智能电网下基于负荷识别的居民电动汽车需求响应特性建模方法研究

当前智能电网技术的发展对系统负荷响应特性的建模工作提出了更高的要求,特别是大规模电动汽车并网后针对居民充电行为的需求响应特性应该得到进一步研究。基于非侵入式负荷监测技术,本文分析了电动汽车实际充电功率特点,提出一种在居民家庭日负荷曲线中识别充电负荷的方法,并将此识别结果作为需求侧响应特性建模的数据基础;针对充电负荷与环境温度、日类型的相关性,本研究将相似日短期负荷预测算法引入到负荷转移率计算过程中,减小因日负荷波动带来的计算误差,并采用优化算法进行参数辨识,进而建立更为准确的分时电价下电动汽车充电负荷响应特性模型。最后仿真验证了该建模方法的有效性和优越性。

Research on Modeling Method of Demand Response Characteristics of Residential EV Based on Load Identification in Smart Grid

The development of smart grid technology has put forward higher requirements for the modeling work of load response, and model of the residents' charging demand response should be further study especially after the large-scale electric vehicles connected to power grid. Based on non-intrusive residential load monitoring technology and the characteristic analyzing of actual electric vehicles charging power, a charging load identification method decomposed from the daily load curve is presented, and the identify results are taken as the basis data for modeling of demand response. Because of the characteristic that charging power load is associated with the ambient temperature and daily type, the similar day short-term load forecasting algorithm is introduced into the calculation progress of the load transfer rate to enhance the calculation accuracy in this paper. In addition, the optimization algorithm is used to identify the parameters, and a more accurate charging load response model of electric vehicles under the TOU price is established. Finally, the simulation results verify the validity and superiority of the method.