DocumentCode :
3301054
Title :
A hybrid approach for security evaluation and preventive control of power systems
Author :
Niazi, K.R. ; Arora, C.M. ; Surana, S.L.
Author_Institution :
Malaviya Nat. Inst. of Technol., Jaipur, India
fYear :
2003
fDate :
15-16 Dec. 2003
Firstpage :
193
Lastpage :
199
Abstract :
This paper presents a hybrid approach for online security evaluation and preventive control of power systems. The artificial neural network (ANN) offers potential advantages regarding efficient computation and ease of knowledge acquisition. However it is a "black box" type approach, which lacks interpretability. The decision tree (DT) approach is known for its interpretability but comparatively less accurate. The proposed hybrid approach combines ANN and DT approaches to exploit their potential while suppressing their drawbacks. It applies an ANN for security evaluation of power systems and DT methodology to drive preventive control measures. A divergence based feature selection algorithm has been investigated to select an optimal combination of neural training features. The method has been applied on an IEEE power system and the results obtained are promising.
Keywords :
decision trees; knowledge acquisition; learning (artificial intelligence); neural nets; power system analysis computing; power system control; power system security; power system transient stability; ANN; IEEE power system; artificial neural network; black box type approach; decision tree approach; divergence based feature selection algorithm; hybrid approach; interpretability; knowledge acquisition; neural training features; power system preventive control; power system security evaluation; Artificial neural networks; Computer networks; Control systems; Decision trees; Hybrid power systems; Knowledge acquisition; Power system control; Power system measurements; Power system security; Power systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Engineering Conference, 2003. PECon 2003. Proceedings. National
Print_ISBN :
0-7803-8208-0
Type :
conf
DOI :
10.1109/PECON.2003.1437442
Filename :
1437442
Link To Document :
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