Multi-Objective Optimization of Energy Saving and Thermal Comfort in Thermo Active Building System based on Model Predictive Control

Japan will have to further reduce CO2 emissions to meet its obligations under the Paris Agreement negotiated at the 2015 United Nations Climate Change Conference. Society is increasingly demanding higher energy-efficiency standards and zero-energy buildings because general commercial buildings have high energy costs, especially for air conditioning. Furthermore, it is just as important to consider the productivity of the people working in these buildings; therefore, there is an urgent need for air-conditioning systems and control methods that are both energy efficient and provide thermal comfort. Radiant heating and cooling has been introduced in Japan in recent years. This is a means of creating an indoor thermal environment that balances energy efficiency and comfort in the office. A thermo-active building system (TABS) is an example of an advanced radiant heating and cooling system. TABS utilizes the building frame, which is mainly concrete slab, to store and radiate heat. Compared with a conventional radiant system, TABS offers higher energy efficiency, a more comfortable environment for workers, and cost advantages. ON/OFF or PID controls are commonly used to control conventional air conditioning; however, to optimize air-conditioning control, it is essential to include load prediction because the thermal response of the ceiling surface temperature is slow due to the ceiling’s large thermal mass. The problem is that either energy consumption increases or thermal comfort decreases in cases where these controls are applied to TABS. In a previous study, we proposed using model predictive control (MPC), which takes into consideration thermal response, as a way of optimizing the control of TABS in an existing office building that also had an outdoor air processing unit. We verified the effectiveness of MPC by performing a coupled analysis using MATLAB/Simulink and CFD as a single-objective optimization method for optimizing thermal comfort; however, energy consumption was not considered in this previous study. Therefore, in the present study, we conducted a fundamental examination of multi-objective optimization of thermal comfort and energy efficiency by performing numerical simulations using MATLAB/Simulink. As the result this study suggests that it is possible to reduce the water flow rate of TABS while maintaining comfort by performing multi-objective optimization. A reduction effect of up to 68.3% was obtained in comparison with reference case.