• DocumentCode
    2590652
  • Title

    Power System Adequacy and Security Calculations Using Monte Carlo Simulation incorporating Intelligent System Methodology

  • Author

    Singh, Chanan ; Luo, Xiaochuan ; Kim, Hyungchul

  • Author_Institution
    Dept. of Electr. Eng., Texas A&M Univ., College Station, TX
  • fYear
    2006
  • fDate
    11-15 June 2006
  • Firstpage
    1
  • Lastpage
    9
  • Abstract
    Monte Carlo simulation has been extensively used in reliability evaluation of electric power systems. One of the issues with this approach has been the computational time for convergence of indices being estimated, especially when the systems are highly reliable. Perhaps the most commonly used approach to deal with this problem has been some version of variance reduction techniques. Recently some publications have proposed use of intelligent systems techniques such as self-organizing maps and linear vector quantization to tackle this problem. This paper will provide a perspective on this hybrid approach using Monte Carlo Simulation and intelligent system methods. The philosophy of this hybridization as well some results will be discussed
  • Keywords
    Monte Carlo methods; power system reliability; power system security; power system simulation; self-organising feature maps; Monte Carlo simulation; computational time; convergence; intelligent system; linear vector quantization; power system security calculations; reliability evaluation; self-organizing maps; variance reduction techniques; Analytical models; Computational intelligence; Computational modeling; Convergence; Hybrid intelligent systems; Intelligent systems; Monte Carlo methods; Power system reliability; Power system security; Power system simulation; Monte Carlo Simulation; Reliability; Self Organizing Maps; linear vector quantization; neural nets;
  • 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.2006.360224
  • Filename
    4202236