Improving the power coefficient of the Darrieus vertical axis wind turbine with the aid of morphing airfoils

With the advent of smart materials in recent years, the aviation industry and airfoils have undergone many changes. Research into the use of smart materials in aircraft wings to increase their performance and then the use of smart materials in wind turbine airfoils has begun. In this study, computational fluid dynamics and URANS equations for a three-bladed Darrieus wind turbine equipped with a morphing airfoil was used to determine the optimum blade cross-section. 250 airfoils were generated by random control points, in Gambit software, they were unstructured and generated as a sliding mesh then they were simulated in 2D Ansys using the k-ω SST turbulence model and PISO algorithm. Control points and power coefficient were used for Artificial Neural Network (ANN)training and the Genetic Algorithm(GA) was used to optimize the power coefficient. In this study, the base airfoil is NACA0015. The results of that have been very effective. For the first case (Determine the optimal cross-section of the turbine at a full round) the power coefficient of Darrieus wind turbine with the optimal cross-section increased by 42%, and the blade section(airfoil) was also drawn. For the second case(Determine the optimal cross-section in each of the four zones of the rotor), the most efficient sections(airfoils) in four-zone were obtained, increasing the turbine power coefficient by 60% was the result of this optimization.