Prediction of cascading collapse occurrence due to the effect of hidden failure protection system using different training algorithms feed-forward neural network / N. H. Idris ...[et al.]
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...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
UiTM Press
2017
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/63015/1/63015.pdf https://ir.uitm.edu.my/id/eprint/63015/ https://jeesr.uitm.edu.my/v1/ |
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| Summary: | 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) |
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