DocumentCode :
75890
Title :
A Novel Implementation for Generator Rotor Angle Stability Prediction Using an Adaptive Artificial Neural Network Application for Dynamic Security Assessment
Author :
Al-Masri, Ahmed Naufal ; Ab Kadir, M.Z.A. ; Hizam, H. ; Mariun, N.
Author_Institution :
Fac. of Inf. Sci. & Eng., Manage. & Sci. Univ., Shah Alam, Malaysia
Volume :
28
Issue :
3
fYear :
2013
fDate :
Aug. 2013
Firstpage :
2516
Lastpage :
2525
Abstract :
This paper addresses a new approach for predicting the generator rotor angle using an adaptive artificial neural network (AANN) for power system stability. The aim of this work is to predict the stability status for each generator when the system is under a contingency. This is based on the initial condition of an operating point, which is represented by the generator rotor angle at a certain load level. An automatic data generation algorithm is developed for the training and testing process. The proposed method has been successfully tested on the IEEE 9-bus test system and the 87-bus system for Peninsular Malaysia.
Keywords :
electric generators; neural nets; power engineering computing; power system security; power system stability; rotors; AANN; IEEE 87-bus system; IEEE 9-bus test system; Peninsular Malaysia; adaptive artificial neural network application; automatic data generation algorithm; dynamic security assessment; generator rotor angle stability prediction; power system stability; Generators; Power system stability; Rotors; Security; Stability criteria; Training; Artificial neural network (ANN); contingency analysis; dynamic security assessment (DSA); rotor angle stability;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2013.2247069
Filename :
6472123
Link To Document :
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