Design of parabolic dish and parabolic trough collector systems and modeling of experimental results using artificial intelligence methods

This study focuses on the design, theoretical analysis, experimental testing, and performance modeling through artificial intelligence methods of concentrated solar power (CSP) systems—specifically parabolic trough collector (PTC) and parabolic dish collector (PDC) systems—were conducted and comparatively evaluated. Within the scope of the research, the mechanical designs, electronic control units, sun-tracking algorithms, optical reflectors, and receiver systems of both PTC and PDC were comprehensively developed. Theoretical analyses focused on energy balance equations and heat transfer mechanisms, thoroughly examining the factors influencing the efficiency and performance of the systems. For the PTC system, the effects of different receiver tube diameters (10 mm, 20 mm, 30 mm) and mass flow rates (0.01 kg/s, 0.02 kg/s, 0.03 kg/s) on thermal performance were investigated. ANSYS simulations demonstrated that optimum performance was achieved with a 20 mm receiver tube diameter at a mass flow rate of 0.02 kg/s. In the case of the PDC system, three different receiver designs (conical spiral, cavity tube, and non-cavity tube) were compared, and the conical spiral receiver was found to provide higher thermal efficiency. In the final stage, the experimental data were modeled using artificial intelligence techniques. The model outputs were validated through comparison with similar studies in the literature. The findings of this study provide a valuable reference for the design and optimization processes of solar energy systems, while also paving the way for further research on evaluating the performance of similar systems under diverse geographical and environmental conditions. In this context, studies supported by economic analyses are expected to reveal the large-scale application potential of such systems.