{"title":"Power System Stabilizers Layout via Flower Pollination Algorithm","authors":"E. Ali","doi":"10.37394/232027.2022.4.12","DOIUrl":null,"url":null,"abstract":"In this article, the optimum layout of Power System Stabilizers (PSSs) using Flower Pollination Algorithm (FPA) is developed in a multimachine environment. The PSSs values tuning problem is turned into an optimization task which is treated by FPA. FPA is used to check for optimum controller parameters by reducing an eigenvalues based objective function involving the damping factor, and the damping ratio of the lightly damped modes. The implementation of the developed FPA based PSSs (FPAPSS) is compared with Particle Swarm Optimization (PSO) based PSSs (PSOPSS) and the Conventional PSSs (CPSS) for various loading conditions and disturbances. The results of the developed FPAPSS are confirmed via time domain analysis, eigenvalues and some indices. Also, the results are introduced to prove the effectiveness of the developed algorithm over the PSO and conventional one.","PeriodicalId":145183,"journal":{"name":"International Journal of Electrical Engineering and Computer Science","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Electrical Engineering and Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37394/232027.2022.4.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this article, the optimum layout of Power System Stabilizers (PSSs) using Flower Pollination Algorithm (FPA) is developed in a multimachine environment. The PSSs values tuning problem is turned into an optimization task which is treated by FPA. FPA is used to check for optimum controller parameters by reducing an eigenvalues based objective function involving the damping factor, and the damping ratio of the lightly damped modes. The implementation of the developed FPA based PSSs (FPAPSS) is compared with Particle Swarm Optimization (PSO) based PSSs (PSOPSS) and the Conventional PSSs (CPSS) for various loading conditions and disturbances. The results of the developed FPAPSS are confirmed via time domain analysis, eigenvalues and some indices. Also, the results are introduced to prove the effectiveness of the developed algorithm over the PSO and conventional one.