Title :
Decentralized identification of building models
Author :
Agbi, Clarence ; Krogh, Bruce
Author_Institution :
Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA
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;
Conference_Titel :
American Control Conference (ACC), 2014
Conference_Location :
Portland, OR
Print_ISBN :
978-1-4799-3272-6
DOI :
10.1109/ACC.2014.6859128