Study on the Planning Method of Electric Vehicle Charging Station considering the Efficiency of Peak Shaving and Frequency Regulations

Peng Peng, Yuxuan Li, Zhenkai Hu, Changhong Deng, Liwen Zhu, Jun He
{"title":"Study on the Planning Method of Electric Vehicle Charging Station considering the Efficiency of Peak Shaving and Frequency Regulations","authors":"Peng Peng, Yuxuan Li, Zhenkai Hu, Changhong Deng, Liwen Zhu, Jun He","doi":"10.1109/ICIT46573.2021.9453510","DOIUrl":null,"url":null,"abstract":"China's provincial and municipal power grid companies continue to introduce the peak shaving and frequency modulation (FM) incentive policy for the auxiliary service market, which will affect the planning and development of electric vehicle(EV) charging stations. In this paper, considering some scenarios of EV charging stations and EVs as a whole to provide power grid peak shaving and FM services, based on the EV charging demand prediction model. This paper proposes an EV charging station planning method that considers the benefit of grid peak shaving and FM. The goal is to minimize the annual social comprehensive cost of the charging station. The optimal location and capacity of EV charging stations are obtained by optimization of simulated annealing particle swarm algorithm. Finally, a simulation analysis was carried out with a part of Xiangzhou area in Zhuhai City as an example, which verified the validity and correctness of the method proposed in this paper.","PeriodicalId":193338,"journal":{"name":"2021 22nd IEEE International Conference on Industrial Technology (ICIT)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 22nd IEEE International Conference on Industrial Technology (ICIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIT46573.2021.9453510","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

China's provincial and municipal power grid companies continue to introduce the peak shaving and frequency modulation (FM) incentive policy for the auxiliary service market, which will affect the planning and development of electric vehicle(EV) charging stations. In this paper, considering some scenarios of EV charging stations and EVs as a whole to provide power grid peak shaving and FM services, based on the EV charging demand prediction model. This paper proposes an EV charging station planning method that considers the benefit of grid peak shaving and FM. The goal is to minimize the annual social comprehensive cost of the charging station. The optimal location and capacity of EV charging stations are obtained by optimization of simulated annealing particle swarm algorithm. Finally, a simulation analysis was carried out with a part of Xiangzhou area in Zhuhai City as an example, which verified the validity and correctness of the method proposed in this paper.
考虑调峰效率和频率调节的电动汽车充电站规划方法研究
中国各省市电网公司不断出台辅助服务市场调峰调频(FM)激励政策,这将影响电动汽车充电站的规划和发展。本文基于电动汽车充电需求预测模型,考虑电动汽车充电站和电动汽车整体为电网提供调峰调频服务的一些场景。提出了一种考虑电网调峰和调频效益的电动汽车充电站规划方法。目标是使充电站的年度社会综合成本最小化。采用模拟退火粒子群算法优化电动汽车充电站的位置和容量。最后,以珠海市香洲部分地区为例进行了仿真分析,验证了本文方法的有效性和正确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信