DEVELOPMENT AND PERFORMANCE EVALUATION OF A SOLAR POWERED ADSORPTION REFRIGERATION SYSTEM

Student: Femi Timothy Apata
Supervisor: Dr Modupe Atinuke Oluleye
HOD: Prof Taiwo Oni
Department of Mechanical Engineering
Engineering
Ekiti State University, Ado-Ekiti, Ekiti State

Abstract

This study reports the design, construction, and performance assessment of a solar-powered adsorption refrigeration system employing an activated carbon–methanol working pair. The increasing need for sustainable and energy-efficient cooling solutions, especially in rural and off-grid communities, has intensified interest in refrigeration systems driven by renewable energy sources. The developed system operates on intermittent adsorption–desorption cycles powered by solar thermal energy. It was designed, fabricated, and experimentally tested through continuous monitoring of hourly temperature variations across major system components, namely the collector bed, condenser, and evaporator. Experimental results showed that the collector bed reached temperatures exceeding 100 °C during the desorption phase, ensuring effective methanol desorption. The condenser temperatures remained within acceptable ambient ranges, while the evaporator achieved sufficiently low temperatures during the adsorption phase, confirming satisfactory cooling performance. The system’s coefficient of performance (COP) was determined using the recorded thermal data, yielding an average value of approximately 0.29, which reflects improved efficiency relative to conventional adsorption refrigeration systems using similar working pairs. Overall, the findings indicate that the developed solar-powered adsorption refrigeration system is efficient, environmentally benign, and well-suited for low-energy cooling applications. The study concludes that solar adsorption refrigeration is a practical and reliable alternative to conventional refrigeration technologies, particularly in regions with high solar availability and limited electricity access, and holds strong potential for further optimization and large-scale application.

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