DocumentCode :
1897922
Title :
On-line voltage stability monitoring using artificial neural network
Author :
Chakrabarti, Saikat ; 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 :
71
Lastpage :
75
Abstract :
This paper proposes a scheme for on-line voltage stability monitoring using artificial neural network (ANN) and a systematic way for training the ANN. Separate ANNs are used for different contingencies and for different load levels under the same contingency. Results of contingency analysis are used along with principal component analysis (PCA) to choose important input features to train the ANN. Implementation of the feature selection scheme enhances the overall usefulness of the neural network. The proposed scheme is applied on the New England 39-bus power system model.
Keywords :
electric potential; neural nets; power engineering computing; power system measurement; power system stability; principal component analysis; artificial neural network; online voltage stability monitoring; power system model; principal component analysis; Artificial neural networks; Monitoring; Power system analysis computing; Power system measurements; Power system modeling; Power system planning; Power system stability; Principal component analysis; Stability analysis; Voltage;
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.2004.1356271
Filename :
1356271
Link To Document :
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