考虑车辆随机行为的车网融合在社区调峰中的潜力

Yalun Li , Kun Wang , Chaojie Xu , Yu Wu , Liguo Li , Yuejiu Zheng , Shichun Yang , Hewu Wang , Minggao Ouyang
{"title":"考虑车辆随机行为的车网融合在社区调峰中的潜力","authors":"Yalun Li ,&nbsp;Kun Wang ,&nbsp;Chaojie Xu ,&nbsp;Yu Wu ,&nbsp;Liguo Li ,&nbsp;Yuejiu Zheng ,&nbsp;Shichun Yang ,&nbsp;Hewu Wang ,&nbsp;Minggao Ouyang","doi":"10.1016/j.nxener.2024.100233","DOIUrl":null,"url":null,"abstract":"<div><div>With large-scale electric vehicles (EVs) promoted and connected to the power grid, the uncontrolled charging of EVs enlarges the peak-valley range of load in the distribution grid. To alleviate the peak-valley range and enhance the stability of the distribution grid, vehicle-grid integration (VGI) is proposed as an economic and potential solution. However, the impact of disorderly charging and the potential of VGI considering random user behavior requires clarification. This paper established a mixed-integer linear programming model with user behavior simulated by the Monte Carlo algorithm. The travel and charging behavior of EVs are provided by Monte Carlo simulation with characteristic parameters from statistical data of urban vehicle travel data. A digital model describing the VGI charging boundary is built to restrict the transition from uncontrolled charging to VGI. Through analysis of the global optimization results, the comparison of disorderly charging with VGI under different scenarios is provided to illustrate the effectiveness of avoiding load uplift and reducing load peak-valley range. In a typical residential community with 100 EVs per 1000 people, disorderly charging increases the peak load by 17.1%, while VGI, with a participation ratio of 30%, reduces the load range by 74.8%. This study clearly demonstrates the effectiveness of VGI and guides the implementation of VGI in the rapid growth of EVs.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"7 ","pages":"Article 100233"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The potentials of vehicle-grid integration on peak shaving of a community considering random behavior of aggregated vehicles\",\"authors\":\"Yalun Li ,&nbsp;Kun Wang ,&nbsp;Chaojie Xu ,&nbsp;Yu Wu ,&nbsp;Liguo Li ,&nbsp;Yuejiu Zheng ,&nbsp;Shichun Yang ,&nbsp;Hewu Wang ,&nbsp;Minggao Ouyang\",\"doi\":\"10.1016/j.nxener.2024.100233\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>With large-scale electric vehicles (EVs) promoted and connected to the power grid, the uncontrolled charging of EVs enlarges the peak-valley range of load in the distribution grid. To alleviate the peak-valley range and enhance the stability of the distribution grid, vehicle-grid integration (VGI) is proposed as an economic and potential solution. However, the impact of disorderly charging and the potential of VGI considering random user behavior requires clarification. This paper established a mixed-integer linear programming model with user behavior simulated by the Monte Carlo algorithm. The travel and charging behavior of EVs are provided by Monte Carlo simulation with characteristic parameters from statistical data of urban vehicle travel data. A digital model describing the VGI charging boundary is built to restrict the transition from uncontrolled charging to VGI. Through analysis of the global optimization results, the comparison of disorderly charging with VGI under different scenarios is provided to illustrate the effectiveness of avoiding load uplift and reducing load peak-valley range. In a typical residential community with 100 EVs per 1000 people, disorderly charging increases the peak load by 17.1%, while VGI, with a participation ratio of 30%, reduces the load range by 74.8%. This study clearly demonstrates the effectiveness of VGI and guides the implementation of VGI in the rapid growth of EVs.</div></div>\",\"PeriodicalId\":100957,\"journal\":{\"name\":\"Next Energy\",\"volume\":\"7 \",\"pages\":\"Article 100233\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Next Energy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2949821X24001388\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Next Energy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949821X24001388","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

随着大型电动汽车的推广和并网,电动汽车的不可控充电扩大了配电网负荷的峰谷范围。为了缓解配电网的峰谷差异,提高配电网的稳定性,提出了一种经济可行的解决方案——车网一体化。然而,无序充电的影响和考虑随机用户行为的VGI的潜力需要澄清。本文建立了一个混合整数线性规划模型,用蒙特卡罗算法模拟了用户行为。利用城市车辆出行数据统计数据中的特征参数,采用蒙特卡罗仿真方法对电动汽车的出行和充电行为进行模拟。建立了一个描述VGI充电边界的数字模型,以限制从非受控充电向VGI的过渡。通过对全局优化结果的分析,比较了不同场景下无序充电与VGI的效果,说明了避免负荷上升和减小负荷峰谷范围的有效性。在每1000人拥有100辆电动汽车的典型住宅社区中,无序充电使峰值负荷增加了17.1%,而VGI的参与率为30%,使负荷范围减少了74.8%。本研究清楚地证明了VGI的有效性,并指导了VGI在电动汽车快速增长中的实施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The potentials of vehicle-grid integration on peak shaving of a community considering random behavior of aggregated vehicles
With large-scale electric vehicles (EVs) promoted and connected to the power grid, the uncontrolled charging of EVs enlarges the peak-valley range of load in the distribution grid. To alleviate the peak-valley range and enhance the stability of the distribution grid, vehicle-grid integration (VGI) is proposed as an economic and potential solution. However, the impact of disorderly charging and the potential of VGI considering random user behavior requires clarification. This paper established a mixed-integer linear programming model with user behavior simulated by the Monte Carlo algorithm. The travel and charging behavior of EVs are provided by Monte Carlo simulation with characteristic parameters from statistical data of urban vehicle travel data. A digital model describing the VGI charging boundary is built to restrict the transition from uncontrolled charging to VGI. Through analysis of the global optimization results, the comparison of disorderly charging with VGI under different scenarios is provided to illustrate the effectiveness of avoiding load uplift and reducing load peak-valley range. In a typical residential community with 100 EVs per 1000 people, disorderly charging increases the peak load by 17.1%, while VGI, with a participation ratio of 30%, reduces the load range by 74.8%. This study clearly demonstrates the effectiveness of VGI and guides the implementation of VGI in the rapid growth of EVs.
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