• DocumentCode
    2287528
  • Title

    Probabilistic load flow procedure for assessing the distributed generation impact on the high voltage network

  • Author

    Careri, F. ; Genesi, C. ; Marannino, P. ; Montagna, M. ; Rossi, S. ; Siviero, I.

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Pavia, Pavia, Italy
  • fYear
    2011
  • fDate
    25-27 May 2011
  • Firstpage
    882
  • Lastpage
    888
  • Abstract
    This paper presents a Probabilistic Load Flow (PLF) procedure that allows the impact of distributed generation (DG) on the transmission system to be assessed. By means of the Monte Carlo technique, several system states are simulated, varying the power injection of DG. The load flow solution is performed by the Newton-Raphson method and a distributed slack bus formulation is adopted, in order to distribute the active power mismatch (created by the random generation) on all the thermal units in the system. Tests are carried out both on a small system and on the Italian network. Results lead to conclude that the probabilistic approach to the power system analysis provides more indications than the traditional deterministic techniques, especially considering a high penetration of DG.
  • Keywords
    Monte Carlo methods; Newton-Raphson method; distributed power generation; load flow; probability; transmission network calculations; Monte Carlo technique; Newton-Raphson method; active power mismatch; distributed generation impact; distributed slack bus formulation; high voltage network; power injection; probabilistic load flow; transmission system; Load flow; Load modeling; Mathematical model; Monte Carlo methods; Security; Wind farms; Wind power generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Energy Market (EEM), 2011 8th International Conference on the European
  • Conference_Location
    Zagreb
  • Print_ISBN
    978-1-61284-285-1
  • Electronic_ISBN
    978-1-61284-284-4
  • Type

    conf

  • DOI
    10.1109/EEM.2011.5953134
  • Filename
    5953134