08-16-2017, 08:48 PM
Abstract
A novel application of neural network approach to protection of transmission line is demonstrated in this paper. Different system faults on a protected transmission line should be detected and classified rapidly and correctly. This paper presents the use of neural networks as a protective relaying pattern classifier algorithm. The proposed method uses current signals to learn the hidden relationship in the input patterns. Using the proposed approach, fault detection, classification and faulted phase selection could be achieved within a quarter of cycle. An improved performance is experienced once the neural network is trained sufficiently and suitably, thus performing correctly when faced with different system parameters and conditions. Results of performance studies show that the proposed neural network- based module can improve the performance of conventional fault selection algorithms.
Presented By:
M. Sanaye-Pasand, H. Khorashadi-Zadeh
read full report
http://ipstTechPapers/2003/IPST03Paper5a-1.pdf