• DocumentCode
    3040800
  • Title

    Parametric Sensitivity Study for Wind Power Trading through Stochastic Reserve and Energy Market Optimization

  • Author

    Menin, Michel ; Uzunoglu, Bahri

  • Author_Institution
    Corp. Dominicana de Empresa Electr. Estatales (CDEEE), Santo Domingo, Dominica
  • fYear
    2015
  • fDate
    15-17 April 2015
  • Firstpage
    82
  • Lastpage
    87
  • Abstract
    Trading optimal wind power in energy and regulation markets offer possibilities for increasing revenues as well as impacting security of the system via additional regulation reserve. The bidding in both energy and regulation markets can be computed through stochastic optimization process of both markets as demonstrated in a previous study by Liang. This paper is furthering the previous study by Liang by analyzing the impact of price ratios between energy and reserve market on the revenues for Swedish market. The parametric study reveals that as long as up-regulation prices are below day-ahead energy, the algorithm will bid in both markets to optimize revenue. When regulation prices surpass or equal to day-ahead energy market price then it only bids energy in the regulation market with the current objective function.
  • Keywords
    power generation economics; power markets; power system security; stochastic programming; wind power; Swedish market; day-ahead energy market price; energy market optimization; objective function; optimal wind power trading; parametric sensitivity study; regulation markets; stochastic reserve optimization; system security; up-regulation prices; Linear programming; Optimization; Parametric study; Uncertainty; Wind forecasting; Wind power generation; Reserve market; bidding strategy; electricity market; energy market; power system security; regulation reserve; stochastic optimization; wind power;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Green Technologies Conference (GreenTech), 2015 Seventh Annual IEEE
  • Conference_Location
    New Orleans, LA
  • Type

    conf

  • DOI
    10.1109/GREENTECH.2015.37
  • Filename
    7150233