Exploring the use of TABS and Peak-Shift Control in Office Buildings

Thermally activated building systems (TABS) are gaining attention as a means of realizing comfort and energy efficiency in office spaces. TABS use the building mass for heat dissipation and the storage part of the building to save energy, improve comfort, and shift peak energy consumption. However, the thermal response is slow due to the large thermal capacity. Therefore, in this study, we propose a method for optimizing the operation of TABS by applying Adaptive Model Predictive Control (AMPC) combined with sequential updating of the predictive model through online estimation. Furthermore, we verify the feasibility of Demand-Response (DR) implementation using the proposed method. From the results, AMPC was shown to reduce the control error compared to MPC and to reduce computational load compared to Nonlinear MPC (NLMPC). We also confirmed that DR control using AMPC can suppress TABS operation during the hours of 8:00 - 10:00 and 16:00 - 18:00 when electricity demand is high, while maintaining PMV within ±0.3 and ensuring energy efficiency.