Application of genetic algorithm for problem of optimizing location and capacity of distributed generation considering distributed network reconfiguration
Linh Nguyen, T. T. Nguyen, Trieu Ngoc Ton, A. Truong, X. Nguyen
{"title":"Application of genetic algorithm for problem of optimizing location and capacity of distributed generation considering distributed network reconfiguration","authors":"Linh Nguyen, T. T. Nguyen, Trieu Ngoc Ton, A. Truong, X. Nguyen","doi":"10.32508/STDJ.V20IK7.1205","DOIUrl":null,"url":null,"abstract":"This paper presents a method of determining the location and size of distributed generation (DG) considering to operate the configuration of distribution network to minimize the real power loss. The proposed method which is based on the genetic algorithm (GA) is divided into two stages. In the first stage, GA is used to optimize the location and size of DG in the mesh distribution network, while in the second stage, GA is used to determine the radial network configuration after installing DG. The simulation results on the 33-nodes and 69-nodes systems show that the proposed method can be an efficient method for the placing DG problem and that is considering to solve the problem of distribution network reconfiguration.","PeriodicalId":285953,"journal":{"name":"Science and Technology Development Journal","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science and Technology Development Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32508/STDJ.V20IK7.1205","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents a method of determining the location and size of distributed generation (DG) considering to operate the configuration of distribution network to minimize the real power loss. The proposed method which is based on the genetic algorithm (GA) is divided into two stages. In the first stage, GA is used to optimize the location and size of DG in the mesh distribution network, while in the second stage, GA is used to determine the radial network configuration after installing DG. The simulation results on the 33-nodes and 69-nodes systems show that the proposed method can be an efficient method for the placing DG problem and that is considering to solve the problem of distribution network reconfiguration.