Optimal placement of charging stations using CSO-TLBO algorithm

S. Deb, K. Kalita, Xiao-zhi Gao, K. Tammi, P. Mahanta
{"title":"Optimal placement of charging stations using CSO-TLBO algorithm","authors":"S. Deb, K. Kalita, Xiao-zhi Gao, K. Tammi, P. Mahanta","doi":"10.1109/ICRCICN.2017.8234486","DOIUrl":null,"url":null,"abstract":"The growing apprehension regarding greenhouse gas emission accompanied by fossil fuel depletion has instigated the electrification of transportation sector. As a consequence of this Electric Vehicle (EV) has emerged as an environment friendly solution for the automobile industry. For large scale deployment of EVs development of proper charging infrastructure is indispensable. Charging stations (CS) must be placed in the transport network in such a way that the distribution network parameters are least affected. This work proposes a novel approach for co-ordinated planning of EV charging infrastructures considering superimposition of both transport and distribution network. This approach is validated on IEEE 33 bus distribution network superimposed with 25 node road network. The capability of a new hybrid algorithm which is an amalgamation of Chicken Swarm Algorithm (CSO) and Teaching Learning Based Optimization Algorithm (TLBO) is utilized in this work for attaining optimal solution.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"173 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRCICN.2017.8234486","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17

Abstract

The growing apprehension regarding greenhouse gas emission accompanied by fossil fuel depletion has instigated the electrification of transportation sector. As a consequence of this Electric Vehicle (EV) has emerged as an environment friendly solution for the automobile industry. For large scale deployment of EVs development of proper charging infrastructure is indispensable. Charging stations (CS) must be placed in the transport network in such a way that the distribution network parameters are least affected. This work proposes a novel approach for co-ordinated planning of EV charging infrastructures considering superimposition of both transport and distribution network. This approach is validated on IEEE 33 bus distribution network superimposed with 25 node road network. The capability of a new hybrid algorithm which is an amalgamation of Chicken Swarm Algorithm (CSO) and Teaching Learning Based Optimization Algorithm (TLBO) is utilized in this work for attaining optimal solution.
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
基于CSO-TLBO算法的充电站优化布局
随着化石燃料的枯竭,对温室气体排放的担忧日益增加,促使了交通部门的电气化。因此,电动汽车(EV)已经成为汽车工业的一种环保解决方案。对于电动汽车的大规模部署,发展适当的充电基础设施是必不可少的。充电站(CS)必须以对配电网参数影响最小的方式放置在交通网络中。本研究提出了一种考虑运输和配送网络叠加的电动汽车充电基础设施协调规划的新方法。该方法在IEEE 33总线配网叠加25节点路网上进行了验证。本文利用鸡群算法(CSO)和基于教学的优化算法(TLBO)相结合的一种新的混合算法的能力来获得最优解。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
RGB image encryption using hyper chaotic system Characterisation of wireless network traffic: Fractality and stationarity Security risk assessment in online social networking: A detailed survey Optimalized hydel-thermic operative planning using IRECGA Designing an enhanced ZRP algorithm for MANET and simulation using OPNET
×
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