Abstract
Protection system plays a significant role in power
system and operation of electrical networks especially in
transmission system. The outage in transmission line that causes
from hidden failure in protection system should be avoided.
Artificial Neural Network (ANN) is one of the problem solver with
variety of training algorithms that helps to predict the cascading
collapse occurrence due to the hidden failure effect. The historical
data obtained from NERC report is analyzed and being used in
ANN for prediction purposed. This paper compares the supervised
training algorithms of feed-forward neural network with
backpropagation include Lavenberg- Marquadt (LM), Scale
Conjugate Gradient (SCG) and Quasi Newton Backpropagation
(BFG). IEEE 14 bus system is used as a case study. The
performance of the training algorithms is analyzed based on
Correlation Coefficient (R) and Mean Square Error (MSE)
Metadata
Item Type: | Article |
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Creators: | Creators Email / ID Num. Idris, N. H. norhazwaniidris@yahoo.com Salim, N. A. UNSPECIFIED Othman, M. M. UNSPECIFIED Yasin, Z. M. UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Neural networks (Computer science) |
Divisions: | Universiti Teknologi MARA, Shah Alam > Faculty of Electrical Engineering |
Journal or Publication Title: | Journal of Electrical and Electronic Systems Research (JEESR) |
UiTM Journal Collections: | UiTM Journal > Journal of Electrical and Electronic Systems Research (JEESR) |
ISSN: | 1985-5389 |
Volume: | 11 |
Page Range: | pp. 45-50 |
Keywords: | ANN, Cascading Collapse, Hidden Failure, Training Algorithms Neural Networks, Prediction |
Date: | December 2017 |
URI: | https://ir.uitm.edu.my/id/eprint/63015 |