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Smart fault classification in HVDC system based on optimal probabilistic neural networks

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4 Author(s)
M. Khodaparastan ; Amirkabir University of Technology, Electrical Engineering Department, Tehran, Iran ; A. S. Mobarake ; G. B. Gharehpetian ; S. H Fathi

Optimal probabilistic neural network-based method has been porposed in this paper to identify different types of fault in high voltage direct current (HVDC) system. Probabilistic neural network is a type of artificial neural networks capable of approximating the optimal classifier. The particle swarm optimization is porposed to achive an optimal value of smoothing factor for PNN which is an important parameter. The main purpose of this paper is fast and accurate fault classification, for this purpose simple HVDC system has been evaluated under various fault type condition to examine the efficacy of the proposed method. The performance of the proposed method is investigated using MATLAB/Simulink environment.

Published in:

Smart Grids (ICSG), 2012 2nd Iranian Conference on

Date of Conference:

24-25 May 2012