• DocumentCode
    648241
  • Title

    Intra-day unit commitment for wind farm using model predictive control method

  • Author

    Yonghao Gui ; Chung Hun Kim ; Chung Choo Chung ; Yong-Cheol Kang

  • Author_Institution
    Dept. of Electr. Eng., Hanyang Univ., Seoul, South Korea
  • fYear
    2013
  • fDate
    21-25 July 2013
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper presents centralized control for a wind farm using model predictive control (MPC) method. In order to solve intra-day unit commitment (UC) problem, the UC problem is solved by using the MPC method with short-term wind power forecasting. We introduce a new dynamics model for the UC with some constraints to utilize the benefits of the MPC method. The objective function considering the operation and maintenance costs is formulated by adding a new variable in order to average the operating time of each wind turbine (WT) within the whole time. The proposed method could solve the UC problems on-line using the prediction time horizon that could be selected flexibly considering time horizon based on wind power forecasting errors. From the simulation study using 10 WTs, we observed that the proposed dynamics model of UC effectively provided the optimal solution to each scenario. Numerical study will validate that the proposed method can be applied to solving the UC problem of a large scale wind farm by aggregating WTs.
  • Keywords
    load forecasting; power system control; predictive control; wind power plants; wind turbines; intra-day unit commitment; model predictive control; short-term wind power forecasting; wind farm; wind power forecasting errors; wind turbine; Forecasting; Linear programming; Power system dynamics; Predictive control; Wind farms; Wind power generation; Wind turbines; Centralized control; MPC; unit commitment; wind farm; wind turbine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting (PES), 2013 IEEE
  • Conference_Location
    Vancouver, BC
  • ISSN
    1944-9925
  • Type

    conf

  • DOI
    10.1109/PESMG.2013.6672813
  • Filename
    6672813