{"title":"一种基于最佳引导人工蜂群算法的无功优化技术","authors":"A. Thorat, I. Korachagaon, A. Mulla","doi":"10.1109/ICCPEIC45300.2019.9082408","DOIUrl":null,"url":null,"abstract":"Reactive power play an important role in voltage stability and economic activities of power system. To maintain power quality and security, voltage at each bus should be within its acceptable limit. Reactive power is one of the important aspects of active power loss minimization. Optimizing reactive power is a process of minimizing total active power loss by handling all the parameters of generation and transmission network without violating any specified constraints. The complex nonlinear optimization problem can be solved by classical optimization technique and experimental based technique. For handling wide complex network the experiment based techniques gives good results over numerical technique in most of the cases. This paper presents an application of gbest ABC algorithm to solve reactive power optimization problem. gbest guided ABC algorithm uses swarm intelligence techniques. To check the effectiveness and robustness of gbest-guided ABC algorithm it is applied on IEEE 30, IEEE57 and IEEE 118 standard test bus system. To validate results of gbest – guided ABC algorithm for the application of reactive power optimization problem it is compared with existing available literature data. The statistical analysis of gbest guided ABC algorithm is also carried out for IEEE 30, IEEE57 and IEEE 118 standard test bus system.","PeriodicalId":120930,"journal":{"name":"2019 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A technique to optimize reactive power using gbest Guided Artificial Bee Colony Algorithm\",\"authors\":\"A. Thorat, I. Korachagaon, A. Mulla\",\"doi\":\"10.1109/ICCPEIC45300.2019.9082408\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Reactive power play an important role in voltage stability and economic activities of power system. To maintain power quality and security, voltage at each bus should be within its acceptable limit. Reactive power is one of the important aspects of active power loss minimization. Optimizing reactive power is a process of minimizing total active power loss by handling all the parameters of generation and transmission network without violating any specified constraints. The complex nonlinear optimization problem can be solved by classical optimization technique and experimental based technique. For handling wide complex network the experiment based techniques gives good results over numerical technique in most of the cases. This paper presents an application of gbest ABC algorithm to solve reactive power optimization problem. gbest guided ABC algorithm uses swarm intelligence techniques. To check the effectiveness and robustness of gbest-guided ABC algorithm it is applied on IEEE 30, IEEE57 and IEEE 118 standard test bus system. To validate results of gbest – guided ABC algorithm for the application of reactive power optimization problem it is compared with existing available literature data. The statistical analysis of gbest guided ABC algorithm is also carried out for IEEE 30, IEEE57 and IEEE 118 standard test bus system.\",\"PeriodicalId\":120930,\"journal\":{\"name\":\"2019 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)\",\"volume\":\"98 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCPEIC45300.2019.9082408\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCPEIC45300.2019.9082408","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A technique to optimize reactive power using gbest Guided Artificial Bee Colony Algorithm
Reactive power play an important role in voltage stability and economic activities of power system. To maintain power quality and security, voltage at each bus should be within its acceptable limit. Reactive power is one of the important aspects of active power loss minimization. Optimizing reactive power is a process of minimizing total active power loss by handling all the parameters of generation and transmission network without violating any specified constraints. The complex nonlinear optimization problem can be solved by classical optimization technique and experimental based technique. For handling wide complex network the experiment based techniques gives good results over numerical technique in most of the cases. This paper presents an application of gbest ABC algorithm to solve reactive power optimization problem. gbest guided ABC algorithm uses swarm intelligence techniques. To check the effectiveness and robustness of gbest-guided ABC algorithm it is applied on IEEE 30, IEEE57 and IEEE 118 standard test bus system. To validate results of gbest – guided ABC algorithm for the application of reactive power optimization problem it is compared with existing available literature data. The statistical analysis of gbest guided ABC algorithm is also carried out for IEEE 30, IEEE57 and IEEE 118 standard test bus system.