Mingshen Wang, Xiaodong Yuan, Wenfei Yi, Lei Gao, Zheng Zhang, Li-Na Cui
{"title":"An Electric Vehicle Cluster Model Considering Multiple Uncertainties and Response Costs","authors":"Mingshen Wang, Xiaodong Yuan, Wenfei Yi, Lei Gao, Zheng Zhang, Li-Na Cui","doi":"10.1109/CIEEC54735.2022.9846634","DOIUrl":null,"url":null,"abstract":"The large-scale integration of electric vehicles (EVs) brings challenges to the power grid. Due to the response potential of the EVs for up and down regulation, the EV cluster provides considerable response capacity to the power grid. Existing evaluation methods for the response capacity of EV cluster failed to comprehensively consider the diverse requirements of users, and ignored the impact of battery loss and incentive compensation on users. To solve above problems, the existing cluster modeling methods are improved, including considering user requirements and battery loss factors. Firstly, the diverse requirements of EV users that affect the uncertainty of EV are analyzed. A model for the uncertainty of the single EV’s operation area after grid integration is proposed, and the short-term and long-term scale response capacities of single EV are analyzed. Then, the influence of discharge rate, discharge depth and initial SOC value on battery loss is analyzed. A refined battery loss model was established. Then, the response of EV users under the influence of time-of-use price and incentive compensation price is analyzed. A response cost model is built, and propose an EV cluster response capacity evaluation method. Finally, study results validate the effectiveness of the proposed modeling method for EV cluster.","PeriodicalId":416229,"journal":{"name":"2022 IEEE 5th International Electrical and Energy Conference (CIEEC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 5th International Electrical and Energy Conference (CIEEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIEEC54735.2022.9846634","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
The large-scale integration of electric vehicles (EVs) brings challenges to the power grid. Due to the response potential of the EVs for up and down regulation, the EV cluster provides considerable response capacity to the power grid. Existing evaluation methods for the response capacity of EV cluster failed to comprehensively consider the diverse requirements of users, and ignored the impact of battery loss and incentive compensation on users. To solve above problems, the existing cluster modeling methods are improved, including considering user requirements and battery loss factors. Firstly, the diverse requirements of EV users that affect the uncertainty of EV are analyzed. A model for the uncertainty of the single EV’s operation area after grid integration is proposed, and the short-term and long-term scale response capacities of single EV are analyzed. Then, the influence of discharge rate, discharge depth and initial SOC value on battery loss is analyzed. A refined battery loss model was established. Then, the response of EV users under the influence of time-of-use price and incentive compensation price is analyzed. A response cost model is built, and propose an EV cluster response capacity evaluation method. Finally, study results validate the effectiveness of the proposed modeling method for EV cluster.