• DocumentCode
    3299500
  • Title

    Unit commitment and operating reserves with probabilistic wind power forecasts

  • Author

    Botterud, Audun ; Zhou, Zhengchun ; Wang, Jiacheng ; Valenzuela, Jorge ; Sumaili, Jean ; Bessa, R.J. ; Keko, Hrvoje ; Miranda, V.

  • Author_Institution
    Decision & Inf. Sci. Div., Argonne Nat. Lab., Argonne, IL, USA
  • fYear
    2011
  • fDate
    19-23 June 2011
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    In this paper we discuss how probabilistic wind power forecasts can serve as an important tool to efficiently address wind power uncertainty in power system operations. We compare different probabilistic forecasting and scenario reduction methods, and test the resulting forecasts on a stochastic unit commitment model. The results are compared to deterministic unit commitment, where dynamic operating reserve requirements can also be derived from the probabilistic forecasts. In both cases, the use of probabilistic forecasts contributes to improve the system performance in terms of cost and reliability.
  • Keywords
    load forecasting; power generation dispatch; power generation reliability; probability; stochastic processes; wind power plants; deterministic unit commitment; dynamic operating reserve requirements; power system operations; probabilistic wind power forecasts; reliability; stochastic unit commitment model; unit commitment; wind power uncertainty; Forecasting; Probabilistic logic; Stochastic processes; Uncertainty; Wind forecasting; Wind power generation; Wind power; dispatch; probabilistic forecasts; scenario reduction; unit commitment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    PowerTech, 2011 IEEE Trondheim
  • Conference_Location
    Trondheim
  • Print_ISBN
    978-1-4244-8419-5
  • Electronic_ISBN
    978-1-4244-8417-1
  • Type

    conf

  • DOI
    10.1109/PTC.2011.6019263
  • Filename
    6019263