• DocumentCode
    176184
  • Title

    Modeling research on ground-coupled heat pump system based on artificial neural network

  • Author

    Yating Zhang ; Weichang Jiang ; Ruihua Wang

  • Author_Institution
    Coll. of Elctronic & Control Eng., Beijing Univ. of Technol., Beijing, China
  • fYear
    2014
  • fDate
    May 31 2014-June 2 2014
  • Firstpage
    2320
  • Lastpage
    2323
  • Abstract
    As a new technology of renewable energy, ground-coupled heat pump system has been rising in our country in recently years. However because of the nonlinear and high degree of coupling, it is not clear to find out the relationship between control variables and total energy consumption of the system. This paper proposes a modeling way for ground-coupled heat pump system that uses artificial neural network, it builds the relationship between control variables and total energy consumption of the system directly. Through the comparison we can find a better way for building the Ground-coupled heat pump System.
  • Keywords
    ground source heat pumps; neurocontrollers; renewable energy sources; artificial neural network; control variables; energy consumption; ground coupled heat pump system; renewable energy source; Artificial neural networks; Atmospheric modeling; Educational institutions; Energy consumption; Heat engines; Heat pumps; BP neural network; LM algorithm; RBF neural network; ground-coupled heat pump system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (2014 CCDC), The 26th Chinese
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4799-3707-3
  • Type

    conf

  • DOI
    10.1109/CCDC.2014.6852559
  • Filename
    6852559