Modeling an‎d optimizing of a vertical axis wind turbine with helical blades

1/26/2027 12:00:00 AM

Vertical-axis wind turbines (VAWTs) with helical blades have attracted considerable attention for urban applications due to their independence from wind direction an‎d their low acoustic emissions. Despite advantages such as good self-starting capability an‎d relatively uniform performance, the optimization of this type of turbine has not yet been reported in the scientific literature, which constitutes the main novelty of this dissertation. In the present study, for the first time, three optimization methods—namely the Taguchi method, Response Surface Methodology (RSM), an‎d an Artificial Neural Network coupled with a Genetic Algorithm (ANN–GA)—are employed to optimize a three-bladed helical vertical-axis wind turbine. Each of these optimization techniques is independently coupled with three-dimensional Computational Fluid Dynamics (CFD) simulations to ensure an accurate an‎d reliable optimization process, representing additional novel contributions of this dissertation. The tip speed ratio, helical angle, an‎d airfoil chord length are selec‎ted as the design variables, while the average power coefficient of the helical vertical-axis wind turbine is considered as the objective function in all three optimization approaches. The optimal values of the airfoil chord length, helical angle, an‎d tip speed ratio obtained using the ANN–GA method are 0.42 m, 30°, an‎d 1.4, respectively. At this optimal point, the average power coefficient of the helical turbine reaches 0.185, which represents a 218% increase compared to the initial value of 0.058. Furthermore, the performance of the optimized three-bladed helical vertical-axis wind turbine is compared with that of a straight-bladed vertical-axis wind turbine under identical geometric an‎d operating conditions. The comparison under self-starting conditions reveals that the average torque coefficient of the helical vertical-axis wind turbine in steady-state operation is 22.03% higher than that of the straight-bladed vertical-axis wind turbine. Therefore, the three-bladed helical vertical-axis wind turbine demonstrates superior

توربين باد محورقائم با سه پره مارپيچ , ديناميك سيالات محاسبات سه بعدي , روش تاگوچي , روش سطح پاسخ , شبكه عصبي مصنوعي , الگوريتم ژنتيك , بهينه سازي

Vertical-Axis Wind Turbine with Three Helical Blades (VAWT-3-HB) , Three-Dimensional Computational Fluid Dynamics (3D CFD) , Taguchi Method , Response Surface Methodology (RSM) , Artificial Neural Network , Genetic Algorithm , Optimization

Armin Farvizi

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