最优潮流的多目标差分进化

2009 International Conference on Power Engineering, Energy and Electrical Drives Pub Date : 2009-03-18 DOI:10.1109/POWERENG.2009.4915212

M. A. Abido, N. A. Al-Ali

{"title":"最优潮流的多目标差分进化","authors":"M. A. Abido, N. A. Al-Ali","doi":"10.1109/POWERENG.2009.4915212","DOIUrl":null,"url":null,"abstract":"This paper presents a multiobjective differential evolution (MODE) based approach to solve the optimal power flow (OPF) problem. OPF problem has been treated as a true multiobjective constrained optimization problem. Different objective functions and different operational constraints have been considered in the problem formulation. A clustering algorithm is applied to manage the size of the Pareto set. Also, an algorithm based on fuzzy set theory is used to extract the best compromise solution. Simulation results on IEEE-30 bus test system show the effectiveness of the proposed approach in solving true multi-objective OPF and also finding well distributed Pareto solutions.","PeriodicalId":246039,"journal":{"name":"2009 International Conference on Power Engineering, Energy and Electrical Drives","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"56","resultStr":"{\"title\":\"Multi-objective differential evolution for optimal power flow\",\"authors\":\"M. A. Abido, N. A. Al-Ali\",\"doi\":\"10.1109/POWERENG.2009.4915212\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a multiobjective differential evolution (MODE) based approach to solve the optimal power flow (OPF) problem. OPF problem has been treated as a true multiobjective constrained optimization problem. Different objective functions and different operational constraints have been considered in the problem formulation. A clustering algorithm is applied to manage the size of the Pareto set. Also, an algorithm based on fuzzy set theory is used to extract the best compromise solution. Simulation results on IEEE-30 bus test system show the effectiveness of the proposed approach in solving true multi-objective OPF and also finding well distributed Pareto solutions.\",\"PeriodicalId\":246039,\"journal\":{\"name\":\"2009 International Conference on Power Engineering, Energy and Electrical Drives\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-03-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"56\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Power Engineering, Energy and Electrical Drives\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/POWERENG.2009.4915212\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Power Engineering, Energy and Electrical Drives","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/POWERENG.2009.4915212","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 56

摘要

提出了一种基于多目标差分进化(MODE)的最优潮流求解方法。将OPF问题视为一个真正的多目标约束优化问题。在问题的表述中考虑了不同的目标函数和不同的操作约束。采用聚类算法来管理Pareto集合的大小。同时，采用基于模糊集理论的算法提取最佳妥协解。在IEEE-30总线测试系统上的仿真结果表明，该方法在求解真多目标OPF和找到分布良好的Pareto解方面是有效的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Multi-objective differential evolution for optimal power flow

This paper presents a multiobjective differential evolution (MODE) based approach to solve the optimal power flow (OPF) problem. OPF problem has been treated as a true multiobjective constrained optimization problem. Different objective functions and different operational constraints have been considered in the problem formulation. A clustering algorithm is applied to manage the size of the Pareto set. Also, an algorithm based on fuzzy set theory is used to extract the best compromise solution. Simulation results on IEEE-30 bus test system show the effectiveness of the proposed approach in solving true multi-objective OPF and also finding well distributed Pareto solutions.

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

2009 International Conference on Power Engineering, Energy and Electrical Drives

自引率

0.00%

发文量