{"title":"Particle Swarm Optimization with Time Varying Acceleration Coefficients for Congestion Management","authors":"E. Muneender, D. Vinodkumar","doi":"10.1109/STUDENT.2012.6408372","DOIUrl":null,"url":null,"abstract":"This paper presents an application of Particle Swarm Optimization with Time Varying Acceleration Coefficients (PSO-TVAC) algorithm for Congestion Management (CM) using optimal re-scheduling of real power generation. The optimal rescheduling of powers in a pool model is formulated as a constrained nonlinear optimization problem. The PSO-TVAC algorithm is proposed to assess the generation re-schedule to relieve the congestion optimally. The generators participating in the congestion management are selected based on real power transmission congestion distribution factors (PTCDFs). The effectiveness of the proposed method has been tested on 39-bus New England Test system. The simulation experiments reveal that the proposed method performs better than conventional PSO.","PeriodicalId":282263,"journal":{"name":"2012 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (STUDENT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (STUDENT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/STUDENT.2012.6408372","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 presents an application of Particle Swarm Optimization with Time Varying Acceleration Coefficients (PSO-TVAC) algorithm for Congestion Management (CM) using optimal re-scheduling of real power generation. The optimal rescheduling of powers in a pool model is formulated as a constrained nonlinear optimization problem. The PSO-TVAC algorithm is proposed to assess the generation re-schedule to relieve the congestion optimally. The generators participating in the congestion management are selected based on real power transmission congestion distribution factors (PTCDFs). The effectiveness of the proposed method has been tested on 39-bus New England Test system. The simulation experiments reveal that the proposed method performs better than conventional PSO.