" Building Energy Management Using Model-Based Predictive Control: Energy Modeling and Optimal Control

The heat and moisture transfer in the building envelope significantly affects indoor climate and overall thermal performance. This work presents a Building Energy Analysis Model (BEAM) that predicts heat and moisture transfer throughout a building. The coupled model accounts for key hygrothermal effects in buildings and is implemented in MATLAB, verified against EnergyPlus. BEAM is then reduced through a model order reduction process to create a lower-order system, Re-BEAM, which is computationally efficient and compatible with control algorithms.Using Re-BEAM, a Model-Based Predictive Control (MBPC) method is developed to incorporate essential building data into control algorithms, optimizing energy consumption while maintaining comfort levels. The optimal setpoint schedules generated by the MBPC can be applied to various HVAC systems.Simulation results show that the proposed method outperforms traditional constant control strategies and occupant-dependent temperature schedules, providing significant reductions in both energy use and peak load. This approach offers a more efficient and adaptive way to control building systems, improving energy efficiency and comfort.

" Building Energy Management Using Model-Based Predictive Control: Energy Modeling and Optimal Control Keywords:

Building energy model , energy efficiency , thermal model , hygrothermal model , model-based control