首页 | 本学科首页   官方微博 | 高级检索  
     

考虑电动汽车有序充电的光储充电站储能容量优化策略
引用本文:李景丽,时永凯,张琳娟,杨旭晨,王利利,陈 星. 考虑电动汽车有序充电的光储充电站储能容量优化策略[J]. 电力系统保护与控制, 2021, 49(7): 94-102
作者姓名:李景丽  时永凯  张琳娟  杨旭晨  王利利  陈 星
作者单位:郑州大学电气工程学院,河南 郑州 450001;国网河南省电力公司经济技术研究院,河南 郑州 450000;国网河南省电力公司商丘供电公司,河南 商丘 476000
基金项目:国家自然科学基金项目资助(51307152)
摘    要:针对电动汽车和光伏系统接入配电网与储能装置结合过程中的配置优化问题,提出了一种考虑电动汽车有序充电的光储充电站储能容量优化策略.首先,基于典型日光照强度曲线和光电能量转换关系计算光伏系统输出功率.其次,根据电动汽车用户出行习惯、充电行为特性、充电模式等充电负荷影响因素,建立影响电动汽车充电负荷的概率模型,利用蒙特卡洛方...

关 键 词:电动汽车  有序充电  光储充电站  容量优化  粒子群算法
收稿时间:2020-10-27
修稿时间:2021-01-26

Optimization strategy for the energy storage capacity of a charging station with photovoltaic and energy storage considering orderly charging of electric vehicles
LI Jingli,SHI Yongkai,ZHANG Linjuan,YANG Xuchen,WANG Lili,CHEN Xing. Optimization strategy for the energy storage capacity of a charging station with photovoltaic and energy storage considering orderly charging of electric vehicles[J]. Power System Protection and Control, 2021, 49(7): 94-102
Authors:LI Jingli  SHI Yongkai  ZHANG Linjuan  YANG Xuchen  WANG Lili  CHEN Xing
Affiliation:1. School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China; 2. State Grid Henan Economic and Technological Research Institute, Zhengzhou 450000, China;3. Shangqiu Power Supply Company, State Grid Henan Electric Power Company, Shangqiu 476000, China
Abstract:There is a configuration optimization problem in the process of integrating electric vehicles and photovoltaic systems into the distribution network and energy storage devices. Thus this paper proposes an energy storage capacity optimization strategy for photovoltaic storage charging stations that considers the orderly charging of electric vehicles. First, it calculates the output power of the photovoltaic system based on a typical daylight intensity curve and the photoelectric energy conversion relationship. Secondly, from charging load influencing factors such as the travel habits of electric vehicle users, charging behavior characteristics, charging mode and so on, a probability model that affects the charging load of electric vehicles is established, and the Monte Carlo method is used to predict the charging load under disorderly charging. Then taking the minimum peak-valley difference of the power grid output curve as the objective function, the particle swarm algorithm is used to calculate the total power grid output load during orderly charging, and it then determines the optimal solution for the energy storage capacity of an optical storage charging station. Finally, the strategy is used to calculate the optimal energy storage capacity in a residential area optical storage charging station with electric private cars and electric taxis as the main service objects. The results show that the disorderly charging of electric vehicles when energy storage is not considered causes the power grid load to add peaks. The peak-to-valley difference of the power grid load is reduced by 15.35% under orderly charging. When the orderly charging of electric vehicles is considered and the optimal energy storage capacity is configured, the peak-to-valley difference of power grid load decreases by 20.65%. This realizes peak shaving and valley filling, and enhances the stability of power system operation. The results obtained in this paper provide a reference for the energy storage capacity configuration of an optical storage charging station.This work is supported by the National Natural Science Foundation of China (No. 51307152).
Keywords:electric vehicle   orderly charging   optical storage and charging station   capacity optimization   particle swarm algorithm
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《电力系统保护与控制》浏览原始摘要信息
点击此处可从《电力系统保护与控制》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号