engleski

Hierarchical model predictive control of temperature in building zones

Buildings belong to the large energy consumers class and account for 40% of worldwide primary energy consumption. Application of advanced control, fault detection and diagnosis algorithms in buildings has been intensively investigated with the aim to improve their energy efficiency and bring the buildings sector into the smart city arena. In the thesis, a general methodology for minimizing thermal energy consumption using current energy sources and minimal retrofitting through the use of advanced identification and control techniques is presented. The proposed modelling, identification and control algorithms are validated via simulation studies and on-line implementation of the model predictive control for zone temperature control on a real 248-zones skyscraper building. The developed frameworks pave the way to fast deployment of model-based energy management strategies in buildings and unleash significant energy and cost-saving potentials of a smart building in a smart city.

Building energy management system ; Zone comfort control ; Model predictive control ; Energy efficiency ; Comfort-savings trade-off ; Building thermal model ; Constrained unscented Kalman filter ; Identification ; Semiphysical modelling ; Control-oriented fan coil unit model ; Hydraulic and thermodynamic modelling

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