摘要
随着电动汽车的不断普及,如何准确获取电动汽车的充电行为并对电动汽车进行针对性管理与调控,成为电网管理人员关注的问题。本文提出多源数据驱动的电动汽车用户识别方法,基于家庭用电数据和电动汽车充电桩数据挖掘家庭用电行为与电动汽车出行规律,以及电动汽车与家庭用户特性的关联程度,建立适用于特定数据场景下的电动汽车用户关联识别匹配参数,从而识别家庭用户与电动汽车之间的关联性并确定电动汽车的最佳归属。最后,通过算例验证了本文方法的有效性。
With the increasing popularity of electric vehicles(EVs),how to accurately obtain the information about the charging behaviors of EVs and thus effectively manage and regulate them has become a concern for power grid manag⁃ers.In this paper,a multi-source data-driven based EV user identification method is proposed.Based on the household electricity consumption data and EV charging pile data,the electricity consumption behaviors of household and EV traf⁃fic rules are mined.Then,based on the correlations between EVs and household user characteristics,the correlation matching parameters suitable for specific data scenarios are established,thereby identifying the correlations between household users and EVs and determining the best ownership of EVs.Finally,the results of a case study validate the ef⁃fectiveness of the proposed method.
作者
刘艳丽
王俊毅
LIU Yanli;WANG Junyi(Key Laboratory of Smart Grid of Ministry of Education,Tianjin University,Tianjin 300072,China)
出处
《电力系统及其自动化学报》
CSCD
北大核心
2023年第6期141-147,共7页
Proceedings of the CSU-EPSA
关键词
电动汽车
用户识别
数据分析
关联匹配
electric vehicle(EV)
user identification
data analysis
correlation matching
