基于鸡群优化的电动汽车充电站多目标运行启发式方法

IF 9 1区 工程技术 Q1 ENERGY & FUELS Energy Pub Date : 2024-11-09 DOI:10.1016/j.energy.2024.133749
Sulabh Sachan
{"title":"基于鸡群优化的电动汽车充电站多目标运行启发式方法","authors":"Sulabh Sachan","doi":"10.1016/j.energy.2024.133749","DOIUrl":null,"url":null,"abstract":"<div><div>The emissions of greenhouse gasses and high vehicle operating cost are the widespread issues, majorly derived by the large number of conventional fossil-fuel based vehicles. This had led many automobile manufacturers to move towards electric vehicles (EVs). However, EVs significantly impact the power grid because of the energy needed to re-energize their batteries. This study introduces an effective multi-objective function that utilizes Chicken Swarm Optimization (CSO) to perform the optimal operation for the Charging Stations (CSs) within the distribution network. The aim here is to reduce the power losses, the average voltage deviation index (AVDI), voltage stability index (VSI), and the impact of harmonic distortion. The simulations are conducted on 69-bus radial distribution network.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133749"},"PeriodicalIF":9.0000,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Heuristics for multi-objective operation of EV charging stations based on Chicken Swarm Optimization\",\"authors\":\"Sulabh Sachan\",\"doi\":\"10.1016/j.energy.2024.133749\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The emissions of greenhouse gasses and high vehicle operating cost are the widespread issues, majorly derived by the large number of conventional fossil-fuel based vehicles. This had led many automobile manufacturers to move towards electric vehicles (EVs). However, EVs significantly impact the power grid because of the energy needed to re-energize their batteries. This study introduces an effective multi-objective function that utilizes Chicken Swarm Optimization (CSO) to perform the optimal operation for the Charging Stations (CSs) within the distribution network. The aim here is to reduce the power losses, the average voltage deviation index (AVDI), voltage stability index (VSI), and the impact of harmonic distortion. The simulations are conducted on 69-bus radial distribution network.</div></div>\",\"PeriodicalId\":11647,\"journal\":{\"name\":\"Energy\",\"volume\":\"313 \",\"pages\":\"Article 133749\"},\"PeriodicalIF\":9.0000,\"publicationDate\":\"2024-11-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0360544224035278\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0360544224035278","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0

摘要

温室气体排放和高昂的汽车运营成本是普遍存在的问题,这主要是由大量使用化石燃料的传统汽车造成的。这促使许多汽车制造商转向电动汽车(EV)。然而,电动汽车由于需要为电池重新充电,因此对电网产生了很大影响。本研究引入了一种有效的多目标函数,利用鸡群优化(CSO)为配电网络中的充电站(CS)执行最佳操作。其目的是减少功率损耗、平均电压偏差指数(AVDI)、电压稳定指数(VSI)和谐波畸变的影响。模拟在 69 总线径向配电网络上进行。
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
Heuristics for multi-objective operation of EV charging stations based on Chicken Swarm Optimization
The emissions of greenhouse gasses and high vehicle operating cost are the widespread issues, majorly derived by the large number of conventional fossil-fuel based vehicles. This had led many automobile manufacturers to move towards electric vehicles (EVs). However, EVs significantly impact the power grid because of the energy needed to re-energize their batteries. This study introduces an effective multi-objective function that utilizes Chicken Swarm Optimization (CSO) to perform the optimal operation for the Charging Stations (CSs) within the distribution network. The aim here is to reduce the power losses, the average voltage deviation index (AVDI), voltage stability index (VSI), and the impact of harmonic distortion. The simulations are conducted on 69-bus radial distribution network.
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
Energy
Energy 工程技术-能源与燃料
CiteScore
15.30
自引率
14.40%
发文量
0
审稿时长
14.2 weeks
期刊介绍: Energy is a multidisciplinary, international journal that publishes research and analysis in the field of energy engineering. Our aim is to become a leading peer-reviewed platform and a trusted source of information for energy-related topics. The journal covers a range of areas including mechanical engineering, thermal sciences, and energy analysis. We are particularly interested in research on energy modelling, prediction, integrated energy systems, planning, and management. Additionally, we welcome papers on energy conservation, efficiency, biomass and bioenergy, renewable energy, electricity supply and demand, energy storage, buildings, and economic and policy issues. These topics should align with our broader multidisciplinary focus.
期刊最新文献
High temperature heat pumps for industrial heating processes using water as refrigerant Exploration on deep pulverized coal activation and ultra-low NOx emission strategies with novel purifying-combustion technology Collaborative strategy towards a resilient urban energy system: Evidence from a tripartite evolutionary game model Household, sociodemographic, building and land cover factors affecting residential summer electricity consumption: A systematic statistical study in Phoenix, AZ Economic benefits for the metallurgical industry from co-combusting pyrolysis gas from waste
×
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