{"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.
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。