• DocumentCode
    1993953
  • Title

    Mixed AC/DC OPF using differential evolution for global minima identification

  • Author

    Marten, Anne-Katrin ; Sass, Florian ; Westermann, Dirk

  • Author_Institution
    Dept. of Power Syst., Tech. Univ. Ilmenau, Ilmenau, Germany
  • fYear
    2015
  • fDate
    June 29 2015-July 2 2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    There are a lot of challenges coming up for the transmission system in Europe. This is mainly caused by tremendous increasing infeed from renewable energies in remote areas as the North Sea and increasing cross border energy trades. A suitable solution is a meshed onshore HVDC grid spanning the existing AC transmission grid. This new transmission layer must be actively included in grid´s operation management in order to make use of its whole advantages. A part of it is operation planning for meshed HVDC grids integrated in an AC system. Therefore a mixed AC/DC optimal power flow can be used. As conventional optimization methods for such kind of optimization problems converge in local minima or do not converge at all, this paper proposed application of an artificial intelligence optimization algorithm namely differential evolution.
  • Keywords
    HVDC power transmission; evolutionary computation; load flow; power grids; power system management; power transmission planning; AC transmission grid; Europe; North Sea; artificial intelligence optimization; differential evolution; global minima identification; grid´s operation management; meshed onshore HVDC grid operation planning; mixed AC-DC OPF; mixed AC-DC optimal power flow; renewable energy; transmission system; Artificial intelligence; Convergence; HVDC transmission; Linear programming; Optimization; Sociology; Statistics; HVDC grid operation; converter schedules; local minima; mixed AC/DC OPF;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    PowerTech, 2015 IEEE Eindhoven
  • Conference_Location
    Eindhoven
  • Type

    conf

  • DOI
    10.1109/PTC.2015.7232830
  • Filename
    7232830