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
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