• DocumentCode
    157686
  • Title

    Sensitivity analysis of a simulation model for evaluating renewable distributed generation on a power network

  • Author

    Mena, Rodrigo ; Zio, Enrico ; Hennebel, Martin

  • Author_Institution
    Syst. Sci. & the Energetic Challenge, Ecole Centrale Paris - Supelec, Paris, France
  • fYear
    2014
  • fDate
    7-10 July 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    We present a sensitivity analysis of a simulation model for the evaluation of the performance of a renewable distributed generation (DG) network. Uncertainties in renewable energy sources, components failure and repair events, loads and grid power supply are taken into account. The sensitivity analysis is performed with respect to the characteristic uncertain variables associated to each type of DG technology available. The impact of these uncertain variables is evaluated in terms of two performance functions, global cost (Cg) and energy not supplied (ENS). The results show the trends of performance of the DG-integrated network under different conditions. This allows evaluating the impact of the different technologies.
  • Keywords
    Monte Carlo methods; distributed power generation; failure analysis; maintenance engineering; power generation faults; power grids; renewable energy sources; sensitivity analysis; DG-integrated network; Monte Carlo simulation; characteristic uncertain variables; components failure; distributed generation network; energy not supplied; global cost; grid power supply; power network; renewable distributed generation performance evaluation; renewable energy sources; repair events; sensitivity analysis; simulation model; Analytical models; Equations; Load modeling; Power demand; Sensitivity analysis; Uncertainty; Monte Carlo simulation; distribution network; renewable energy generation; sensitivity analysis; uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Probabilistic Methods Applied to Power Systems (PMAPS), 2014 International Conference on
  • Conference_Location
    Durham
  • Type

    conf

  • DOI
    10.1109/PMAPS.2014.6960673
  • Filename
    6960673