Wavelet Analysis and Radial Basis Function Neural Network Based Stability Status Prediction Scheme

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Emmanuel Asuming Frimpong
Philip Yaw Okyere
Johnson Asumadu



This paper presents a technique for predicting the transient stability status of a power system. Bus voltages of system generators are used as input parameter. The bus voltages are processed using wavelet transform. Daubechies 8 mother wavelet is employed to extract wavelet entropy of detail 1 coefficients. The sum of wavelet entropies is used as input to a trained radial basis function neural network which predicts the transient stability status. The IEEE 39-bus test system was used to validate the effectiveness and applicability of the technique. The technique is simple to apply and can be implemented in real-time. The prediction accuracy was found to be 86.5% for 200 test cases.


Keywords : Radial basis function, Transient analysis and Wavelet transform


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