{"title":"Planning of electric vehicle charging infrastructure","authors":"C. H. Dharmakeerthi, N. Mithulananthan, T. Saha","doi":"10.1109/PESMG.2013.6672085","DOIUrl":null,"url":null,"abstract":"The Electric Vehicle (EV) has become the sustainable alternative to fossil fuel driven automobiles. As a result, a new type of load is being seen on power systems. Hence, provision of an EV charging infrastructure has become a new challenge for power system engineers worldwide. It has been identified that the voltage dependent nature of EV load may lead to voltage instabilities in the system. Furthermore, significant load integration into the distribution system may overload the system components, increase power system losses and may violate system constraints. Despite these factors EV consumers should be provided with convenient and reliable charging facilities. Hence, the identification of a charging infrastructure which satisfies requirements of both the EV customer and the power system is of primary importance. A particle swarm optimization (PSO) based approach is considered here for planning of EV charging infrastructure.","PeriodicalId":433870,"journal":{"name":"2013 IEEE Power & Energy Society General Meeting","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Power & Energy Society General Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PESMG.2013.6672085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
Abstract
The Electric Vehicle (EV) has become the sustainable alternative to fossil fuel driven automobiles. As a result, a new type of load is being seen on power systems. Hence, provision of an EV charging infrastructure has become a new challenge for power system engineers worldwide. It has been identified that the voltage dependent nature of EV load may lead to voltage instabilities in the system. Furthermore, significant load integration into the distribution system may overload the system components, increase power system losses and may violate system constraints. Despite these factors EV consumers should be provided with convenient and reliable charging facilities. Hence, the identification of a charging infrastructure which satisfies requirements of both the EV customer and the power system is of primary importance. A particle swarm optimization (PSO) based approach is considered here for planning of EV charging infrastructure.