Hybrid S-transform and Kalman filtering approach for detection and measurement of short duration disturbances in power networks

This paper presents a new approach in the detection, localization, and classification of short duration disturbances in the power networks using a phase-corrected wavelet transform known as S-transform (ST) and an extended Kalman filter (EKF). The ST has excellent time-frequency resolution characteristics and provides detection, localization, and visual patterns suitable for automatic recognition of power quality events. The EKF, on the other hand, provides automatic classification and measurements of the frequently occurring power frequency short duration disturbances on the power networks. Thus, by combining both the ST and EKF, it is possible to completely classify and measure the short duration power quality disturbances. The proposed technique is applied to both simulated and experimentally obtained short duration power network disturbances in the presence of additive noise, and the results reveal significant accuracy in completely characterizing the power quality events.