{"title":"基于网络重构的配电网网损最小的粒子群算法与粒子群算法的比较分析","authors":"Ankush Tandon, D. Saxena","doi":"10.1109/CIPECH.2014.7019093","DOIUrl":null,"url":null,"abstract":"This paper presents an effective methodology, to solve the Distribution Network Reconfiguration (DNR) problem using Selective Particle Swarm Optimization (SPSO) algorithm which aims at finding the best radial operating configuration that minimizes the power losses of the system while satisfying the imposed operating constraints. The algorithm is a simple modification of Binary Particle Swarm Optimization (BPSO) where the search space is selective. To demonstrate the performance and effectiveness of the proposed method a comparative analysis of SPSO with BPSO for network reconfiguration, under four different load levels, namely base, light, medium and heavy, on 33-bus and 69-bus radial distribution system is presented. Test results have shown that SPSO can effectively ensure loss minimization with better convergence characteristics and improved voltage profile as compared to BPSO.","PeriodicalId":170027,"journal":{"name":"2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH)","volume":"156 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"A comparative analysis of SPSO and BPSO for power loss minimization in distribution system using network reconfiguration\",\"authors\":\"Ankush Tandon, D. Saxena\",\"doi\":\"10.1109/CIPECH.2014.7019093\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an effective methodology, to solve the Distribution Network Reconfiguration (DNR) problem using Selective Particle Swarm Optimization (SPSO) algorithm which aims at finding the best radial operating configuration that minimizes the power losses of the system while satisfying the imposed operating constraints. The algorithm is a simple modification of Binary Particle Swarm Optimization (BPSO) where the search space is selective. To demonstrate the performance and effectiveness of the proposed method a comparative analysis of SPSO with BPSO for network reconfiguration, under four different load levels, namely base, light, medium and heavy, on 33-bus and 69-bus radial distribution system is presented. Test results have shown that SPSO can effectively ensure loss minimization with better convergence characteristics and improved voltage profile as compared to BPSO.\",\"PeriodicalId\":170027,\"journal\":{\"name\":\"2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH)\",\"volume\":\"156 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIPECH.2014.7019093\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIPECH.2014.7019093","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A comparative analysis of SPSO and BPSO for power loss minimization in distribution system using network reconfiguration
This paper presents an effective methodology, to solve the Distribution Network Reconfiguration (DNR) problem using Selective Particle Swarm Optimization (SPSO) algorithm which aims at finding the best radial operating configuration that minimizes the power losses of the system while satisfying the imposed operating constraints. The algorithm is a simple modification of Binary Particle Swarm Optimization (BPSO) where the search space is selective. To demonstrate the performance and effectiveness of the proposed method a comparative analysis of SPSO with BPSO for network reconfiguration, under four different load levels, namely base, light, medium and heavy, on 33-bus and 69-bus radial distribution system is presented. Test results have shown that SPSO can effectively ensure loss minimization with better convergence characteristics and improved voltage profile as compared to BPSO.