This paper presents a method for power swing and fault diagnosis of power system based on Wavelet Packet Transform(WPT) and Support Vector Machine (SVM) classifier. The method adopts Least Square Support Vector Machine (LS-SVM) classifier to identify the power swing and fault types. The power swing blocking elements are based on monitoring the rate of change of wavelet packet energy and wavelet packet entropy of voltage and current signal, the positive current and zero sequence component. The process of training the LS-SVM using a K-folded cross validation process for determining the values of parameter σ and parameter γ in RBF kernel parameters can minimize the classification error. The proposed method can successfully detect power swing and provide power swing blocking signal for accurate distance protection.

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