{"title":"基于QPSO算法的配电网分布式发电最优选址","authors":"B. Hussain, A. Amin, A. Mahmood, M. Usman","doi":"10.1109/ICEET48479.2020.9048230","DOIUrl":null,"url":null,"abstract":"Environmental concerns, technology improvement and deregulation of electricity markets have encouraged the use of Distributed Generation (DG) sources. An optimal site selection for DG placement can improve distribution system efficiency by minimizing network losses and improving system voltage. Finding an optimal place of DG for a distribution network is a complex optimization issue. In this paper, we have demonstrated the modified version of Particle Swarm Optimization (PSO) called Quantum Behaved PSO (QPSO) algorithm to determine optimal location of DG units for power loss minimization. A standard IEEE 33 and 69-node distribution network are used to validate the effectiveness of the demonstrated method. The simulation results are matched with the literature and it is established that the QPSO has better ability to minimize network losses and improve system voltage by finding more precise location for DG installation.","PeriodicalId":144846,"journal":{"name":"2020 International Conference on Engineering and Emerging Technologies (ICEET)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Optimal Site Selection for Distributed Generation in the Distribution Network by QPSO Algorithm\",\"authors\":\"B. Hussain, A. Amin, A. Mahmood, M. Usman\",\"doi\":\"10.1109/ICEET48479.2020.9048230\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Environmental concerns, technology improvement and deregulation of electricity markets have encouraged the use of Distributed Generation (DG) sources. An optimal site selection for DG placement can improve distribution system efficiency by minimizing network losses and improving system voltage. Finding an optimal place of DG for a distribution network is a complex optimization issue. In this paper, we have demonstrated the modified version of Particle Swarm Optimization (PSO) called Quantum Behaved PSO (QPSO) algorithm to determine optimal location of DG units for power loss minimization. A standard IEEE 33 and 69-node distribution network are used to validate the effectiveness of the demonstrated method. The simulation results are matched with the literature and it is established that the QPSO has better ability to minimize network losses and improve system voltage by finding more precise location for DG installation.\",\"PeriodicalId\":144846,\"journal\":{\"name\":\"2020 International Conference on Engineering and Emerging Technologies (ICEET)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Engineering and Emerging Technologies (ICEET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEET48479.2020.9048230\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Engineering and Emerging Technologies (ICEET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEET48479.2020.9048230","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Optimal Site Selection for Distributed Generation in the Distribution Network by QPSO Algorithm
Environmental concerns, technology improvement and deregulation of electricity markets have encouraged the use of Distributed Generation (DG) sources. An optimal site selection for DG placement can improve distribution system efficiency by minimizing network losses and improving system voltage. Finding an optimal place of DG for a distribution network is a complex optimization issue. In this paper, we have demonstrated the modified version of Particle Swarm Optimization (PSO) called Quantum Behaved PSO (QPSO) algorithm to determine optimal location of DG units for power loss minimization. A standard IEEE 33 and 69-node distribution network are used to validate the effectiveness of the demonstrated method. The simulation results are matched with the literature and it is established that the QPSO has better ability to minimize network losses and improve system voltage by finding more precise location for DG installation.