DocumentCode :
1897934
Title :
On-line transient stability assessment using artificial neural network
Author :
Sawhney, Harinder ; Jeyasurya, B.
Author_Institution :
Fac. of Eng. & Appl. Sci., Memorial Univ. of Newfoundland, St. John´´s, Nfld., Canada
fYear :
2004
fDate :
28-30 July 2004
Firstpage :
76
Lastpage :
80
Abstract :
This paper proposes an application of artificial neural network (ANN) for contingency screening and ranking of a power system with respect to transient stability. Feature selection techniques are used to select the important features as input to the neural network. The proposed scheme is applied to two sample power systems. Results presented show the merit of the scheme for on-line transient stability assessment (TSA).
Keywords :
neural nets; online operation; power engineering computing; power system transient stability; artificial neural network; feature selection techniques; online transient stability assessment; Artificial neural networks; Neural networks; Power system dynamics; Power system faults; Power system modeling; Power system reliability; Power system security; Power system stability; Power system transients; Stability criteria;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Engineering, 2004. LESCOPE-04. 2004 Large Engineering systems Conference on
Print_ISBN :
0-7803-8386-9
Type :
conf
DOI :
10.1109/LESCPE.2004.1356272
Filename :
1356272
Link To Document :
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