{"title":"Modeling and Simulation of EV Unscheduled Charging and its Impact on Distribution Systems","authors":"I. Anselmo, H. Mahmood","doi":"10.1109/ISGTLatinAmerica52371.2021.9543054","DOIUrl":null,"url":null,"abstract":"The growing deployment of electric vehicles (EVs) in the utility grid raises concerns regarding the current distribution infrastructure's capability to accommodate such a rapidly increasing load demand. This paper presents a methodology for modeling and simulating EV charging demand in residential distribution systems. The modeling approach can be used to study the impact of unscheduled charging and also for energy management studies. Since each driver or a group of drivers has a particular behavior, the daily EV plug-in profile variations are characterized to show the individual driving behavior. This approach is more suitable for energy management studies and charging coordination algorithms. The impact of unscheduled charging is investigated using the IEEE 13- Node Test Feeder with 601 EVs, which represents a 50 % penetration level. Tesla Model 3 EV is used, and the 13- Node Test Feeder is simulated in the MATLAB software. Statistical studies, using a year worth of data, show the significant effect of unscheduled charging on the quality of the distribution system operation. Feeders that are impacted the most in terms of violating the voltage limit and current limits are highlighted, and the violation statistics are presented.","PeriodicalId":120262,"journal":{"name":"2021 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISGTLatinAmerica52371.2021.9543054","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
The growing deployment of electric vehicles (EVs) in the utility grid raises concerns regarding the current distribution infrastructure's capability to accommodate such a rapidly increasing load demand. This paper presents a methodology for modeling and simulating EV charging demand in residential distribution systems. The modeling approach can be used to study the impact of unscheduled charging and also for energy management studies. Since each driver or a group of drivers has a particular behavior, the daily EV plug-in profile variations are characterized to show the individual driving behavior. This approach is more suitable for energy management studies and charging coordination algorithms. The impact of unscheduled charging is investigated using the IEEE 13- Node Test Feeder with 601 EVs, which represents a 50 % penetration level. Tesla Model 3 EV is used, and the 13- Node Test Feeder is simulated in the MATLAB software. Statistical studies, using a year worth of data, show the significant effect of unscheduled charging on the quality of the distribution system operation. Feeders that are impacted the most in terms of violating the voltage limit and current limits are highlighted, and the violation statistics are presented.