电动汽车有序充电研究数据集

电动汽车有序充电研究数据集主要面向计及用户互动潜力的有序充电调度策略研究，通过采集项目参与方北京华商三优新能源科技有限公司在北京市内运营的充电桩的充电订单数据，通过充电设施车网互动平台离线数据和实时数据的计算，采用聚类分析、机器学习和模型建模等方法生成得到，包含充电开始时间、充电结束时间、充电量和充电策略等数据，数据量是280MB

The orderly charging research dataset for electric vehicles is primarily developed for studies on orderly charging scheduling strategies accounting for user interaction potential. It is generated by collecting charging order data from charging piles operated within Beijing by the project participant, Beijing Huashang Sanyou New Energy Technology Co., Ltd., performing calculations on offline and real-time data from the charging facility vehicle-to-grid (V2G) interaction platform, and employing methods such as cluster analysis, machine learning, and model development. The dataset includes data such as charging start time, charging end time, charging quantity, and charging strategy, with a total size of 280 MB.

搜集汇总

背景与挑战

背景概述

该数据集面向电动汽车有序充电调度策略研究，包含北京市内充电桩的充电订单数据，通过聚类分析、机器学习和模型建模等方法生成，数据量303.98MB，涵盖充电时间、电量和策略等信息。