WAVELET ANALYSIS AND NEURAL-NETWORK-BASED ADAPTIVE SINGLE-POLE AUTORECLOSURE SCHEME FOR EHV TRANSMISSION-SYSTEMS

This paper proposes a wavelet analysis and neural network based adapti ve single-pole autoreclosure scheme for Extra High Voltage (EHV) trans mission systems. First, the fault transients generated by the secondar y are and permanent faults are analysed using discrete wavelet transfo rm with particular reference to the development of the adaptive autore closure scheme. Daubechies D4 wavelet transform is adopted and the num erical analyses reveal that certain wavelet components can be effectiv ely used as the features to detect and identify the fault relevant cha racteristics in transmission systems. Several results of wavelet analy sis are used as the feature vectors of artificial neural network which is designed to distinguish between transient and permanent faults, an d to determine the secondary are extinction point. The outcome of the study clearly indicates that the wavelet analysis combined with neural network approach can be used as an attractive and effective means of realising an adaptive autoreclosing scheme. (C) 1998 Elsevier Science Ltd. All rights reserved.