Please use this identifier to cite or link to this item: https://dspace.ctu.edu.vn/jspui/handle/123456789/68905
Title: Fault localization on the transmission lines by wavelet technique combined radial basis function neural network
Authors: Nguyen, Nhan Bon
Keywords: Power system fault
Multi-resolution analysis
Radius bias function Neural Network (RBFNN)
Fault location
Power transmission line
Discrete Wavelet transform
Issue Date: 2019
Series/Report no.: Tạp chí Khoa học Giáo dục Kỹ thuật;Số 55 .- Tr.07-11
Abstract: The rapid growth of the electricity system in the of a country's economic development has led to an increase in the number of power transmission lines operating at different voltage levels and the total length of power transmission lines. Thus, Faults on the transmission line are unavoidable. In this paper, Wavelet transforms for the recognition and localization of short circuits faults on the power transmission lines. In that, the voltage waves and current waves on the lines are simulated by Simulink - Matlab. The Wavelet transform is used with the RBF Neural network to find out where the short circuit faults occurred. The proposed method is applied for a power system which is a power transmission lines, one load and one generator. The results are achieved and demonstrated the potential for on-line identification capabilities in Vietnam Power System.
URI: https://dspace.ctu.edu.vn/jspui/handle/123456789/68905
ISSN: 1859-1272
Appears in Collections:Khoa học Giáo dục Kỹ thuật

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