Optimal control method for flexible loads in thermally activated buildings
DOI:
https://doi.org/10.18686/cest334Keywords:
TABS; building energy flexibility; model predictive control; thermal inertia; multi-objective optimizationAbstract
As the penetration of renewable energy in the energy system continues to rise, the intermittency and stochasticity of energy supply have become increasingly significant, posing challenges to the dynamic coordination between energy supply and demand. Building thermal mass, with its inherent heat capacity, offers substantial energy storage potential, presenting a cost-effective alternative to traditional active energy storage methods. The activation and precise control of flexible energy from the building's thermal mass, has become a critical area of research. In this paper, based on a case floor-type thermally activated building system (TABS), the methods and constraints of simulating the energy flexibility potential on the demand side of the building were analyzed. By developing model predictive control (MPC) strategies, including white-box MPC, grey-box MPC, and black-box MPC, this study compared and assessed the control performance in terms of room temperature, accumulated energy cost, and the utilization efficiency of energy flexibility. Compared with the traditional rule-based control method, the MPCs showed better performance in room-temperature control, operation economics, and efficiency of flexible-load utilization, effectively saving energy costs by up to 20% and improving flexibility utilization by nearly 40%. Moreover, based on the performance comparison of the MPCs, white-box MPC performed optimally in terms of room-temperature control, while grey-box MPC was more effective in reducing energy costs and improving energy flexibility. The findings of this paper can provide theoretical insight for the efficient utilization of energy flexibility from building thermal mass and the selection of control methods.
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Copyright (c) 2025 Xiaochen Yang, Ruizhi Wang, Zhenya Zhang, Ping Wang, Dingzhou Liu, Yixuan Jiang
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