Economic operation of two area power system through gravitational search algorithm

Anumeha, K. Yadav, S. Agarwal
{"title":"Economic operation of two area power system through gravitational search algorithm","authors":"Anumeha, K. Yadav, S. Agarwal","doi":"10.1109/RDCAPE.2015.7281394","DOIUrl":null,"url":null,"abstract":"A new Meta heuristic optimization method based on Newton's laws of gravity and motion has been developed by Rashedi E. et al. known as Gravitational Search Algorithm (GSA). In this paper GSA is implemented to economic operation of a two area power system and computes how much power has to be generated internally in an area and how much power has to be borrowed from other area through tie-line for a specified load in most economical sense. This method is explained with an example and the result obtained by the proposed method is compared with by particle swarm optimization (PSO) as reported in literature. It has been shown that this method is more efficient and takes less computation time than PSO.","PeriodicalId":403256,"journal":{"name":"2015 International Conference on Recent Developments in Control, Automation and Power Engineering (RDCAPE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Recent Developments in Control, Automation and Power Engineering (RDCAPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RDCAPE.2015.7281394","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

A new Meta heuristic optimization method based on Newton's laws of gravity and motion has been developed by Rashedi E. et al. known as Gravitational Search Algorithm (GSA). In this paper GSA is implemented to economic operation of a two area power system and computes how much power has to be generated internally in an area and how much power has to be borrowed from other area through tie-line for a specified load in most economical sense. This method is explained with an example and the result obtained by the proposed method is compared with by particle swarm optimization (PSO) as reported in literature. It has been shown that this method is more efficient and takes less computation time than PSO.
利用引力搜索算法求解两区电力系统的经济运行
Rashedi E. et al.提出了一种新的基于牛顿引力和运动定律的Meta启发式优化方法,称为引力搜索算法(gravity Search Algorithm, GSA)。本文将GSA应用于两区电力系统的经济运行中,在最经济的意义上计算某一特定负荷下,某一区域内部需要发多少电和通过联络线从其他区域借用多少电。通过实例对该方法进行了说明,并与文献报道的粒子群优化(PSO)方法进行了比较。结果表明,该方法比粒子群算法效率高,计算时间短。
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 求助全文
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:604180095
Book学术官方微信