• DocumentCode
    2051227
  • Title

    Probabilistic load flow computation using first-order second-moment method

  • Author

    Can Wan ; Zhao Xu ; Zhao Yang Dong ; Kit Po Wong

  • Author_Institution
    Dept. of Electr. Eng., Hong Kong Polytech. Univ., Hong Kong, China
  • fYear
    2012
  • fDate
    22-26 July 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper proposes a new probabilistic load flow method based on the first-order second-moment method. The proposed method aims to obtain the mean and standard deviation of load flow solution distributions considering various uncertainties in system operation. Power injection uncertainties including fluctuation of loads and unit outages are considered in the probabilistic load flow calculation. The performance of the proposed method is examined by comparing the results with those from Monte Carlo simulation using IEEE 9-bus and 118-bus test systems. A normalized accuracy and efficiency based procedure is developed for result analyses. Numerical tests demonstrate that the proposed method can obtain accurate results while reducing the computation time significantly.
  • Keywords
    Monte Carlo methods; computational complexity; load flow; method of moments; IEEE 118-bus test systems; IEEE 9-bus test systems; Monte Carlo simulation; computation time; efficiency based procedure; first-order second-moment method; loads fluctuation; mean deviation; normalized accuracy; power injection uncertainties; probabilistic load flow computation; standard deviation; unit outages; Accuracy; Equations; Load flow; Mathematical model; Probabilistic logic; Standards; Uncertainty; First-order second-moment method; power system; probabilistic density function; probabilistic load flow;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting, 2012 IEEE
  • Conference_Location
    San Diego, CA
  • ISSN
    1944-9925
  • Print_ISBN
    978-1-4673-2727-5
  • Electronic_ISBN
    1944-9925
  • Type

    conf

  • DOI
    10.1109/PESGM.2012.6345023
  • Filename
    6345023