• DocumentCode
    620408
  • Title

    Nonlinear distributed MPC strategy with application to AGC of interconnected power system

  • Author

    Huiyun Nong ; Xiangjie Liu

  • Author_Institution
    Sch. of Control & Comput. Eng., North China Electr. Power Univ., Beijing, China
  • fYear
    2013
  • fDate
    25-27 May 2013
  • Firstpage
    3935
  • Lastpage
    3940
  • Abstract
    In practical power system, the existence of the valve limit on the governor and the generation rate constraints (GRC) present great challenge to the automatic generation control (AGC). In this paper, the valve limit on the governor is modeled by a T-S model, and a distributed model predictive control (MPC) method is employed to AGC to cope with the generation rate constraints (GRC). Model predictive control is a popular control strategy which takes systematic account of process input, state and output constraints, and distributed MPC is suitable for controlling large-scale networked systems such as power system. This method decomposes the overall system into subsystems, each with its own MPC controller. The proposed methodology is tested with a four-area interconnected power system. Simulation results demonstrate the proposed distributed MPC achieves performance equivalent to centralized MPC.
  • Keywords
    centralised control; distributed parameter systems; networked control systems; nonlinear control systems; power system control; power system interconnection; predictive control; AGC; GRC; T-S model; centralized model predictive control method; four-area interconnected power system; generation rate constraints; governor; large-scale networked controller; nonlinear distributed MPC strategy; output constraints; process input; systematic account; valve limit; Automatic generation control; Frequency control; Mathematical model; Power systems; Predictive models; Valves; AGC; T-S model; distributed MPC;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2013 25th Chinese
  • Conference_Location
    Guiyang
  • Print_ISBN
    978-1-4673-5533-9
  • Type

    conf

  • DOI
    10.1109/CCDC.2013.6561637
  • Filename
    6561637