Title :
Artificial neural networks for power systems diagnosis
Author :
Navarro, Victor ; da Silva, A.L. ; De Carvalho, Luis A V ; Zaverucha, Gerson
Author_Institution :
COPPE, Univ. Federal do Rio de Janeiro, Brazil
fDate :
27 Jun- 2 Jul 1994
Abstract :
In this paper, we study the application of artificial neural networks to help a power system´s operator to diagnose the faults during a disturbance. Towards this goal, an analysis of the training and simulation of an intelligent alarm processor of a simplified power system generation plant is presented in detail. This system is capable of diagnosing not only single faults but also multiple ones, even when the associated alarm set is incomplete. The results obtained demonstrate that neural network is a very powerful and reliable method for the solution of existing problems in power systems
Keywords :
electrical faults; fault diagnosis; fault location; neural nets; power system analysis computing; artificial neural networks; disturbance; fault diagnosis; intelligent alarm processor; power systems diagnosis; Analytical models; Artificial intelligence; Artificial neural networks; Neural networks; Power generation; Power system analysis computing; Power system faults; Power system reliability; Power system simulation; Power systems;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374804
