DocumentCode :
976072
Title :
New method for generators´ angles and angular velocities prediction for transient stability assessment of multimachine power systems using recurrent artificial neural network
Author :
Bahbah, Amr G. ; Girgis, Adly A.
Author_Institution :
Clemson Univ., SC, USA
Volume :
19
Issue :
2
fYear :
2004
fDate :
5/1/2004 12:00:00 AM
Firstpage :
1015
Lastpage :
1022
Abstract :
Recurrent radial basis function (RBF) and multilayer perceptron (MLP) artificial neural network (ANN) schemes are proposed for dynamic system modeling, and generators´ angles and angular velocities prediction for transient stability assessment. The method is presented for multimachine power systems. In this scheme, transient stability is assessed based on monitoring generators´ angles and angular velocities with time, and checking whether they exceed the specified limits for system stability or not. Data generation schemes have been proposed. The proposed recurrent ANN scheme is not sensitive to fault locations. It is only dependent on the postfault system configuration.
Keywords :
angular velocity; multilayer perceptrons; power engineering computing; power system transient stability; radial basis function networks; angular velocity prediction; data generation schemes; generator angles; multilayer perceptrons; multimachine power system; recurrent artificial neural network; recurrent radial basis function; transient stability assessment; Angular velocity; Artificial neural networks; Monitoring; Multilayer perceptrons; Power generation; Power system dynamics; Power system faults; Power system modeling; Power system stability; Power system transients;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2004.826765
Filename :
1295012
Link To Document :
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