基于Asaga的电动汽车快速充电站优化配置

F. Yuting, Zang Haixiang, Chen Ming, Shen Haiping, Miao Liheng, Wei Zhinong, Sun Guoqiang
{"title":"基于Asaga的电动汽车快速充电站优化配置","authors":"F. Yuting, Zang Haixiang, Chen Ming, Shen Haiping, Miao Liheng, Wei Zhinong, Sun Guoqiang","doi":"10.1109/CICED.2018.8592515","DOIUrl":null,"url":null,"abstract":"Construction of rapid charging stations is one of the most important keys to the popularization of electric vehicles (EVs). This paper proposed a multi-objective electric vehicle rapid charging station planning model which considers the profits of users and charging stations. A sizing model is proposed based on queuing theory aiming at minimizing the capacity while satisfy the constraints. A locating model aiming at minimizing the construction cost of charging stations and the distance between users and charging stations simultaneously is proposed. The multiobjective problem is transformed into a single objective problem by utilizing weighting coefficients and the problem is solved by Adaptive Simulated Annealing Genetic Algorithm (ASAGA). Subsequently, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was utilized to obtain the terminal planning result. The simulation results have demonstrated the effectiveness and feasibility of the proposed model.","PeriodicalId":142885,"journal":{"name":"2018 China International Conference on Electricity Distribution (CICED)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Optimal Allocation for Electric Vehicle Rapid Charging Stations Based on Asaga\",\"authors\":\"F. Yuting, Zang Haixiang, Chen Ming, Shen Haiping, Miao Liheng, Wei Zhinong, Sun Guoqiang\",\"doi\":\"10.1109/CICED.2018.8592515\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Construction of rapid charging stations is one of the most important keys to the popularization of electric vehicles (EVs). This paper proposed a multi-objective electric vehicle rapid charging station planning model which considers the profits of users and charging stations. A sizing model is proposed based on queuing theory aiming at minimizing the capacity while satisfy the constraints. A locating model aiming at minimizing the construction cost of charging stations and the distance between users and charging stations simultaneously is proposed. The multiobjective problem is transformed into a single objective problem by utilizing weighting coefficients and the problem is solved by Adaptive Simulated Annealing Genetic Algorithm (ASAGA). Subsequently, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was utilized to obtain the terminal planning result. The simulation results have demonstrated the effectiveness and feasibility of the proposed model.\",\"PeriodicalId\":142885,\"journal\":{\"name\":\"2018 China International Conference on Electricity Distribution (CICED)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 China International Conference on Electricity Distribution (CICED)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CICED.2018.8592515\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 China International Conference on Electricity Distribution (CICED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICED.2018.8592515","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

快速充电站的建设是电动汽车普及的关键之一。提出了一种考虑用户和充电站利益的多目标电动汽车快速充电站规划模型。提出了一种基于排队论的分级模型,以满足约束条件下最小化容量为目标。提出了一种以充电站建设成本最小、用户与充电站之间距离最小为目标的定位模型。利用加权系数将多目标问题转化为单目标问题,采用自适应模拟退火遗传算法(ASAGA)求解。随后,利用TOPSIS (Order Preference by Similarity to Ideal Solution)算法得到了终端规划结果。仿真结果验证了该模型的有效性和可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Optimal Allocation for Electric Vehicle Rapid Charging Stations Based on Asaga
Construction of rapid charging stations is one of the most important keys to the popularization of electric vehicles (EVs). This paper proposed a multi-objective electric vehicle rapid charging station planning model which considers the profits of users and charging stations. A sizing model is proposed based on queuing theory aiming at minimizing the capacity while satisfy the constraints. A locating model aiming at minimizing the construction cost of charging stations and the distance between users and charging stations simultaneously is proposed. The multiobjective problem is transformed into a single objective problem by utilizing weighting coefficients and the problem is solved by Adaptive Simulated Annealing Genetic Algorithm (ASAGA). Subsequently, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was utilized to obtain the terminal planning result. The simulation results have demonstrated the effectiveness and feasibility of the proposed model.
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
期刊最新文献
A Deep Game Bidding Model and Practice of Electricity Market Research on Fault Location for UHV Half-wavelength Transmission Lines Comprehensive Evaluation of Insulation Performance of DC XLPE Cables Improvement of Distribution System Maintenance Plan Based on Risk Level The Application of Transient Calculation for Loop Closing of Distribution Network Based on The DSA
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1