{"title":"Regional autonomy control of EV charging with PV/ES systems in active distribution network","authors":"Chen Zhang, Guiping Zhu","doi":"10.1109/APPEEC.2015.7381031","DOIUrl":null,"url":null,"abstract":"A regional autonomy control (RAC) strategy is proposed in this paper in order to solve the integration problem of massive electric vehicle (EV) clusters into future city power grids from a high vision of active distribution network (ADN), minimize the negative impacts on the existing grid, and improve the load profile. The strategy mainly consists of two parts: the power allocation algorithm that dynamically allocates the available capacity for charging to each EV charger according to EV urgency level, and the adjustment mechanism that estimates the available capacity considering the regional differences of daily load characteristics and EV charging behaviors. By implementing the proposed strategy, regional EV charging load can be regulated to alleviate the overloads for the corresponding district and ensure the charging satisfaction as well. Models of business district and residential district were simulated and the obtained results have shown the effectiveness of the strategy.","PeriodicalId":439089,"journal":{"name":"2015 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APPEEC.2015.7381031","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
A regional autonomy control (RAC) strategy is proposed in this paper in order to solve the integration problem of massive electric vehicle (EV) clusters into future city power grids from a high vision of active distribution network (ADN), minimize the negative impacts on the existing grid, and improve the load profile. The strategy mainly consists of two parts: the power allocation algorithm that dynamically allocates the available capacity for charging to each EV charger according to EV urgency level, and the adjustment mechanism that estimates the available capacity considering the regional differences of daily load characteristics and EV charging behaviors. By implementing the proposed strategy, regional EV charging load can be regulated to alleviate the overloads for the corresponding district and ensure the charging satisfaction as well. Models of business district and residential district were simulated and the obtained results have shown the effectiveness of the strategy.