• DocumentCode
    184484
  • Title

    Decentralized identification of building models

  • Author

    Agbi, Clarence ; Krogh, Bruce

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA
  • fYear
    2014
  • fDate
    4-6 June 2014
  • Firstpage
    1070
  • Lastpage
    1075
  • Abstract
    As energy efficient model-based controllers gain acceptance in the building domain, the problem of identifying accurate building models for control becomes even more important. Current literature provides analysis on the identifiability of building models. However, in practice, building models can be too large and too complex to properly identify parameter estimates. Towards that end, we present a strategy to decompose large building models into smaller building zone models so that these zone models can be individually identified. We find that the identifiability of zone models imply the identifiability of the building model, and we outline a decentralized approach to identify large building models. Finally, we demonstrate this approach with a simulated building example.
  • Keywords
    buildings (structures); energy conservation; parameter estimation; building model identifiability; building zone models; controllers gain acceptance; decentralized identification; energy efficient model; parameter estimate identification; Analytical models; Atmospheric modeling; Buildings; Computational modeling; Partitioning algorithms; Temperature measurement; Thermal noise; Building and facility automation; Grey-box modeling; Identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2014
  • Conference_Location
    Portland, OR
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4799-3272-6
  • Type

    conf

  • DOI
    10.1109/ACC.2014.6859128
  • Filename
    6859128