• DocumentCode
    631030
  • Title

    MPC for reducing energy storage requirement of wind power systems

  • Author

    Chiao-Ting Li ; Huei Peng ; Jing Sun

  • Author_Institution
    Dept. of Mech. Eng., Univ. of Michigan, Ann Arbor, MI, USA
  • fYear
    2013
  • fDate
    17-19 June 2013
  • Firstpage
    6607
  • Lastpage
    6612
  • Abstract
    This paper discusses using the battery energy storage system (BESS) to mitigate wind power intermittency, so that wind power can be dispatchable on an hourly basis like fossil fuel power plants. In particular, model predictive control (MPC) is used to control the charge and discharge of BESS to compensate for wind power forecast errors and minimize operation costs to the wind farm owner. A ramp rate penalty on wind power scheduling is included in the optimization to make the optimal control trajectory smoother, while the performance is kept intact. Numerical simulations with a one-year long wind power dataset show that MPC controller is much more effective in reducing the operation cost to the wind farm owner than the heuristic control algorithm or conventional reserves, in that BESS with a much smaller capacity will be suffice to achieve the same cost reduction.
  • Keywords
    battery storage plants; error compensation; load forecasting; numerical analysis; optimal control; power generation control; power generation economics; power generation scheduling; predictive control; wind power plants; MPC controller; battery energy storage system; charge control; discharge control; energy storage requirement reduction; fossil fuel power plants; model predictive control; numerical simulations; operation cost minimization; operation cost reduction; optimal control trajectory smoother; ramp rate penalty; wind farm; wind power forecast error compensation; wind power intermittency mitigation; wind power scheduling; wind power systems; Batteries; Discharges (electric); Heuristic algorithms; System-on-chip; Wind farms; Wind forecasting; Wind power generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2013
  • Conference_Location
    Washington, DC
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4799-0177-7
  • Type

    conf

  • DOI
    10.1109/ACC.2013.6580876
  • Filename
    6580876