{"title":"Optimization of EV bus charging schedule by stochastic programming","authors":"Tetsuya Sato, T. Shiina, Ryunosuke Hamada","doi":"10.1109/IIAIAAI55812.2022.00124","DOIUrl":null,"url":null,"abstract":"In recent years, introducing electric vehicle (EV) buses, their charging equipment and infrastructures has become an urgent issue. The purpose of this study is to propose a scheduling model that minimizes the total charging time of EV buses as a makespan using multiple EV buses and chargers, considering fluctuations in the charging time of each EV bus. Generally, directly solving a problem with probabilistic constraints is difficult, thus it often convert into a deterministic equivalent of stochastic program. Therefore, first, this study solved the relaxed problem of deterministic equivalent and assigned each EV bus to each charger using branch and bound (BB) method. Then, it introduced the probabilistic constraints for calculating the exact value of the makespan. The results of numerical experiments demonstrated the effectiveness of this solution.","PeriodicalId":156230,"journal":{"name":"2022 12th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 12th International Congress on Advanced Applied Informatics (IIAI-AAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIAIAAI55812.2022.00124","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
In recent years, introducing electric vehicle (EV) buses, their charging equipment and infrastructures has become an urgent issue. The purpose of this study is to propose a scheduling model that minimizes the total charging time of EV buses as a makespan using multiple EV buses and chargers, considering fluctuations in the charging time of each EV bus. Generally, directly solving a problem with probabilistic constraints is difficult, thus it often convert into a deterministic equivalent of stochastic program. Therefore, first, this study solved the relaxed problem of deterministic equivalent and assigned each EV bus to each charger using branch and bound (BB) method. Then, it introduced the probabilistic constraints for calculating the exact value of the makespan. The results of numerical experiments demonstrated the effectiveness of this solution.