Masaharu Tanaka, H. Eto, Yuji Mizuno, N. Matsui, F. Kurokawa
{"title":"Genetic algorithm based optimization for configuration and operation of emergency generators in medical facility","authors":"Masaharu Tanaka, H. Eto, Yuji Mizuno, N. Matsui, F. Kurokawa","doi":"10.1109/ICRERA.2017.8191194","DOIUrl":null,"url":null,"abstract":"In this paper, the application of genetic algorithm (GA) to energy management of isolated power system is discussed. A method to realize the simultaneous optimization of configuration and operation with emergency generators (EGs) in a hospital is proposed as an example. The simultaneous optimization of configuration and operation needs search of enormous combinations, which is generally considered to be a difficult problem. In the proposal, we show a method to efficiently perform the simultaneous optimization of configuration and operation by dual gene coding. The effectiveness of the proposed method is examined by a case study using actual data in a hospital.","PeriodicalId":6535,"journal":{"name":"2017 IEEE 6th International Conference on Renewable Energy Research and Applications (ICRERA)","volume":"9 1","pages":"919-924"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 6th International Conference on Renewable Energy Research and Applications (ICRERA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRERA.2017.8191194","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
In this paper, the application of genetic algorithm (GA) to energy management of isolated power system is discussed. A method to realize the simultaneous optimization of configuration and operation with emergency generators (EGs) in a hospital is proposed as an example. The simultaneous optimization of configuration and operation needs search of enormous combinations, which is generally considered to be a difficult problem. In the proposal, we show a method to efficiently perform the simultaneous optimization of configuration and operation by dual gene coding. The effectiveness of the proposed method is examined by a case study using actual data in a hospital.