• DocumentCode
    1803677
  • Title

    A practical method of unit commitment considering wind power

  • Author

    Yang, Pengpeng ; Zhao, Long ; Li, Zhi

  • Author_Institution
    Planning & Consulting Dept., Shandong Electr., Power Eng. Consulting Inst. Corp., Ltd., Jinan, China
  • fYear
    2010
  • fDate
    5-7 Nov. 2010
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    In this paper, a dispersed probability distribution model is built based on statistics of wind power forecasting error. Thus, the probabilistic reserve constraints in the analytic expression can be introduced into the traditional unit commitment (UC) model by Gauss function fitting of the distributions of different generations considering wind power. Otherwise, in order to solve the UC problem with these reserve constraints efficiently, this paper presents an improved approach of modifying Lagrangian multipliers based on the concept of average cost in the unit decommitment (UD) method. In addition, the search range and economic indices of units are also improved. A 26-unit system is analyzed to exhibit the effectiveness of the probabilistic reserve constraints and the proposed UD method.
  • Keywords
    Gaussian distribution; load forecasting; power generation dispatch; power generation scheduling; probability; wind power; Gauss function fitting; Lagrangian multipliers; economic unit index; probabilistic reserve constraints; probability distribution; unit commitment; wind power forecasting error; Cost function; Forecasting; Power systems; Probabilistic logic; Probability distribution; Wind power generation; Lagrangian mutiplier; forcasting errors; power system; unit decommitment; window power;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    World Non-Grid-Connected Wind Power and Energy Conference (WNWEC), 2010
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-8920-6
  • Electronic_ISBN
    978-1-4244-8921-3
  • Type

    conf

  • DOI
    10.1109/WNWEC.2010.5673177
  • Filename
    5673177