• DocumentCode
    2717
  • Title

    Probabilistic power flow of correlated hybrid wind-photovoltaic power systems

  • Author

    Aien, Morteza ; Khajeh, Morteza Gholipour ; Rashidinejad, Masoud ; Fotuhi-Firuzabad, Mahmud

  • Author_Institution
    Dept. of Electr. Eng., Grad. Univ. of Adv. Technol., Kerman, Iran
  • Volume
    8
  • Issue
    6
  • fYear
    2014
  • fDate
    Aug-14
  • Firstpage
    649
  • Lastpage
    658
  • Abstract
    As a matter of course, the unprecedented ascending penetration of distributed energy resources, mainly harvesting renewable energies such as wind and solar, is concomitant with environmentally friendly concerns. This type of energy resources are innately uncertain and bring about more uncertainties in the power system context, consequently, necessitates probabilistic analysis of the system performance. Moreover, the uncertain parameters may have a considerable level of correlation to each other, in addition to their uncertainties. The two point estimation method (2PEM) is recognised as an appropriate probabilistic method. This study proposes a new methodology for probabilistic power flow studies for such a problem by modifying the 2PEM. The original 2PEM cannot handle correlated uncertain variables, but the proposed method has been equipped with this ability. To justify the impressiveness of the method, two case studies namely the Wood & Woollenberg 6-bus and the IEEE118-bus test systems are examined using the proposed method, then the obtained results are compared against the Monte Carlo simulation results. Comparison of the results justifies the effectiveness of the method in the respected area with regards to both accuracy and execution time criteria.
  • Keywords
    hybrid power systems; load flow; photovoltaic power systems; probability; wind power plants; 2PEM; IEEE118-bus test systems; Wood &Woollenberg 6-bus; correlated hybrid wind-photovoltaic power systems; probabilistic power flow; two point estimation method;
  • fLanguage
    English
  • Journal_Title
    Renewable Power Generation, IET
  • Publisher
    iet
  • ISSN
    1752-1416
  • Type

    jour

  • DOI
    10.1049/iet-rpg.2013.0120
  • Filename
    6867442