基于AGA的电动汽车充电策略优化研究

Bowen Xu
{"title":"基于AGA的电动汽车充电策略优化研究","authors":"Bowen Xu","doi":"10.5220/0008870302270234","DOIUrl":null,"url":null,"abstract":"Because the charging load of electric vehicles is random in time and space, a large number of disorderly charging of electric vehicles will lead to the peak load of distribution network exceeding the limit of equipment, which will bring adverse effects on the operation of power grid. In order to smooth the daily load curve of distribution network, this paper establishes a solution model of intelligent charging control strategy for large-scale electric vehicle considering the charging demand constraints of electric vehicle users, and uses adaptive genetic algorithm (AGA) to solve the model. Taking IEEE33 bus distribution network as an example, based on Monte Carlo stochastic simulation of large-scale electric vehicle gridconnected scene, the impact of electric vehicle load on distribution network under two control modes of disorderly charging and intelligent charging is studied comparatively, and the effectiveness of this method is","PeriodicalId":186406,"journal":{"name":"Proceedings of 5th International Conference on Vehicle, Mechanical and Electrical Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Research on Charging Strategy Optimization of Electric Vehicle based on AGA\",\"authors\":\"Bowen Xu\",\"doi\":\"10.5220/0008870302270234\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Because the charging load of electric vehicles is random in time and space, a large number of disorderly charging of electric vehicles will lead to the peak load of distribution network exceeding the limit of equipment, which will bring adverse effects on the operation of power grid. In order to smooth the daily load curve of distribution network, this paper establishes a solution model of intelligent charging control strategy for large-scale electric vehicle considering the charging demand constraints of electric vehicle users, and uses adaptive genetic algorithm (AGA) to solve the model. Taking IEEE33 bus distribution network as an example, based on Monte Carlo stochastic simulation of large-scale electric vehicle gridconnected scene, the impact of electric vehicle load on distribution network under two control modes of disorderly charging and intelligent charging is studied comparatively, and the effectiveness of this method is\",\"PeriodicalId\":186406,\"journal\":{\"name\":\"Proceedings of 5th International Conference on Vehicle, Mechanical and Electrical Engineering\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 5th International Conference on Vehicle, Mechanical and Electrical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5220/0008870302270234\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 5th International Conference on Vehicle, Mechanical and Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0008870302270234","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

由于电动汽车的充电负荷在时间和空间上具有随机性,大量的电动汽车无序充电将导致配电网的峰值负荷超过设备的极限,给电网的运行带来不利影响。为了平滑配电网日负荷曲线,考虑电动汽车用户的充电需求约束,建立了大型电动汽车智能充电控制策略的求解模型,并采用自适应遗传算法(AGA)对模型进行求解。以IEEE33总线配电网为例,基于蒙特卡罗随机模拟大规模电动汽车并网场景,比较研究了无序充电和智能充电两种控制模式下电动汽车负荷对配电网的影响,并验证了该方法的有效性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Charging Strategy Optimization of Electric Vehicle based on AGA
Because the charging load of electric vehicles is random in time and space, a large number of disorderly charging of electric vehicles will lead to the peak load of distribution network exceeding the limit of equipment, which will bring adverse effects on the operation of power grid. In order to smooth the daily load curve of distribution network, this paper establishes a solution model of intelligent charging control strategy for large-scale electric vehicle considering the charging demand constraints of electric vehicle users, and uses adaptive genetic algorithm (AGA) to solve the model. Taking IEEE33 bus distribution network as an example, based on Monte Carlo stochastic simulation of large-scale electric vehicle gridconnected scene, the impact of electric vehicle load on distribution network under two control modes of disorderly charging and intelligent charging is studied comparatively, and the effectiveness of this method is
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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