Shape Optimization of Wind Turbine Airfoils by Genetic Algorithm

Abstract

Wind Turbine airfoil was optimized by a new genetic method so that its performance increases. A new method was proposed to optimize thin airfoils for use in wind turbine rotors. It is a common practice in the classic methods based on the genetic algorithms for airfoil shape optimizations, to use the computational fluid dynamics solvers. The main disadvantage of this method is the considerable running time for these algorithms. This disadvantage was significantly reduced by using the new technique. Comparing the results of the proposed algorithm with the classic ones approves its higher performance and lower computation time. Another advantage of this method is the reduced number of the design variables needed for optimization by inverse design method. The proposed modifications on the genetic algorithm offer a higher performance wind turbine blades faster than classic algorithms simplicity. However, the classical direct approaches mostly perform a local search. The inverse approach The inverse approach is far more powerful since the designer has much more precise control over the final performance of the airfoil. However, while every airfoil shape produces a particular set of performance characteristics, not every set of performance characteristics can be used to generate a realistic airfoil shape. The designer must be aware of what is practical, the trade-offs required between different types of performance, and physical constraints. As a tradeoffs required between the different types of performance, and physical constraints. Consequently, classical design and optimizing methods mainly adopt trial and error approach and strongly rely on designer's future experience rather than the current needs. A global optimization method based on genetic algorithm or intelligent genetic algorithm is expected to shorten and simplify the iterative design process and improve the design output. A similar approach has been previously used for aerodynamic optimization of turbo machinery cascades (1), and very good results were obtained. Glaurt (2) neglected the drag of airfoil and offered a popular theory for optimizing the airfoil. This theory was further developed by Stewart (3) and improved by Miller (4). Wilson (5) offered a method base on calculating sensitivity of flow field parameters.