An Electricity-theft checking method based on time-frequency correlation analysis of power big data

Abstract:
Electricity theft not only affects the operating costs of power supply companies, but also causes serious harm to the safe operation and smooth transmission of the power grid. In the current trend of the big data era, the high-frequency power consumption data collected by each station is used to analyze the line loss. This method of checking electricity stealing improves the efficiency of traditional checking, but it usually focuses on the time series analysis, the frequency domain relationship between historical data is ignored. In this paper, an electricity-theft checking method based on time-frequency correlation analysis of power big data is proposed. Through analyzing the characteristic of time domain and frequency domain of power big data, the detection of suspected electricity-stealing performance are done. The calculation example shows that the time-frequency correlation analysis can effectively identify the electricity stealing users and the two methods are consistent.