Journal
JOURNAL OF BUILDING PERFORMANCE SIMULATION
Volume 6, Issue 3, Pages 175-198Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/19401493.2012.680497
Keywords
concrete core activation (CCA); model predictive control (MPC); controller building model; parameter estimation; office building
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Funding
- Institute for the Promotion of Innovation through Science and Technology in Flanders (IWT-Vlaanderen)
- European ERANET-EraSME-GEOTABS project
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Model predictive control (MPC) is a good candidate to exploit the energy cost savings potential of concrete core activation (CCA), while guaranteeing thermal comfort. A bottleneck for practical implementation is the selection and identification of the building control model. Using grey box models, this article studies the impact of model structure and identification data set on the MPC control performance for an office building with CCA. Results for a one-year simulation show: (1) a second-order model can achieve equal control performance as a fourth-order one, (2) inclusion of solar or internal gains in the identification data set improves the model accuracy in general, especially for the fourth-order models and (3) MPC with a second-order model reduces electricity consumption by 15% compared to a reference controller, hereby deploying information about past operative temperature prediction errors and this without the need for solar or internal gains predictions.
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