Title :
Distinguish between fault and switching operation generated transients using a fuzzy neural network
Author :
Bo, Z.Q. ; Wang, G.S. ; Jiang, F. ; Moore, P.J. ; Johns, A.T.
Author_Institution :
Bath Univ., UK
Abstract :
This paper proposes a technique for discriminating between faults and switching operations on a transmission system using a fuzzy logic controlled neural network (FCNN). In the technique, a specially designed transient detector is employed to capture the fault and switching operation induced transients. The detector outputs are used to train a fuzzy logic controlled neural network. The FCNN detects the different characteristics of switching from that of the fault. The digital modelling of typical 400 kV transmission system which includes a switching arc model is presented in the paper. The results show that the trained FCNN is able to discriminate between a fault and a switching operation under various system and fault conditions
Keywords :
electrical faults; fuzzy neural nets; learning (artificial intelligence); power system analysis computing; power system transients; switching; transmission network calculations; computer simulation; detector outputs; fault discrimination; fuzzy logic-controlled neural network; neural net training; switching arc model; switching operations; transient detector; transmission system; Circuit faults; Distributed parameter circuits; Fault detection; Frequency; Fuzzy logic; Fuzzy neural networks; Neural networks; Power system transients; Power transmission lines; Surges;
Conference_Titel :
Energy Management and Power Delivery, 1998. Proceedings of EMPD '98. 1998 International Conference on
Print_ISBN :
0-7803-4495-2
DOI :
10.1109/EMPD.1998.705458