• DocumentCode
    647595
  • Title

    Applying probabilistic collocation method to power flow analysis in networks with wind farms

  • Author

    Keyou Wang ; Guojie Li ; Xiuchen Jiang

  • Author_Institution
    Dept. of Electr. Eng., Shanghai Jiao Tong Univ., Shanghai, China
  • fYear
    2013
  • fDate
    21-25 July 2013
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In power systems with a high wind power penetration, probabilistic load flow analysis is a fundamental problem for system planning and operation due to the uncertainty and fast fluctuation of wind speed. This paper proposes probabilistic collocation method (PCM) for load flow analysis with a penetration of wind farms. The orthogonal polynomials are utilized to generate the approximation of the random variable of interest as the function of uncertainty parameters. The proposed method is a computational efficient solution to provide quite an accurate approximation for the given probability distribution of system response. Therefore the method can significantly reduce the computational time compared to the traditional brute force Monte Carlo approach. Illustration examples are given on the IEEE 39 bus system to show the effectiveness of the proposed method.
  • Keywords
    Monte Carlo methods; Weibull distribution; load flow; probability; wind power plants; Monte Carlo approach; high wind power penetration; orthogonal polynomials; power flow analysis; power systems; probabilistic collocation method; probabilistic load flow analysis; probability distribution; system planning; wind farms; wind speed; Approximation methods; Mathematical model; Phase change materials; Polynomials; Probabilistic logic; Uncertainty; Wind speed; Probabilistic Collocation Method; Probabilistic Load Flow; Uncertainty Analysis; Weibull Distribution; Wind Energy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting (PES), 2013 IEEE
  • Conference_Location
    Vancouver, BC
  • ISSN
    1944-9925
  • Type

    conf

  • DOI
    10.1109/PESMG.2013.6672103
  • Filename
    6672103