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Transactions: WSEAS TRANSACTIONS ON POWER SYSTEMS
Transactions ID Number: 32-262
Full Name: Geev Mokryani
Position: Lecturer
Age: ON
Sex: Male
Address: Azad University of Soofian
Country: IRAN
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E-mail address: gmokryani@gmail.com
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Title of the Paper: Detection of Ferroresonance Based on Wavelet Transform and Competitive Neural Network
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Number of paper pages: 17
Abstract: Ferroresonance has more damaging effects on transformers and other equipments in distribution networks such as oscillating over voltages and over currents, distortion in voltage and current waveforms, transformer heating, loud noise due to magnetostriction and mal-operation of the protective devices. This paper proposes a novel method for identification of Ferroresonance in distribution networks. Using this method Ferroresonance can be discriminate from other transients such as capacitor switching, load switching, transformer switching. Wavelet transform is used for decomposition of signals and Competitive Neural Network is implemented for Ferroresonance identification. Ferroresonance data and other transients are obtained by simulation of a real 20kV distribution feeder using Electromagnetic Transient Program (EMTP). Using Daubechies mother wavelet signals are decomposed up to six levels. The energy of detail signals that obtained by wavelet transform are used for!
training and trailing Competitive neural network. The results show that the Competitive neural network is effective for discriminating Ferroresonance from other transients.
Keywords: Ferroresonance, EMTP program, Wavelet transform, Competitive neural network
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