Paper
The Classification of Power Swing Based on PNN and MLPNN
- Authors:
- Ahmad Farid Bin Abidin; Azah Mohamed; Hussein Shareef
- Abstract
- An intelligent approach is developed to discriminate a fault, stable swing and unstable swing for correct distance relay operation by using the S-transform and the probabilistic neural network (PNN). To illustrate the effectiveness of the proposed techniques, simulations were carried out on the IEEE 39 bus and a practical test system using the PSS/E and MATLAB software. Test results show that the PNN gives an overall classification accuracy of 97.33% in which it performs better than MLPNN in detecting and classifying unstable swing, stable swing, fault, fault clearance and post fault events. Such fast and accurate intelligent detection schemes are useful for preventing distance relay from tripping during power swing.
- Keywords
- Unstable Swing; Stable Swing; S-transform; Probabilistic Neural Network (PNN); Multi Layer Perceptron Neural Network (MLPNN)
- StartPage
- 44
- EndPage
- 53
- Doi