Enhanced wind turbine blade design for improved power output and reduced noise

Abstract

Current wind turbine optimization studies primarily employ either the Blade Element Method (BEM) or Computational Fluid Dynamics (CFD) to evaluate rotor aerodynamic performance. While BEM remains widely used due to its simplicity and low computational cost, it depends heavily on empirical correction factors that can limit its accuracy in complex flow conditions. Conversely, although CFD provides highly accurate results by solving the Navier-Stokes equations, it is computationally expensive and often impractical for large-scale parametric studies. Vortex methods—particularly the prescribed wake method—offer a promising compromise, balancing computational efficiency with acceptable levels of accuracy. In the present study, we propose a novel wind turbine blade model derived through a multi-objective optimization of the blade's geometric parameters, specifically chord distribution and twist angle. The aerodynamic performance of the optimized blade is evaluated using an enhanced prescribed wake model. Aerodynamic noise is estimated using Brooks’ empirical method, while the blade production cost is calculated using Zudong’s cost model. The resulting blade design demonstrates a 3% increase in power output, a 0.02 dB reduction in noise emissions, and a marginal 1.2% increase in production cost. These findings suggest that moderate improvements in performance and environmental impact can be achieved through geometry-based optimization without substantial cost penalties.