This paper introduces a state-of-the-art modelling technique to investigate the performance of solar assisted dehumidification and regeneration cycles. The dehumidification/regeneration system investigated in this study employs a solid adsorbent bed and enables use of both solar energy and returning warm air to deliver efficient dehumidification and regeneration of the treated air. Study of literature revealed a huge gap between model results and industrial performance of such systems. Hence, the modelling work presented in this paper employs Gaussian Process Regression (GPR) technique to close the gap between model outputs and real-life operation parameters of the system. An extensive amount of laboratory tests were also carried out on the dehumidification/regeneration system and model predictions were validated through comparison with experimental results. The model predictions were found to be in good agreement with experimental results, with maximum error not exceeding 10%.
The GPR technique enables simultaneous analysis of a vast quantity of key system parameters derived from mathematical models and laboratory tests. The system parameters investigated in this study include: temperature, relative humidity and flow rate of process air, and temperature of regeneration air, solar radiation intensity, operating time, moisture extraction efficiency of the dehumidification cycle and moisture removal efficiency of the regeneration cycle. Investigation of both modelling and experimental results revealed that efficiencies of the both dehumidification and regeneration cycles decrease as relative humidity of the process air increases. The increase in regeneration temperature leads to an increase in regeneration efficiency whereas; it does not have a significant impact on the dehumidification efficiency. A similar trend was also observed when solar intensity were increased.
The proposed technique reduced the complexity of model by eliminating the need for heat and mass transfer calculations; reduced the performance gap between model results and real-life performance data, and increased the reliability of model outputs by showing a good agreement with experimental results. The GPR based mathematical model delivers an effective design and performance evaluation tool for the solar assisted dehumidification and regeneration systems and provides an unprecedented opportunity for commercializing such systems.