A refined dynamic liquid dehumidification model for the packed dehumidifier considering time-varying thermal mass of the desiccant

Liquid desiccant dehumidification technology is a promising, energy-efficient dehumidification approach. It can flexibly adapt to variations in renewable energy supply and users' demands, making it an inherently dynamic process. However, optimizing this process from a dynamic perspective is often neglected. This is mainly due to the challenges in establishing a dynamic dehumidification model, where the desiccant's thermal mass and heat and mass transfer coefficients should be time-dependent. In this paper, a refined dynamic dehumidification framework using the finite difference method is developed, where governing equations for the mass and species conservations are rebuilt taking the thermal mass and desiccant concentration as time- dependent variables. Auxiliary equations determining evolutions of the desiccant's thermal mass and heat and mass transfer coefficients are derived based on the continuity equation and analogy method, respectively. Subsequently, the experiments are carried out and serve as a benchmark to check the simulations. It suggests the simulated results using the refined model align well with the experimental data and demonstrate around 50 % better predictive accuracy compared to the existing method, indicating the feasibility of the refined model. The refined model also contributes to rapid adaptation of the dehumidification process to meet specific needs. In a specific case, this could result in energy savings of 60 % for the regeneration of the desiccant solution. This study provides a reference for quantifying evolutions of the liquid desiccant's thermal mass based on an understanding of the physical process. It lays a solid foundation for modeling the dynamic dehumidification process at the design stage and assists in operating an energy-saving dehumidification system.