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
Link To Document