Title :
Identification of ferroresonance based on wavelet transform and artificial neural networks
Author :
Mokryani, G. ; Haghifam, M.-R. ; Esmaeilpoor, J.
Author_Institution :
Islamic Azad Univ., Ilkhchi
Abstract :
A novel method for Ferroresonance detection is presented in this paper. Using this method Ferroresonance can he discriminate from other transients such as capacitor switching, load switching, transformer switching. Wavelet transform is used for decomposition of signals and competitive neural network used for classification. Ferroresonance data and other transients are obtained by simulation using EMTP program. Results show that the proposed procedure is efficient in identifying Ferroresonance from other events.
Keywords :
EMTP; distribution networks; neural nets; wavelet transforms; EMTP program; artificial neural network; capacitor switching; electric power distrihution system; ferroresonance Identification; ferroresonance detection; load switching; transformer switching; wavelet transform; Artificial neural networks; Capacitance; Capacitors; Ferroresonance; Frequency; Inductance; Neural networks; Power system transients; Voltage control; Wavelet transforms; Competitive Neural Network; EMTP program; Ferroresonance; Wavelet transform;
Conference_Titel :
Power Engineering Conference, 2007. AUPEC 2007. Australasian Universities
Conference_Location :
Perth, WA
Print_ISBN :
978-0-646-49488-3
Electronic_ISBN :
978-0-646-49499-1
DOI :
10.1109/AUPEC.2007.4548122
