改进最小二乘变点识别法在负荷分解的应用

Application of Improved Least Squares Changepoint Recognition Method in Load Disaggregation

摘要:

随着全世界正进行的大规模智能电表的推广安装,使用非侵入式负荷监测分解方法,总电能消耗分解为单独设备的消耗,成为最近的研究热点。而变点识别是负荷分解方法中的第一步。精确的变点检测为后续提取特征以及识别负荷,打下了坚实的基础。提出了一种基于均值变点模型的识别算法,通过滑动窗口,利用最小二乘法计算目标函数,以确定变点个数。最后,提出假设检验,来验证变点检测的准确性。它能根据相关信号准确检测到负荷投切等引起的电气量变化、发生时刻等重要信息,并记录下来,然后为后续的负荷识别和分解提供保障。最后以某商业写字楼为例,通过测量该商业部分用电负荷数据,从而验证了该算法的可行性。

Abstract:

With the promotion and installation of large-scale smart meters in the world, the use of Non-Intrusive Load Monitoring (NILM) to decompose the total power consumption into the consumption of individual devices has become a new research hotspot. Changepoint recognition is the first step in the NILM method. Accurate change point detection lays a solid foundation for subsequent extraction of features and identification of loads. In this paper, a recognition algorithm based on mean change point model is proposed. By using the sliding window, the objective function is calculated by least squares method to determine the number of change points. Finally, a hypothesis test is proposed to verify the accuracy of the changepoint detection. It can accurately detect important changes such as electrical quantity changes and occurrence times caused by load switching according to relevant signals, and record them, and then provide protection for subsequent load identification and decomposition. At the end of this paper, a commercial office building is taken as an example to verify the feasibility of the algorithm by measuring the electrical load data of the commercial part.