{"title":"Improving Reliability on Distribution Systems Using BPSO for Device Placement","authors":"R. Bhugwandeen, A. Saha","doi":"10.1109/ROBOMECH.2019.8704777","DOIUrl":null,"url":null,"abstract":"This paper presents a Binary Particle Swarm Optimization algorithm for strategic placement of additional protection devices to improve reliability on real KwaZulu-Natal distribution networks, each with unique characteristics. Historical data was used to model the performance of the components and simulated using DigSilent PowerFactory to evaluate reliability on the system. The results of each case study considered are reported and discussed to find the most economically feasible solution. The Binary Particle Swarm Optimization algorithm introduced results in minimal improvements after the addition of switches. Nonetheless, there are significant improvements in System Average Interruption Duration Index of up to 21% and Energy Not Served of 11% after the placement of additional reclosers.","PeriodicalId":344332,"journal":{"name":"2019 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa (SAUPEC/RobMech/PRASA)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa (SAUPEC/RobMech/PRASA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBOMECH.2019.8704777","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
This paper presents a Binary Particle Swarm Optimization algorithm for strategic placement of additional protection devices to improve reliability on real KwaZulu-Natal distribution networks, each with unique characteristics. Historical data was used to model the performance of the components and simulated using DigSilent PowerFactory to evaluate reliability on the system. The results of each case study considered are reported and discussed to find the most economically feasible solution. The Binary Particle Swarm Optimization algorithm introduced results in minimal improvements after the addition of switches. Nonetheless, there are significant improvements in System Average Interruption Duration Index of up to 21% and Energy Not Served of 11% after the placement of additional reclosers.