{"title":"最小代价机组承诺问题的改进遗传算法","authors":"S. Jalilzadeh, Y. Pirhayati","doi":"10.1109/ICICISYS.2009.5357777","DOIUrl":null,"url":null,"abstract":"In this paper an Improved Genetic Algorithm (IGA) for unit commitment problem with lowest cost is presented. The unit commitment problem (UCP) has an important role in power systems, due to improvement of commitment schedules results in the reduction of operating costs. However, the unit commitment problem is one of the most difficult optimization problems in power systems, because this problem has many constraints. Moreover, search space is vast. To overcome these problems, a genetic operator based on unit characteristic classification technique are proposed. From simulation results, better solutions are obtained in comparison with previously reported results.","PeriodicalId":206575,"journal":{"name":"2009 IEEE International Conference on Intelligent Computing and Intelligent Systems","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"An Improved Genetic Algorithm for unit commitment problem with lowest cost\",\"authors\":\"S. Jalilzadeh, Y. Pirhayati\",\"doi\":\"10.1109/ICICISYS.2009.5357777\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper an Improved Genetic Algorithm (IGA) for unit commitment problem with lowest cost is presented. The unit commitment problem (UCP) has an important role in power systems, due to improvement of commitment schedules results in the reduction of operating costs. However, the unit commitment problem is one of the most difficult optimization problems in power systems, because this problem has many constraints. Moreover, search space is vast. To overcome these problems, a genetic operator based on unit characteristic classification technique are proposed. From simulation results, better solutions are obtained in comparison with previously reported results.\",\"PeriodicalId\":206575,\"journal\":{\"name\":\"2009 IEEE International Conference on Intelligent Computing and Intelligent Systems\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Conference on Intelligent Computing and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICISYS.2009.5357777\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Intelligent Computing and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICISYS.2009.5357777","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Improved Genetic Algorithm for unit commitment problem with lowest cost
In this paper an Improved Genetic Algorithm (IGA) for unit commitment problem with lowest cost is presented. The unit commitment problem (UCP) has an important role in power systems, due to improvement of commitment schedules results in the reduction of operating costs. However, the unit commitment problem is one of the most difficult optimization problems in power systems, because this problem has many constraints. Moreover, search space is vast. To overcome these problems, a genetic operator based on unit characteristic classification technique are proposed. From simulation results, better solutions are obtained in comparison with previously reported results.