Jie Yu, Jianqiang Hu, Cheng Li, Qingjie Zhang, Chuan Liu, Shidong Liu
{"title":"Distributed demand response charging control of multiple plug-in electric vehicle clusters","authors":"Jie Yu, Jianqiang Hu, Cheng Li, Qingjie Zhang, Chuan Liu, Shidong Liu","doi":"10.1049/stg2.12124","DOIUrl":null,"url":null,"abstract":"<p>This paper is devoted to the distributed demand response (DR) charging control of plug-in electric vehicles (PEVs) for frequency regulation in power systems in terms of load following service. Specifically, PEVs are divided into different clusters according to their parking place under different energy management systems. Each EV cluster is modelled by a transport-based load aggregate model with the input being the charging rate, and the output is the aggregate power. Based on the aggregate charging control model, a novel dynamic real-time distributed pinning control algorithm is proposed to coordinate the charging rates such that the aggregate charging power of PEVs can follow a given reference power trajectory. The theoretical analysis shows that if the reference power profile is in the trackable area of all PEVs' charging power and the ramping rate is restrained by a predefined bounded constraint, then the demand response charging tracking control is solvable. Finally, simulation results on an EV system with twelve PEV clusters are presented to show the effectiveness of the proposed demand response control algorithm.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12124","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Smart Grid","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/stg2.12124","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
This paper is devoted to the distributed demand response (DR) charging control of plug-in electric vehicles (PEVs) for frequency regulation in power systems in terms of load following service. Specifically, PEVs are divided into different clusters according to their parking place under different energy management systems. Each EV cluster is modelled by a transport-based load aggregate model with the input being the charging rate, and the output is the aggregate power. Based on the aggregate charging control model, a novel dynamic real-time distributed pinning control algorithm is proposed to coordinate the charging rates such that the aggregate charging power of PEVs can follow a given reference power trajectory. The theoretical analysis shows that if the reference power profile is in the trackable area of all PEVs' charging power and the ramping rate is restrained by a predefined bounded constraint, then the demand response charging tracking control is solvable. Finally, simulation results on an EV system with twelve PEV clusters are presented to show the effectiveness of the proposed demand response control algorithm.