Fractal analysis of power grid faults and cross correlation for the faults and meteorological factors

Abstract

Power-grid faults pose a great threat to the economy and to social stability. In this paper, the detrended fluctuation analysis method is used to investigate the scaling properties of power grid faults and the correlation between faults and meteorological factors that are closely related to power grid faults. Multifractal detrended fluctuation analysis showed that the fault time series were multifractal. Further investigations revealed the origins of multifractality in power-grid fault time series, and the results showed that the temporal correlations in the data represent the distribution of the returns, which are a significant source of multifractal scaling. Then, cross correlations between the fault and the four meteorological factors were investigated using the detrended cross-correlation analysis method. The results showed that maximum wind speed has a considerable impact on the number of transmission system line faults per day, whereas daily precipitation, daily mean air temperature, and maximum wind speed have a considerable impact on the number of distribution system line faults per day.