Chaotic Adaptive Particle Swarm Optimisation using logistics and Gauss map for solving cubic cost economic dispatch problem

C. Rani, E. Petkov, K. Busawon, M. Farrag
{"title":"Chaotic Adaptive Particle Swarm Optimisation using logistics and Gauss map for solving cubic cost economic dispatch problem","authors":"C. Rani, E. Petkov, K. Busawon, M. Farrag","doi":"10.1109/EFEA.2014.7059939","DOIUrl":null,"url":null,"abstract":"This paper proposes Chaotic Adaptive Particle Swarm Optimisation (CAPSO) algorithm to solve Cubic Cost Economic Dispatch (CCED) problem. A Chaotic Local Search operator (CLS) is introduced in the proposed algorithm to avoid premature convergence. The basic strategy of the proposed algorithm is combining PSO with Adaptive Inertia Weight Factor (AIWF) and CLS, in which PSO with AIWF is applied to perform global exploration and CLS is used to perform exploitation to find the optimal solution. Logistics and Gauss map technique is used in performing CLS and the results are compared. The applicability and high feasibility of the proposed method is validated on a standard 5-generator test system. The simulation results confirm that this algorithm is capable of giving higher quality solutions with fast convergence characteristics.","PeriodicalId":129568,"journal":{"name":"3rd International Symposium on Environmental Friendly Energies and Applications (EFEA)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"3rd International Symposium on Environmental Friendly Energies and Applications (EFEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EFEA.2014.7059939","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

This paper proposes Chaotic Adaptive Particle Swarm Optimisation (CAPSO) algorithm to solve Cubic Cost Economic Dispatch (CCED) problem. A Chaotic Local Search operator (CLS) is introduced in the proposed algorithm to avoid premature convergence. The basic strategy of the proposed algorithm is combining PSO with Adaptive Inertia Weight Factor (AIWF) and CLS, in which PSO with AIWF is applied to perform global exploration and CLS is used to perform exploitation to find the optimal solution. Logistics and Gauss map technique is used in performing CLS and the results are compared. The applicability and high feasibility of the proposed method is validated on a standard 5-generator test system. The simulation results confirm that this algorithm is capable of giving higher quality solutions with fast convergence characteristics.
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
基于物流和高斯映射的混沌自适应粒子群优化求解三次成本经济调度问题
针对三次成本经济调度问题,提出混沌自适应粒子群算法(CAPSO)。该算法引入了混沌局部搜索算子(CLS),避免了算法的过早收敛。该算法的基本策略是将粒子群算法与自适应惯性权重因子(AIWF)和自适应惯性权重因子(CLS)相结合,利用自适应惯性权重因子(AIWF)和自适应惯性权重因子(CLS)进行全局搜索,利用自适应惯性权重因子(CLS)进行挖掘,找到最优解。运用物流和高斯图技术实现了CLS,并对结果进行了比较。在一个标准的5发电机测试系统上验证了该方法的适用性和高可行性。仿真结果表明,该算法能够给出高质量的解,且收敛速度快。
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
Chaotic Adaptive Particle Swarm Optimisation using logistics and Gauss map for solving cubic cost economic dispatch problem Harnessing electric energy from vehicle induced wind gust Left invertibility of piecewise smooth system: The Alpazur case A simple method to determine the optimal location of active flow controllers on wind turbine blades MPPT control of variable speed wind generators with squirrel cage induction machines
×
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