• DocumentCode
    3217376
  • Title

    Wind power day-ahead uncertainty management through stochastic unit commitment policies

  • Author

    Ruiz, Pablo A. ; Philbrick, C. Russ ; Sauer, Peter W.

  • Author_Institution
    CRA Int., Cambridge, MA
  • fYear
    2009
  • fDate
    15-18 March 2009
  • Firstpage
    1
  • Lastpage
    9
  • Abstract
    Day-ahead uncertainty management in power systems has traditionally been approached by means of multistage decision making and operating reserve requirements. An alternate approach for managing uncertainty is a stochastic formulation, which allows the explicit modeling of the sources of uncertainty. The large investments in wind power has increased the importance of operations uncertainty management due to the considerable operational uncertainty wind plants have. This paper evaluates the benefits of a combined approach that uses stochastic and reserve methods for the efficient management of uncertainty in the unit commitment problem for systems with significant amount of wind power. Numerical studies on a model of the PSCo system show that the unit commitment solutions obtained for the combined approach are robust and superior with respect to the traditional approach in terms of economic metrics and curtailed wind power.
  • Keywords
    numerical analysis; power generation dispatch; power generation scheduling; power system management; stochastic processes; wind power plants; decision making; economic metrics; stochastic formulation; stochastic unit commitment policies; wind plants; wind power day-ahead uncertainty management; Decision making; Energy management; Investments; Power system management; Power system modeling; Robustness; Stochastic processes; Stochastic systems; Uncertainty; Wind energy; Monte-Carlo simulation; Wind power; economic dispatch; operating reserve; reliability; stochastic programming; unit commitment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Systems Conference and Exposition, 2009. PSCE '09. IEEE/PES
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    978-1-4244-3810-5
  • Electronic_ISBN
    978-1-4244-3811-2
  • Type

    conf

  • DOI
    10.1109/PSCE.2009.4840133
  • Filename
    4840133