Title :
Neural networks based algorithm for detecting high impedance faults on power distribution lines
Author :
Al-Dabbagh, M. ; Al-Dabbagh, L.
Author_Institution :
Dept. of Electr. & Commun. Eng., Papua New Guinea Univ. of Technol., Papua New Guinea
Abstract :
This paper investigates a new technique for accurate high impedance fault detection on power distribution lines using artificial neural networks (ANN). The need for ANN techniques in such applications is described and the implementation for power distribution lines is described. The backpropagation learning algorithm is used for adjusting the weights in a multilayer neural network to minimize the prediction error with respect to the connection weights in the network. The paper shows the ability of the new protection scheme to identify high impedance faults for improved protection discrimination
Keywords :
backpropagation; fault location; minimisation; multilayer perceptrons; power distribution faults; power distribution lines; power distribution protection; power engineering computing; ANN; artificial neural networks; backpropagation learning algorithm; high impedance fault detection; multilayer neural network; neural network based algorithm; power distribution lines; prediction error minimization; weight adjustment; Artificial neural networks; Backpropagation algorithms; Electrical fault detection; Fault detection; Fault diagnosis; Impedance; Multi-layer neural network; Neural networks; Power distribution lines; Protection;
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5529-6
DOI :
10.1109/IJCNN.1999.836206
