A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Building models for model predictive control of office buildings with concrete core activation
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.
Building models for model predictive control of office buildings with concrete core activation
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.
Building models for model predictive control of office buildings with concrete core activation
Sourbron, Maarten (author) / Verhelst, Clara (author) / Helsen, Lieve (author)
Journal of Building Performance Simulation ; 6 ; 175-198
2013-05-01
24 pages
Article (Journal)
Electronic Resource
English
Building type basics for office buildings
| UB Braunschweig | 2002
Office buildings -- Building type study 318
Engineering Index Backfile | 1963
Building type basics for office buildings
| TIBKAT | 2002