Wavelet , Kalman Filter and Fuzzy-Expert Combined System for Classifying Power System Disturbances

A new algorithm for power system disturbance classification is proposed in this paper. It is a two-stage system that employs the great potentials of the discrete wavelet transform (DWT), Kalman filter and a fuzzy-expert system. For the first stage, the captured voltage waveform is passed through the DWT to determine the noise inside it. The covariance of this noise is then calculated and fed together with the captured voltage waveform to the Kalman filter to provide the amplitude and the slope of this waveform. These are considered as an input to the fuzzy-expert system in the second stage to determine the class to which the waveform belongs. Simulation and experimental results confirm the aptness and the capability of the proposed system in power system disturbance detection and classification. keywords: Power quality, DWT, Kalman filter, Fuzzy expert system, Power System Disturbance.