A Time Sequence Data Processing Method Based on Random Matrix of Smart Electric Meter

With the expansion of the scale of intelligent power distribution network and the complexity of power grid structure, the amount of data in power system increases rapidly, and the power equipment are faced with new challenges. Based on the principle of big data and data mining analysis, this paper proposes a method based on random matrix theory and clustering algorithm to evaluate the running state of electric energy meter. Specifically, time series data of various indicators is characterized by real-time separation window technology. Based on the random matrix theory, the random matrix based analysis model is constructed to calculate and analyze the statistical timing characteristics in real time. The proposed method has good robustness, reliability and timeliness, which provides a new idea for the application research of power grid detection technology.