M. Brenna, A. Dolara, S. Leva, M. Longo, D. Zaninelli
{"title":"Optimal playing of electric vehicle charging stations","authors":"M. Brenna, A. Dolara, S. Leva, M. Longo, D. Zaninelli","doi":"10.1109/ICRERA.2017.8191268","DOIUrl":null,"url":null,"abstract":"In the face of energy crisis and environmental pollution problems, all the countries in the world vigorously promote the development of electric vehicles. Electric vehicle charging infrastructure is the necessary infrastructure to the development of electric vehicles. This work has been focused on Electric Vehicles' Charging Stations (CSs) deployment. It has been considered in this study several constraints (opening cost, distance between charging stations and clients, the, etc.). It has been proposed a mathematical formulation of the problem. Then, it has been solved it using an optimized genetic algorithm with an objective of calculating the necessary number of charging stations and the best position to locate them in order to satisfy the demand. Different situations are considered. The algorithm will be applied to the city of Milan as a case study.","PeriodicalId":6535,"journal":{"name":"2017 IEEE 6th International Conference on Renewable Energy Research and Applications (ICRERA)","volume":"180 1","pages":"210-215"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 6th International Conference on Renewable Energy Research and Applications (ICRERA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRERA.2017.8191268","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In the face of energy crisis and environmental pollution problems, all the countries in the world vigorously promote the development of electric vehicles. Electric vehicle charging infrastructure is the necessary infrastructure to the development of electric vehicles. This work has been focused on Electric Vehicles' Charging Stations (CSs) deployment. It has been considered in this study several constraints (opening cost, distance between charging stations and clients, the, etc.). It has been proposed a mathematical formulation of the problem. Then, it has been solved it using an optimized genetic algorithm with an objective of calculating the necessary number of charging stations and the best position to locate them in order to satisfy the demand. Different situations are considered. The algorithm will be applied to the city of Milan as a case study.