Suzhou Electric Appliance Research Institute
期刊号: CN32-1800/TM| ISSN1007-3175

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基于分时电价的电动汽车有序充放电策略研究

来源:电工电气发布时间:2022-04-20 13:20 浏览次数:336

基于分时电价的电动汽车有序充放电策略研究

吴芳柱,田园
(国网江苏省电力有限公司南京供电分公司,江苏 南京 210019)
 
    摘 要:为了减缓电动汽车无序充电造成的负荷波动,提出一种基于分时电价的电动汽车有序充放电策略。构建了居民区电动汽车负荷模型,在考虑负荷均方差、用户充放电成本和电动汽车充电量的情况下,建立多目标优化函数,并采用改进粒子群算法求解多维优化问题。仿真结果表明,所提有序充放电策略能在有效平缓电网负荷曲线的同时,增大电动汽车充电电量和减少用户充放电成本,最大程度满足用户出行需求。
    关键词:电动汽车;有序充放电;多目标优化;改进粒子群算法
    中图分类号:TM714 ;U469.72     文献标识码:A     文章编号:1007-3175(2022)04-0021-05
 
Coordinated Charging Strategy for Electric Vehicle Charging and
Discharging Based on Time-Use Price
 
WU Fang-zhu, TIAN Yuan
(Nanjing Power Supply Company, State Grid Jiangsu Electric Power Co., Ltd, Nanjing 210019, China)
 
    Abstract: For alleviating the load fluctuation caused by disorderly charging, this paper proposed an ordered charging and discharging strategy for electric vehicles based on the time-of-use pricing system.Furthermore, it helped to structure an electric vehicle load model. This research considered many situations, such as the mean square error of the load, the cost of charge and discharge, and the charging capacity of electric vehicles. It established a multi-objective optimization function and used the improved particle swarm algorithm to solve multidimensional optimization problems.The simulation result shows that the strategy could effectively smooth the grid load curve, increase electric vehicle charging capacity and save charging and discharging costs. It helps to meet the travel needs of users.
    Key words: electric vehicle; coordinated charging and discharging; multi-objective optimization; improved particle swarm algorithm
 
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