• 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