针对智慧园区充电设施少不能满足电动汽车发展需求问题, 提出一种适用于智慧园区电动汽车有序共享充电需求建模分析方法, 通过分析充电数据提供充电计划, 并辅助园区能量管理系统制定有序充电策略. 利用功率谱密度估计方法统计分析单个EV充电电流, 并通过人工智能网络完成EV在线识别分类工作, 基于插入时间、能量和工作日之间的相关性统计分析每个EV充电习惯, 利用测量电网侧的电流来预测充电需求, 基于核密度估计建立充电需求统计模型. 通过某住宅小区充电设施采集的实际数据验证该模型精度的有效性和适用性, 为智能园区电动汽车充电提供帮助.
In view of the problem that charging facilities in intelligent park cannot meet the development demand of electric vehicles, a modeling and analysis method suitable for orderly shared charging demand of electric vehicles in intelligent park is proposed. Charging plans are provided by analyzing charging data, and orderly charging strategies are formulated in the energy management system of the park. Power spectral density estimation method using statistical analysis of single EV charging current, and complete EV on-line identification in artificial intelligence network classification work, based on the correlation between insertion time, energy, and working day statistical analysis each EV charging habits, the grid side current is measured using to predict the charging demand, based on kernel density estimate charging demand statistics model is set up. The validity and applicability of the model are verified by the actual data collected from a charging facility in a residential area, which can provide help for EV charging in the intelligent park.