Airfoils Optimization Design of Vertical Axis Wind Turbine Based on Kriging Surrogate Model and MIGA

The airfoil optimization of vertical axis wind turbine (VAWT) often encounters challenges such as high computational costs and long convergence times, especially in the analysis of complex aerodynamic characteristics. When using the Computational Fluid Dynamics (CFD) method for optimization design, the computational workload is usually enormous, making it difficult to efficiently handle many design variables and complex aerodynamic parameters. In this paper, a design configuration with three blades, a chord length of 0.42 m, and a rotation radius of 1.4 m is adopted as the basis for optimization using the surrogate model. Subsequently, an optimization design is carried out through the proposed Kriging surrogate model in combination with the Multi - Island Genetic Algorithm (MIGA). The Kriging surrogate method for airfoil optimization significantly enhances the aerodynamic performance of the wind turbine. Particularly at high tip - speed ratios, its power coefficient is increased by 14.2%, which validates the effectiveness of this method in the optimization design of wind turbines. Meanwhile, this optimization strategy improves the aerodynamic performance of VAWT, enabling them to achieve better energy conversion efficiency under a wider range of operating conditions.