• DocumentCode
    3259765
  • Title

    An energy saving model predictive control for central air-conditioning system

  • Author

    Wu, Zhangxian ; Yang, Guotian ; Liu, Xiangjie ; Sheng, Xing ; Song, Pengchuan

  • Author_Institution
    Dept. of Autom., North China Electr. Power Univ., Beijing, China
  • fYear
    2009
  • fDate
    23-26 Jan. 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper, a model predictive control method is proposed to improve the performance on both temperature control and energy conservation for central air-conditioning system. Since the lack of consideration of the impact of cooling load can lead to a limitation on the energy saving effect, a cooling load model is proposed. Parameters in cooling load model, as well as the temperature model and energy consumption model are estimated. The optimal predictive controller is designed, and a chance constrained programming method is utilized to solve the optimal problem with stochastic parameters. Through a solution algorithm based on genetic algorithm, the control vector which can keep optimal in most uncertain cases can be acquired. The comparative results show the effectiveness of the proposed method.
  • Keywords
    air conditioning; control system synthesis; energy conservation; genetic algorithms; predictive control; temperature control; central air conditioning system; chance constrained programming method; cooling load model; energy conservation; energy saving model predictive control; genetic algorithm; stochastic parameters; temperature control; Central air conditioning; Cooling; Energy conservation; Energy consumption; Load modeling; Optimal control; Predictive control; Predictive models; Stochastic processes; Temperature control; Energy conversation; Model predictive control; chance constrained programming; cooling load;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    TENCON 2009 - 2009 IEEE Region 10 Conference
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-4546-2
  • Electronic_ISBN
    978-1-4244-4547-9
  • Type

    conf

  • DOI
    10.1109/TENCON.2009.5396223
  • Filename
    5396223