Abstract:
Space ventilation with dehumidified cool outdoor air is essential to dilute the indoor
generated species to within their healthy thresholds and maintain breathable indoor air
quality (IAQ) in built environments. Using conventional vapor-compression cooling for
outdoor air dehumidification is energy intensive, especially in hot and humid regions.
To reduce this energy consumption, desiccant dehumidification wheels and packed beds
are integrated with the air conditioning systems. However, these systems result in large
pressure drops requiring larger parasitic power consumption and require external
heating sources for regeneration. In this study, a two-stage direct solar-regenerated
desiccant dehumidification rotating belt (SR-DDRB) system is proposed. The aim is to
investigate the performance of the SR-DDRB in sustainably dehumidifying the outdoor
air while meeting the indoor humidity levels at enhanced IAQ and at minimal energy
consumption in hot and humid climates. Mathematical models were developed for the
SR-DDRB and validated experimentally. An artificial neural network was trained using
the validated SR-DDRB model to reduce the computational time of the optimization
process of the genetic algorithm. The system was sized, and its operation was optimized
for a case study of a typical office space located in hot and humid climate.
Over the entire cooling season, the proposed system operating at its optimal conditions,
was able to meet an indoor RH of 58 ± 1.5%. The system maintained the CO2
concentration of 780 ± 41 ppm, well below the allowable 1,000 ppm limit set by
ASHRAE with a total energy consumption of 26 kWh over its entire cooling season.
