Multi-Objective Optimization of Performance of a Solar Air Heater With Fin and Baffle and Recycle Using Genetic Algorithm

Present work focuses on energy and exergy performance and parameter optimization of a solar air heater integrated with fins, baffles and external recycle. Theoretical analysis has been considered to study the effect of geometrical and operating parameters on effective and exergy efficiency of SAH. Energy and exergy balance equations have been solved by developed code using MATLAB. Further, Genetic algorithm has been invoked to optimize the design and operating parameters of SAH. The distance between the fins (number of fins), the width and the distance between the baffles and the recyle ratio are the parameters whose optimal values were obtained for different values of Reynolds numbers and solar radiation with the aim of achieving maximum energy and exergy efficiency. It was found that the use of fins and baffles under external recycle in a flat solar air heater improved thermal efficiency in all cases. However, at higher air flows, the additional power required to overcome the pressure drop may impair the performance of the SAH. The best effective and exergy efficiency for various Re are respectively 64.15% and 6.34% which obtaind for I=1200 W/m2. Simulations results of present model has been validated with models available in the literature and found to be in good agreement.