• DocumentCode
    1718308
  • Title

    New tool for integration of wind power forecasting into power system operation

  • Author

    Gubina, Andrej F. ; Keane, Andrew ; Meibom, Peter ; Sullivan, Jonathan O. ; Goulding, Oisin ; McCartan, Tom ; Malley, Mark O.

  • Author_Institution
    Sch. of Electr., Electron. & Mech. Eng., Univ. Coll. Dublin, Dublin, Ireland
  • fYear
    2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The paper describes the methodology that has been developed for transmission system operators (TSOs) of Republic of Ireland, Eirgrid, and Northern Ireland, SONI the TSO in Northern Ireland, to study the effects of advanced wind power forecasting on optimal short-term power system scheduling. The resulting schedules take into account the electricity market conditions and feature optimal reserve scheduling. The short-term wind power prediction is provided by the Anemos tool, and the scheduling function, including the reserve optimisation, by the Wilmar tool. The proposed methodology allows for evaluation of the impacts that different types of wind energy forecasts (stochastic vs. deterministic vs. perfect) have on the schedules, and how the new incoming information via in-day scheduling impacts the quality of the schedules. Within the methodology, metrics to assess the quality of the schedules is proposed, including the costs, reliability and cycling. The resulting schedules are compared to the Day-ahead and In-day results of the existing scheduling methodology, reserve constrained unit commitment (RCUC), with the historical data used as the input for calibration.
  • Keywords
    load forecasting; scheduling; wind power; Northern Ireland; Wilmar tool; optimal short-term power system scheduling; power system operation; reserve constrained unit commitment; reserve optimisation; scheduling function; transmission system operators; wind power forecasting; Economic forecasting; Power system modeling; Power systems; Predictive models; Stochastic processes; Uncertainty; Weather forecasting; Wind energy; Wind energy generation; Wind forecasting; Forecasting; power generation scheduling; reserve optimization; stochastic scheduling; wind power;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    PowerTech, 2009 IEEE Bucharest
  • Conference_Location
    Bucharest
  • Print_ISBN
    978-1-4244-2234-0
  • Electronic_ISBN
    978-1-4244-2235-7
  • Type

    conf

  • DOI
    10.1109/PTC.2009.5281936
  • Filename
    5281936