Diagnosis of Power Quality Events Based on Detrended Fluctuation Analysis

This paper presents a novel technique to diagnose frequently encountered power quality (PQ) disturbance cases both single and mixed event types. Adopting existing approach to emulate signals containing different types of PQ disturbance events, a specially designed hardware setup has been developed in the laboratory. Captured signals from the developed event generator have been analyzed to extract useful information for diagnosis of various PQ disturbances. In the proposed method, a signal tracker capable of continuously tracking normal level of the signal has been employed to extract actual disturbance within it. A suitably designed detrended fluctuation analysis tool has been effectively used to diagnose the PQ disturbances. Implementation of the proposed technique shows the effectiveness in differentiating PQ events distinctly without much involving conventional analytical tools that result in minimum computational burden as compared to the existing methods. To establish the effectiveness and to get acceptability, the proposed method has been rigorously tested on significant number of captured signals containing different types of PQ disturbances and a satisfactory outcome has been observed.