基于KM算法投切事件匹配的负荷辨识方法

负荷投切事件是关联负荷分类、辨识的一个重要依据,为了能够准确的实现非侵入式负荷投切过程的辨识,提出一种基于KM算法投切事件匹配的非侵入式负荷辨识方法。在该方法中,首先采用一种功率曲线拟合逼近的方式进行负荷事件检测,并利用投切稳态特征建立用电设备投入和切除特征的概率分布模型。同时,考虑到负荷投入事件和切除事件数量不对等情况,将负荷事件与数据库负荷进行匹配,并采用加权优化的KM算法寻找最佳解,从而实现负荷投入和切除的正确匹配辨识。最后,在真实的测试场景并结合REDD数据集进行实验,结果表明文中方法能对负荷投切事件进行有效匹配辨识,为实现能耗细分奠定了基础。

A load event matching method for non-intrusive load identification based on KM algorithm

Load turning on and off events are important basis for load classification and identification. In order to accurately identify the process of load switching, a non-intrusive load identification method based on KM matching algorithm is proposed. In this method, firstly, an approximation method fitting the power curve is used to detect load events, and the probability distribution model of load event signatures is established by using the switching steady-state signatures. At the same time, considering that the number of load turning on and off events is not equal, the load events are matched with loads in database, and weighted optimization KM algorithm is used to find the optimal solution, so as to realize the correct matching. Finally, in the test of real scenario and REDD dataset, the results show that the proposed method can effectively match and identify load events, which can be the foundation for subsequent energy consumption subdivision.