{"title":"A stochastic optimization approach to aggregated electric vehicles charging in smart grids","authors":"Ziming Zhu, S. Lambotharan, W. Chin, Z. Fan","doi":"10.1109/ISGT-ASIA.2014.6873763","DOIUrl":null,"url":null,"abstract":"Electric vehicles (EVs) are considered to be an important component of distributed energy storage and supply devices in smart grids. EVs can serve as a distributed mobile energy resource in the electricity market. They can be used to store and transport energy from one geographical area to another as supportive energy supply. EVs should be included in future electricity demand management and consumption optimization system. This paper presents a dynamic optimization framework to formulate the optimal charging problem. The framework considers an aggregated charging station where a large number of EVs can be charged simultaneously during permitted time. The optimization will provide every individual EV an optimal charging strategy to proactively control their charging rates in order to minimise the charging costs. The optimization is based on stochastic optimal control methods. Numerical results are presented to demonstrate the proposed framework.","PeriodicalId":444960,"journal":{"name":"2014 IEEE Innovative Smart Grid Technologies - Asia (ISGT ASIA)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Innovative Smart Grid Technologies - Asia (ISGT ASIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISGT-ASIA.2014.6873763","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
Electric vehicles (EVs) are considered to be an important component of distributed energy storage and supply devices in smart grids. EVs can serve as a distributed mobile energy resource in the electricity market. They can be used to store and transport energy from one geographical area to another as supportive energy supply. EVs should be included in future electricity demand management and consumption optimization system. This paper presents a dynamic optimization framework to formulate the optimal charging problem. The framework considers an aggregated charging station where a large number of EVs can be charged simultaneously during permitted time. The optimization will provide every individual EV an optimal charging strategy to proactively control their charging rates in order to minimise the charging costs. The optimization is based on stochastic optimal control methods. Numerical results are presented to demonstrate the proposed framework.