Stockwell-transform for electrical defaults localization

Several methods have been proposed for detection and classification of power quality (PQ). A novel algorithm to detect and identify faults power swings is proposed based on S-Transform and Approximate Shannon Energy (SSE) for power quality analysis. This paper investigates the use and the performance of (SSE). Using real and simulated data, two methods are applied: wavelet analysis, and our approach has been evaluated according to the accuracy of detection of the beginning and end of the disturbance in question. For application, six types of disturbance including a voltage sag, swell, interruption, with and without harmonics were investigated. The proposed method (SSE) has better performance for detection frequency intervals of the disturbances.