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《Proceedings of the Csee》 2002-02
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BI Tian shu 1, NI Yi xin 1, WU Fu li 1, YANG Qi xun 2 (1.Dept. of Electrical & Electronic Engineering,The University of Hong Kong,Hong Kong, China; 2.Dept.of Electrical Engineering,North China Electric Power University,Beijing 100085, China)  
Fault section estimation is of great importance to the restoration of power systems. In this paper, the application of Radial Basis Function Neural Network (RBF NN) to fault section estimation is addressed. The orthogonal least square algorithm has been extended to optimize the parameters of RBF NN. A classical Back Propagation Neural Network (BP NN) has been developed to solve the same problem for comparison. Computer test is conducted on a 4 bus test system and the test results show that the RBF NN is quite effective and superior to BP NN in fault section estimation.
【CateGory Index】: TM711;TP183
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