{"title":"Research on The Method for Optimal Location of Charging Stations Based on The Spatial and Temporal Characteristics of Electric Vehicle Charging Demand","authors":"Shumin Chen, Junda Li, Lingfang Li","doi":"10.1109/iSPEC54162.2022.10033066","DOIUrl":null,"url":null,"abstract":"Reasonable and scientific charging stations location planning is the prerequisite for electric vehicles application. There are many factors affecting the location of charging stations. Not only the spatial and temporal characteristics of charging load, but also the cost and interests of each market entity should be considered. Based on the prediction of electric vehicle charging load in the temporal dimension, this paper distributes the charging demand spatially. Then the interests of electric vehicle owners, charging station operators and power grid companies is comprehensively considered in the optimization location model. The optimization location model is established with the objective of minimum cost in the whole society and with the constraint to meet the charging demand. At last, a study case is taken to verify the accuracy of the optimization location model.","PeriodicalId":129707,"journal":{"name":"2022 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Sustainable Power and Energy Conference (iSPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iSPEC54162.2022.10033066","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
Reasonable and scientific charging stations location planning is the prerequisite for electric vehicles application. There are many factors affecting the location of charging stations. Not only the spatial and temporal characteristics of charging load, but also the cost and interests of each market entity should be considered. Based on the prediction of electric vehicle charging load in the temporal dimension, this paper distributes the charging demand spatially. Then the interests of electric vehicle owners, charging station operators and power grid companies is comprehensively considered in the optimization location model. The optimization location model is established with the objective of minimum cost in the whole society and with the constraint to meet the charging demand. At last, a study case is taken to verify the accuracy of the optimization location model.