Online Energy Management Framework for Smart Buildings With Low-Complexity Estimators

Abstract

This letter proposes an online energy management framework for smart buildings. Two low-complexity estimators for thermal comfort and electrical load are investigated and integrated into an optimization framework. The proposed framework optimizes operations of a battery system and multiple heating, ventilation, and air conditioning (HVAC) systems to minimize energy consumption and power peak while maximizing occupants' thermal comfort. The effectiveness of the proposed framework is demonstrated using data measured in actual campus buildings in terms of system costs, thermal comfort, and computational complexity. The results show that the proposed framework can reduce electricity costs by 5.7% compared to the baseline.