In recent years, the airfoil sections with blunt trailing edge (called flatback airfoils) have been proposed for the inboard regions of large wind‐turbine blades because they provide several structural and aerodynamic performance advantages. The purpose of this paper is to optimize the shape of these airfoils for optimal performance using a multi‐objective genetic algorithm.
A multi‐objective genetic algorithm is employed for shape optimization of flatback airfoils to achieve two objectives, namely the generation of maximum lift as well as the maximum lift to drag ratio. The commercially available software FLUENT is employed for calculation of the flow field using the Reynolds‐Averaged Navier‐Stokes (RANS) equations in conjunction with a two‐equation Shear Stress Transport (SST) turbulence model and a three‐equation k‐kl‐ω turbulence model.
It is shown that the multi‐objective genetic algorithm based optimization can generate superior flatback airfoils compared to those obtained by using a single objective genetic algorithm.
The method of employing genetic algorithms for shape optimization of flatback airfoils could be considered as an excellent example for the optimization of other types of wind turbine blades such as DU FX and S series airfoils.
This paper is the first to employ the multi‐objective genetic algorithm for shape optimization of flatback airfoils for wind‐turbine blades to achieve superior performance.
