Title :
Comparing least squares support vector machine and probabilistic neural network in transient stability assessment of a large-scale power system
Author :
Wahab, Noor Izzri Abdul ; Mohamed, Azah ; Hussain, Aini
Author_Institution :
Dept. of Electr., Univ. Kebangsaan Malaysia, Bangi
Abstract :
This paper presents transient stability assessment of a large practical power system using two artificial neural network techniques which are the probabilistic neural network (PNN) and the least squares support vector machine (LS-SVM). The large power system is divided into five smaller areas depending on the coherency of the areas when subjected to disturbances. This is to reduce the number of data sets collected for the respective areas. Transient stability of the power system is first determined based on the generator relative rotor angles obtained from time domain simulation outputs. Simulations were carried out on the test system considering three phase faults at different loading conditions. The data collected from the time domain simulations are then used as inputs to the PNN and LS-SVM. Both networks are used as classifiers to determine whether the power system is stable or unstable. Classification results show that the PNN gives faster and more accurate transient stability assessment compared to the LS-SVM.
Keywords :
fault diagnosis; neural nets; power engineering computing; power system transient stability; support vector machines; generator relative rotor angles; large-scale power system; least squares support vector machine; power system disturbances; probabilistic neural network; time domain simulations; transient stability assessment; Artificial neural networks; Large-scale systems; Least squares methods; Neural networks; Power generation; Power system faults; Power system simulation; Power system stability; Power system transients; Support vector machines; least squares support vector machine; probabilistic neural network; transient stability assessment;
Conference_Titel :
Power and Energy Conference, 2008. PECon 2008. IEEE 2nd International
Conference_Location :
Johor Bahru
Print_ISBN :
978-1-4244-2404-7
Electronic_ISBN :
978-1-4244-2405-4
DOI :
10.1109/PECON.2008.4762523