Application of artificial neural network for voltage stability assessment / Idris Harun
This report presents an application of Artificial Neural Network model for prediction of voltage stability condition in power system network. Voltage stability analysis involves the determination of stability factor, i.e. L-factor. The ANN by using the Back-Propagation method was selected. The ANN m...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
2003
|
| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/77858/1/77858.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | This report presents an application of Artificial Neural Network model for prediction of voltage stability condition in power system network. Voltage stability analysis involves the determination of stability factor, i.e. L-factor. The ANN by using the Back-Propagation method was selected. The ANN model developed has three layers i.e. input layer, hidden layer and output layer. The same sets of data have used in the training and the same other sets of data for testing process. AU those sets of data were obtained by the Load Flow programme. Real, reactive power, Vload and Oload have been used as input nodes and L-factor values as output node. Tests were carried out and the results were compared on the basic of learning rate, momentum, number of hidden node and iteration. From the results, it shows that the artificial neural network can be used to predict the level of voltage stability condition. |
|---|