{"title":"A two-stage genetic based technique for the unit commitment optimization problem","authors":"A. Eldin, M. El-Sayed, H. Youssef","doi":"10.1109/MEPCON.2008.4562322","DOIUrl":null,"url":null,"abstract":"A genetic based technique is presented for solving the unit commitment optimization problem. The proposed technique consists mainly of two stages. In the first stage, economic dispatch for each interval (hour) of study is executed. Several solutions (individuals) are generated around the previous economic dispatch solution. These individuals are introduced as a part of the initial population of the genetic algorithm which is applied as a second stage to optimally identify the solution of the unit commitment optimization problem. The proposed technique is applied to the 10 unit, and the 26 unit test systems.","PeriodicalId":236620,"journal":{"name":"2008 12th International Middle-East Power System Conference","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 12th International Middle-East Power System Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MEPCON.2008.4562322","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23
Abstract
A genetic based technique is presented for solving the unit commitment optimization problem. The proposed technique consists mainly of two stages. In the first stage, economic dispatch for each interval (hour) of study is executed. Several solutions (individuals) are generated around the previous economic dispatch solution. These individuals are introduced as a part of the initial population of the genetic algorithm which is applied as a second stage to optimally identify the solution of the unit commitment optimization problem. The proposed technique is applied to the 10 unit, and the 26 unit test systems.