Intelligential method optimization for improve heat transfer in solar hybrid collector

In order to enhance the efficiency of photovoltaic panels, it is imperative to maintain a low temperature for the photovoltaic module. A recent study delved into this matter, utilizing Response Surface Methodology (RSM) and Multi-objective Genetic Algorithm (MOGA) to optimize the design of the solar system. This was done by examining various parameters, such as the gap, velocity, and solar system temperature. ANSYS software and Navier Stokes equations were used for simulations. The research findings revealed that an optimal gap size of approximately 3 cm was the most effective, with only slight variations in energy gain observed. This highlights the importance of maintaining specific design parameters to ensure optimal performance of solar systems.