国产欧美精品一区二区,中文字幕专区在线亚洲,国产精品美女网站在线观看,艾秋果冻传媒2021精品,在线免费一区二区,久久久久久青草大香综合精品,日韩美aaa特级毛片,欧美成人精品午夜免费影视

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.