{"title":"Development of a Genetic Algorithm based electric vehicle charging coordination on distribution networks","authors":"Yen-Chih Yeh, M. Tsai","doi":"10.1109/CEC.2015.7256903","DOIUrl":null,"url":null,"abstract":"In recent years, the development of electric vehicles has gained a lot progress. Many infrastructures are being installed for the electrical vehicles. However, due to the limited power availability, not every electric vehicle can be charged simultaneously in parking lots. This paper proposed a simulation environment which is a Genetic Algorithm based charging control system that can achieve more efficient charging schedule, and take the power constraints into consideration as well. The results of three simulated scenarios are presented. The simulations show that the proposed Genetic Algorithm based charging control system can efficiently maximize the profit or minimize the charging time according to the objectives of different parking lots.","PeriodicalId":403666,"journal":{"name":"2015 IEEE Congress on Evolutionary Computation (CEC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Congress on Evolutionary Computation (CEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEC.2015.7256903","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
In recent years, the development of electric vehicles has gained a lot progress. Many infrastructures are being installed for the electrical vehicles. However, due to the limited power availability, not every electric vehicle can be charged simultaneously in parking lots. This paper proposed a simulation environment which is a Genetic Algorithm based charging control system that can achieve more efficient charging schedule, and take the power constraints into consideration as well. The results of three simulated scenarios are presented. The simulations show that the proposed Genetic Algorithm based charging control system can efficiently maximize the profit or minimize the charging time according to the objectives of different parking lots.