An application of the spectral kurtosis to characterize power quality events

This paper deals with a novel application of the Spectral Kurtosis (SK) in power-quality modeling and analysis. The two major advantages of this three-spectral analysis are: robustness to noise and the capability to detect nonlinearities, as impulsive-like signals. The first aim is to study some of the theoretical aspects of the SK estimation, performing a connection to the power-quality event analysis. Then, real-life situations’ performances are presented to correlate results with synthetics. Despite the fact the limited resolution in the frequency domain (to gain computation speed), the method presents an accuracy of 84% over real-life registers.

► Higher-order estatistics in the frequency-domain to analyze Power Quality (PQ). ► The spectral kurtosis has been used to extract features associated to PQ events. ► The performance of the estimator has been evaluated over real-life PQ events, obtaining an accuracy of 84%. ► High processing speed in the frequency domain via an unbiased estimator.