Online management framework for building HVAC systems considering peak shaving and thermal comfort

Abstract

In this study, an online management framework for building HVAC (Heating, Ventilation, and Air-Conditioning) systems, which achieves peak shaving and thermal comfort improvement, has been designed and studied experimentally. We formulate a model predictive control (MPC) problem for the HVAC control, of which the objective is to minimize the electricity costs and demand peak and maximize thermal comfort. A thermal equivalent circuit model (TECM) was developed to describe the target room's thermal behavior. The TECM is experimentally validated under different ambient temperatures, heat/cooling loads, and occupations. The temperature responses obtained from TECM have a good agreement with observations, and the maximum deviation is below 8%. The online management framework of the HVAC system was developed based on TECM, which includes a monitoring system based on HVAC built-in sensor and embedded technology and a real-time HVAC system control module based on the MPC problem. The performance of the proposed framework with different operating conditions was investigated in the actual room. The results show that the HVAC systems using this framework can achieve better room temperature control and a further improvement in energy efficiency.