the voltage deviation remains within 3.00%,and the network loss rate is around 2%,which effectively reduces the loss rate of the power grid and provides assurance for the stable operation of the power system.

关 键 词：充电负荷模型 粒子群优化算法 有序充电 多目标优化 

分 类 号：TM910.6[电气工程—电力电子与电力传动]