• DocumentCode
    1467914
  • Title

    Reliability Assessment of Time-Dependent Systems via Sequential Cross-Entropy Monte Carlo Simulation

  • Author

    González-Fernández, Reinaldo A. ; Silva, Armando M Leite da

  • Author_Institution
    Inst. of Electr. Syst. & Energy, Fed. Univ. of Itajuba-UNIFEI, Itajuba, Brazil
  • Volume
    26
  • Issue
    4
  • fYear
    2011
  • Firstpage
    2381
  • Lastpage
    2389
  • Abstract
    This paper proposes a new methodology to evaluate system generating capacity reliability indices considering time-dependent power sources and loads. Based on sequential Monte Carlo simulation (MCS) and the cross-entropy (CE) method, the basic idea is to find an optimal distortion for the equipment transition rates using the CE concepts. A chronological simulation is then carried out using these newly found optimal reference parameters. This process suitably modifies the chronological evolution of the system in order to improve its statistical efficiency and convergence properties. As a result, the computational efforts of the sequential simulation can be greatly reduced while retaining many of its main advantages. Comparisons with the chronological, pseudo-chronological, and quasi-sequential MCS are carried out using the IEEE-RTS-96 (Reliability Test System) and modifications of this system that include renewable sources.
  • Keywords
    Monte Carlo methods; distortion; power system reliability; renewable energy sources; statistical analysis; CE method; IEEE-RTS-96; convergence properties; optimal distortion; optimal reference parameters; power load; pseudo-chronological simulation; quasi-sequential MCS; reliability assessment; renewable sources; sequential cross-entropy Monte Carlo simulation; sequential simulation; statistical efficiency; time-dependent system power source; Computational modeling; Load modeling; Monte Carlo methods; Power system reliability; Renewable energy resources; Risk analysis; Cross-entropy method; Monte Carlo simulation; rare events; reliability assessment; renewable energy sources; risk analysis;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2011.2112785
  • Filename
    5727933