Application of model-based control strategy to hybrid free cooling system with latent heat thermal energy storage for TBSs

Abstract

This paper explored the application of model predictive control (MPC) technology to the TBSs hybrid free cooling system with latent heat thermal energy storage (LHTES) unit for minimizing the building operational cost without sacrificing temperature requirements. First, the system was briefly introduced and the dynamic thermal process models of building structure and LHTES unit were developed. Then, a hierarchical control structure with dynamic multi-swarm particle swarm optimization was presented to address the dimensional challenge and discontinuities in control variables. Due to the considerable decrease of optimization variable space, the method presented in this paper enables long-term simulation and application in a real controller. Simulations were carried out based on a typical TBS building located in Beijing, China. The total energy consumption of the cooling system and the control quality of indoor air temperature were used as the criteria to evaluate the performance. Compared to a defined baseline case, the optimal control method can achieve significant energy saving, i.e. up to 18%. The impacts of the size of LHTES unit and the type of building structure were discussed, as well. The active and passive heat capacity both played a catalytic role in performance of MPC. Additionally, an uncertainty analysis demonstrated that the proposed approach has strong robustness and can handle quite high errors in forecasting building disturbances from energy consumption level. In summary, the knowledge and use of the plant system and future disturbances make MPC a powerful control tool for TBS buildings for maximizing the use of renewable energy sources.