{"title":"SVC nonlinear optimal control with comparison to GA based conventional control in power system stability improvement","authors":"Debasish Mondal","doi":"10.1109/ICECI.2014.6767382","DOIUrl":null,"url":null,"abstract":"This paper aims to design a nonlinear control scheme for a Static Var Compensator (SVC) in order to improve dynamic stability in a Single Machine Infinite Bus (SMIB) power system. The nonlinear model of the SMIB system is exactly linearized applying feedback linearization method, and the optimal control law is estimated by the Linear Quadratic Regulator (LQR) principle. The performance of the proposed nonlinear controller is compared with the performance of a conventional controller whose parameters are optimized through Genetic Algorithm (GA). The results and effectiveness of the proposed control schemes are presented employing time domain simulation and analysis. It has been observed that, in comparison with the conventional controller, significant improvements in dynamic stability of the test power system are achieved by the proposed nonlinear control strategy.","PeriodicalId":315219,"journal":{"name":"International Conference on Electronics, Communication and Instrumentation (ICECI)","volume":"218 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Electronics, Communication and Instrumentation (ICECI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECI.2014.6767382","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 aims to design a nonlinear control scheme for a Static Var Compensator (SVC) in order to improve dynamic stability in a Single Machine Infinite Bus (SMIB) power system. The nonlinear model of the SMIB system is exactly linearized applying feedback linearization method, and the optimal control law is estimated by the Linear Quadratic Regulator (LQR) principle. The performance of the proposed nonlinear controller is compared with the performance of a conventional controller whose parameters are optimized through Genetic Algorithm (GA). The results and effectiveness of the proposed control schemes are presented employing time domain simulation and analysis. It has been observed that, in comparison with the conventional controller, significant improvements in dynamic stability of the test power system are achieved by the proposed nonlinear control strategy.