新能源汽车大数据在充电供需研究中的应用

Application of big data of new energy vehicles in the research of charging supply and demand

为提高自营充电场站的运营效率,基于新能源汽车大数据,围绕充电供需研究体系和实际运营问题,开展了标杆充电场站识别、充电桩与车辆的匹配性故障识别、区域充电需求识别、用户充电偏好识别和重点目标用户识别等应用。研究结果表明,通过车端充电数据与充电场站边界关联,可精准反映区域内充电资源供给,识别标杆充电场站。在充电供给质量方面,通过识别车端充电异常数据,反映车桩匹配潜在问题,可为充电运营决策提供参考。

In order to improve the operation efficiency of self operated charging stations,based on the big data of new energy vehicles,the application practice of data enabled charging station operation is carried out around the research system of charging supply and demand and the actual operation problems.In practice,we carried out such applications as benchmark charging station identification,matching fault identification between charging pile and vehicle,regional charging demand identification,user charging preference identification and key target user identification.The research results show that the correlation between the charging data at the vehicle end and the boundary of the charging station can accurately reflect the supply of charging resources in the region and identify the benchmark charging station.In terms of charging supply quality,by identifying abnormal charging data at the vehicle end,the potential problems of vehicle-pile matching are reflected,which can provide reference for ccharging operation decisionmaking.