{"title":"Optimal phasor measuring unit placement by binary particle swarm optimization","authors":"S. Kumari, Pratima Walde, Asif Iqbal, A. Tyagi","doi":"10.1109/ICCCNT.2017.8204051","DOIUrl":null,"url":null,"abstract":"This work presents a technique for the optimal Phasor Measurement Units (PMUs) placement for complete power network observability with number of PMUs as minimum as possible. Due to the high installation cost of PMUs it is necessary to make the system fully observable with minimum PMUs. A binary particle swarm optimization method (BPSO) is implemented on IEEE standard system and Puducherry 17 bus system. The BPSO method of Optimum PMU Placement can therefore be applied to any power system to make the system fully observable with different aspects of the power system. The obtained results are compared with other techniques and it is found that Adaptive GA, GILP, SA, TS, BSA and the proposed BPSO method was found better.","PeriodicalId":6581,"journal":{"name":"2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT)","volume":"34 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCNT.2017.8204051","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 work presents a technique for the optimal Phasor Measurement Units (PMUs) placement for complete power network observability with number of PMUs as minimum as possible. Due to the high installation cost of PMUs it is necessary to make the system fully observable with minimum PMUs. A binary particle swarm optimization method (BPSO) is implemented on IEEE standard system and Puducherry 17 bus system. The BPSO method of Optimum PMU Placement can therefore be applied to any power system to make the system fully observable with different aspects of the power system. The obtained results are compared with other techniques and it is found that Adaptive GA, GILP, SA, TS, BSA and the proposed BPSO method was found better.