Model-based optimization strategy for a liquid desiccant cooling and dehumidification system

In this paper, a model-based optimization strategy for a liquid desiccant cooling and dehumidification (LDCD) system is proposed to improve system energy efficiency. The energy models of the LDCD system are established to predict system energy consumption under different operating conditions. To minimize the system energy consumption while maintaining the system thermal performance, the system energy consumption and thermal performance indicators are normalized by introducing a weight factor in cost function, then an optimization problem considering the interactions between components and system constraints is formulated. An improved self-adaptive firefly algorithm with fast convergence rate is proposed to solve the optimization problem and obtain the optimal set-points for control settings. Tests on an experimental apparatus are carried out to verify the energy saving potential of optimal control strategy under different weight factors and operating conditions. The results indicate that the energy consumption of LDCD system in the proposed optimization strategy is reduced by 12.49% over the conventional strategy. Meanwhile, the energy saving potential of the optimal control strategy is more remarkable for high cooling and dehumidification load. The proposed optimal control strategy can work well for applications in control and energy efficiency improvement of the existing dehumidification systems. (C) 2019 Elsevier B.V. All rights reserved.