{"title":"Multi-objective optimal active power dispatch using swarm optimization techniques","authors":"G. Goyal, H. Mehta","doi":"10.1109/NUICONE.2015.7449590","DOIUrl":null,"url":null,"abstract":"This paper deals with application of swarm intelligence based algorithms to solve optimal active power dispatch problem in an efficient manner. In this paper well established artificial intelligent algorithms viz cuckoo search (CS) method; Particle swarm optimization (PSO) and Modified PSO are used to solve a multi-objective optimal power flow (OPF) problem. Some modifications in PSO are carried to enhance its efficiency and search ability. Here combined composite function of fuel cost and emission minimization has been considered. These two objectives are combined into single function of cost with the help of price factor and weight ratios. All three methods are implemented on IEEE 30-bus 6-Generator system and simulation results are compared. The composite results demonstrate the potential of Modified PSO and Cuckoo search method to solve the combined problem of economic dispatch with emission control.","PeriodicalId":131332,"journal":{"name":"2015 5th Nirma University International Conference on Engineering (NUiCONE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 5th Nirma University International Conference on Engineering (NUiCONE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NUICONE.2015.7449590","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
This paper deals with application of swarm intelligence based algorithms to solve optimal active power dispatch problem in an efficient manner. In this paper well established artificial intelligent algorithms viz cuckoo search (CS) method; Particle swarm optimization (PSO) and Modified PSO are used to solve a multi-objective optimal power flow (OPF) problem. Some modifications in PSO are carried to enhance its efficiency and search ability. Here combined composite function of fuel cost and emission minimization has been considered. These two objectives are combined into single function of cost with the help of price factor and weight ratios. All three methods are implemented on IEEE 30-bus 6-Generator system and simulation results are compared. The composite results demonstrate the potential of Modified PSO and Cuckoo search method to solve the combined problem of economic dispatch with emission control.