A new method of transient stability assessment in power systems using LS-SVM
This paper presents transient stability assessment of electrical power system using least squares support vector machine (LS-SVM) and principle component analysis. Transient stability of a power system is first determined based on the generator relative rotor angles obtained from time domain simulat...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2007
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| Online Access: | http://psasir.upm.edu.my/id/eprint/47988/1/A%20new%20method%20of%20transient%20stability%20assessment%20in%20power%20systems%20using%20LS-SVM.pdf http://psasir.upm.edu.my/id/eprint/47988/ |
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| Summary: | This paper presents transient stability assessment of electrical power system using least squares support vector machine (LS-SVM) and principle component analysis. Transient stability of a power system is first determined based on the generator relative rotor angles obtained from time domain simulation outputs. Simulations were carried out on the IEEE 9- bus test system considering three phase faults on the system. The data collected from the time domain simulations are then used as inputs to the LS-SVM in which LS-SVM is used as a classifier to determine the stability state of a power system. Principle component analysis is applied to extract useful input features to the LS-SVM so that training time of the LS-SVM can be reduced. To verify the effectiveness of the proposed LS-SVM method, its performance is compared with the multi layer perceptron neural network. Results show that the LS-SVM gives faster and more accurate transient stability assessment compared to the multi layer perceptron neural network in terms of classification results. |
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