Power System Fault Signal Analysis Based on Permutation Entropy Algorithm

Rapid and accurate diagnosis of fault has a crucial role for speeding up the recovery process and ensuring the safe operation of the power system. This paper analyzes the data sources currently used in power system fault diagnosis, proposes the use of wide-area information for rapid diagnosis of power systems. First, wavelet transform is used to process the wide area measurement data, through correlation coefficient method to eliminate the noise and reconstruct the signal, then permutation entropy calculation use the of the reconstructed signal. Since the complexity of the arrangement of entropy reflects a one-dimensional time series, the signal changes with high sensitivity, therefore, it can be applied to power system fault diagnosis. Compared with the traditional wavelet analysis method, this method avoids the problem of selecting wavelet base and meets the conditions for online fault diagnosis. In addition, it is simple and easy to program. The approach is applied in IEEE10 machine 39-bus system fault diagnosis. The diagnostic results show the applicability and effectiveness of the method.