Abstract

This paper presents a multi-objective optimization of a biomass heating-based two-stage desiccant-supported greenhouse cooling system used for Orchids cultivation in hot and humid weather conditions. The simulation model has been developed considering thermodynamics, economic, and environmental aspects. The thermal coefficient of performance (COPth) of the system and greenhouse temperature have been predicted for the five most impactful months (March, May, August, September, and December) corresponding to the respective seasons of spring, summer, monsoon, autumn, and winter of a calendar year. The system maintains the peak average greenhouse temperature at a maximum of 26 °C during the prominent sunshine period (12 h) in May while ensuring a minimum of 18 °C during nighttime. In terms of system components, the residue boiler stands out as the significant contributor to exergy destruction (45%), followed by regeneration heater 1 (22%), desiccant wheel 1 (7%), and the heat recovery water heater (6%) during the critical operational month of August. Multi-objective optimization has also been conducted using the optimization toolbox provided in matlab-R2017a to determine the optimal performance and operating conditions of the two-stage desiccant cooling system. The optimal conditions display the corresponding total cost rate, considering capital and maintenance costs, operating costs, CO2 penalty costs, and exergetic efficiency.

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