DocumentCode :
2590360
Title :
ANN Design for Fast Security Evaluation of Interconnected Systems with Large Wind Power Production
Author :
Vasconcelos, Helena ; Lopes, J. A Peças
Author_Institution :
INSEC Porto
fYear :
2006
fDate :
11-15 June 2006
Firstpage :
1
Lastpage :
6
Abstract :
This paper presents the performed steps to design an artificial neural network (ANN) tool, able to evaluate, within the framework of on-line security assessment, the dynamic security of interconnected power systems having an increased penetration of wind power production. This approach exploits functional knowledge generated off-line, the linear regression (LR) variable selection stepwise method to perform automatic feature subset selection (FSS) and ANN to provide a way for fast evaluation of the system security degree. In order to choose the best input/output set of variables for the ANN tool, a comparative analysis is performed, regarding the obtained predicting error, by performing a statistical hypothesis test. The reduced error results confirm the feasibility and quality of the derived security structures
Keywords :
neural nets; power system interconnection; power system security; regression analysis; wind power; ANN design; FSS; LR; artificial neural network; feature subset selection; interconnected systems; linear regression; on-line security assessment; security evaluation; statistical hypothesis test; wind power production; Artificial neural networks; Interconnected systems; Linear regression; Performance evaluation; Power system dynamics; Power system interconnection; Power system security; Production systems; Wind energy; Wind energy generation; Artificial neural networks; Dynamic behavior; Feature selection; Interconnected systems; Linear regression; Security assessment; Wind generation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Probabilistic Methods Applied to Power Systems, 2006. PMAPS 2006. International Conference on
Conference_Location :
Stockholm
Print_ISBN :
978-91-7178-585-5
Type :
conf
DOI :
10.1109/PMAPS.2006.360206
Filename :
4202218
Link To Document :
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