Energy, exergy, economic and enviro-economic analysis and artificial neural network modeling of an air-cooled PVT collector with NACA 8412 airfoils
K.N. Çerçi (TU Delft - Heat Transformation Technology, Tarsus University)
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Abstract
This study numerically investigates the performance of an air-cooled photovoltaic thermal (PVT) collector integrated with NACA 8412 airfoils arranged at various positions in both flow (y) and transverse (x) directions, an application not previously explored in the literature. Using the finite element method, the effects of geometric parameters and a range of operational conditions, including airflow characteristics and environmental inputs, were evaluated. Artificial neural network (ANN) models were also developed to predict outlet air temperature, cell temperature, and pressure drop. Favorable energy and exergy performance was achieved with airfoil spacing of 50–70 mm (y-direction) and 35 mm (x-direction). To limit fan power consumption, the inlet air velocity should not exceed 5 m/s. The collector achieved efficiencies of 8.71–9.23 % (electrical), 50.34–70.85 % (thermal), 73.30–93.77 % (primary energy saving), and 10.23–10.69 % (exergy). The electricity production cost ranged from 0.158 to 0.668 $/kWh, and the exergoeconomic parameter varied between 4.10 and 17.55 kWh/$. Annual CO2 mitigation reached up to 0.713 t (energy-based) and 0.275 t (exergy-based), depending on regional solar conditions. Two ANN model groups, one for single-output and one for multi-output predictions, were developed, both providing accurate and reliable results. This study offers a novel approach for enhancing and predicting PVT collector performance with airfoils.