{"title":"基于二元猫群算法的电力系统完全可观测性PMU优化配置","authors":"Ankur Srivastava, Sydulu Maheswarapu","doi":"10.1109/ENERGYECONOMICS.2015.7235114","DOIUrl":null,"url":null,"abstract":"This paper presents a meta-heuristic algorithm using Binary Cat Swarm Optimization (BCSO). BCSO is binary version of Cat Swarm Optimization (CSO) based on the observation of the behavior of cats. BCSO has two modes of operation: seeking mode and tracing mode. This proposed methodology is used for the optimal placement of phasor measurement units (PMUs) for complete observability of a power system. The objective of this optimization problem is the minimization of the total number of PMUs required by keeping the observability of the system intact. The proposed algorithm was examined with IEEE 14-bus and IEEE 30-bus test system and their results are presented in the paper. These results were also verified with different existing conventional and meta-heuristic algorithms such as binary particle swarm optimization, generalized integer linear programming and effective data structure based algorithm. It is first time that the proposed binary cat swarm optimization has been contemplated for the problem of optimal placement of PMUs.","PeriodicalId":130355,"journal":{"name":"2015 International Conference on Energy Economics and Environment (ICEEE)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Optimal PMU placement for complete power system observability using Binary Cat Swarm Optimization\",\"authors\":\"Ankur Srivastava, Sydulu Maheswarapu\",\"doi\":\"10.1109/ENERGYECONOMICS.2015.7235114\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a meta-heuristic algorithm using Binary Cat Swarm Optimization (BCSO). BCSO is binary version of Cat Swarm Optimization (CSO) based on the observation of the behavior of cats. BCSO has two modes of operation: seeking mode and tracing mode. This proposed methodology is used for the optimal placement of phasor measurement units (PMUs) for complete observability of a power system. The objective of this optimization problem is the minimization of the total number of PMUs required by keeping the observability of the system intact. The proposed algorithm was examined with IEEE 14-bus and IEEE 30-bus test system and their results are presented in the paper. These results were also verified with different existing conventional and meta-heuristic algorithms such as binary particle swarm optimization, generalized integer linear programming and effective data structure based algorithm. It is first time that the proposed binary cat swarm optimization has been contemplated for the problem of optimal placement of PMUs.\",\"PeriodicalId\":130355,\"journal\":{\"name\":\"2015 International Conference on Energy Economics and Environment (ICEEE)\",\"volume\":\"120 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Energy Economics and Environment (ICEEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ENERGYECONOMICS.2015.7235114\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Energy Economics and Environment (ICEEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ENERGYECONOMICS.2015.7235114","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal PMU placement for complete power system observability using Binary Cat Swarm Optimization
This paper presents a meta-heuristic algorithm using Binary Cat Swarm Optimization (BCSO). BCSO is binary version of Cat Swarm Optimization (CSO) based on the observation of the behavior of cats. BCSO has two modes of operation: seeking mode and tracing mode. This proposed methodology is used for the optimal placement of phasor measurement units (PMUs) for complete observability of a power system. The objective of this optimization problem is the minimization of the total number of PMUs required by keeping the observability of the system intact. The proposed algorithm was examined with IEEE 14-bus and IEEE 30-bus test system and their results are presented in the paper. These results were also verified with different existing conventional and meta-heuristic algorithms such as binary particle swarm optimization, generalized integer linear programming and effective data structure based algorithm. It is first time that the proposed binary cat swarm optimization has been contemplated for the problem of optimal placement of PMUs.