{"title":"基于选择性粒子群优化算法的配电网优化重构","authors":"Ankush Tandon, D. Saxena","doi":"10.1109/ICPCES.2014.7062806","DOIUrl":null,"url":null,"abstract":"This paper presents an effective methodology to optimally reconfigure an electrical distribution network. Selective Particle Swarm Optimization (SPSO) algorithm is proposed to find the optimal combination of switches that results in a radial configuration with minimum system power loss. SPSO is a modified Binary Particle Swarm Optimization (BPSO) with selective search space. Comparative analysis of SPSO with BPSO for network reconfiguration, under four different loading conditions, namely base, light, medium and heavy, on IEEE 69 bus system is presented to demonstrate the suitability of the proposed method. It is observed that SPSO outperforms BPSO in terms of quality of solution, voltage profile, convergence characteristics and time elapsed to complete optimization process.","PeriodicalId":337074,"journal":{"name":"2014 International Conference on Power, Control and Embedded Systems (ICPCES)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Optimal reconfiguration of electrical distribution network using selective particle swarm optimization algorithm\",\"authors\":\"Ankush Tandon, D. Saxena\",\"doi\":\"10.1109/ICPCES.2014.7062806\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an effective methodology to optimally reconfigure an electrical distribution network. Selective Particle Swarm Optimization (SPSO) algorithm is proposed to find the optimal combination of switches that results in a radial configuration with minimum system power loss. SPSO is a modified Binary Particle Swarm Optimization (BPSO) with selective search space. Comparative analysis of SPSO with BPSO for network reconfiguration, under four different loading conditions, namely base, light, medium and heavy, on IEEE 69 bus system is presented to demonstrate the suitability of the proposed method. It is observed that SPSO outperforms BPSO in terms of quality of solution, voltage profile, convergence characteristics and time elapsed to complete optimization process.\",\"PeriodicalId\":337074,\"journal\":{\"name\":\"2014 International Conference on Power, Control and Embedded Systems (ICPCES)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Power, Control and Embedded Systems (ICPCES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPCES.2014.7062806\",\"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 International Conference on Power, Control and Embedded Systems (ICPCES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPCES.2014.7062806","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal reconfiguration of electrical distribution network using selective particle swarm optimization algorithm
This paper presents an effective methodology to optimally reconfigure an electrical distribution network. Selective Particle Swarm Optimization (SPSO) algorithm is proposed to find the optimal combination of switches that results in a radial configuration with minimum system power loss. SPSO is a modified Binary Particle Swarm Optimization (BPSO) with selective search space. Comparative analysis of SPSO with BPSO for network reconfiguration, under four different loading conditions, namely base, light, medium and heavy, on IEEE 69 bus system is presented to demonstrate the suitability of the proposed method. It is observed that SPSO outperforms BPSO in terms of quality of solution, voltage profile, convergence characteristics and time elapsed to complete optimization process.