Power enhancement of vertical axis wind turbine using optimum trapped vortex cavity

Abstract

Vertical Axis Wind Turbine (VAWT) blades experience stall conditions at lower tip speed ratios during rotation, resulting in inefficient power performance. The power performance can be augmented by improving the blade's aerodynamic efficiency using active or/and passive flow control mechanisms. In this research, the power performance of 2-D H-type VAWT is enhanced by employing an optimum cavity on the suction side of the NACA 0018 blade airfoil. The optimum cavity shape was found using the Genetic Algorithm coupled with the Gaussian Process Regression (GPR) model at an airfoil static stall angle of attack in an isolated environment to reduce the computational cost of the optimization process. Two GPR models were employed to predict lift and drag coefficients, while the lift-to-drag ratio was used as an objective function in the optimization algorithm. 80 CFD runs were utilized for initial training and testing of the models, which reduced computational effort by 97% compared to a pure CFD-based optimization approach. The aerodynamic efficiency of the optimum cavity shape predicted by GPR models was also confirmed by CFD simulation, which showed only a 0.5% difference. For an airfoil with an optimum cavity, the aerodynamic efficiency was consistent at lower angles of attack. However, a significant rise of up to 31.8% was observed in the near stall region between 12° to 16° angle of attack in comparison to clean airfoil. The optimum cavity on baseline VAWT blades enhanced power performance by 63.8% at a TSR of 1.5. Moreover, at TSRs of 2, 2.5, 3, and 3.5, the enhancement in power performance was achieved by 34.4%, 22.2%, 16.1%, and 3.2%, respectively. This demonstrates the potential of employing an optimum cavity on the suction side for performance augmentation without applying the suction and a cost-effective solution by conducting optimization in an isolated environment.