Power quality analysis using modified S-transform on ARM processor

Abstract

The extensive usage of non-linear loads and electronic devices has resulted in increased vulnerability to the power quality (PQ) disturbances in the power system. Hence, the analysis of PQ disturbances becomes crucial to maintain the reliability of the distributed generation (DG). This paper presents the analysis of various disturbances like voltage swell, voltage sag, notch, flicker, spike, harmonics, momentary interruption and oscillatory transients by using a signal processing technique i.e. modified Stockwell transform (MST). The technique is employed to provide sufficient time-frequency characteristics and retain the phase information of input to detect the different PQ disturbances. Moreover, the localization of Gaussian window is exploited by providing different scaling parameters which correspond to the linear phase of frequency and provides better resolution. The voltage signal is utilized for the detection of the disturbances at a point of common coupling. The time-frequency features are re-transformed into the time space (original signal) by using the inverse modified S-transform to visualize the different PQ disturbances in real-time. In this study, the methodology is implemented on commercially available ARM (Advanced RISC Machine) processor due to its features such low cost and low power consumption for real-time power quality analysis.