Abstract
An automatic design environment is implemented for the aerodynamic design of wind turbine blades. This tool involves the integration of evolutionary techniques and a simple, fast, and robust aerodynamic simulator which was developed for the prediction of the performance of any turbine blade produced by the evolutionary process. The aerodynamic simulator is based on blade element theory in which a panel method is combined with an integral boundary layer code to calculate the blade airfoils’ characteristics. In order to reduce computations some simplifications have been applied and the results corrected by means of the application of neural network based approximations. Results of the simulations obtained using this technique, of the application of the automatic design procedure and of the operation of the wind turbines thus obtained are presented.
Highlights
To obtain efficient wind turbine blades that lead to acceptable economical performance of the turbines during their lifetime involves a complex aerodynamic design process
This paper proposes an approach to carry out this task by means of evolutionary techniques within an automatic design environment
The aerodynamic simulator is based on blade element theory in which an airfoil analysis method based on potential theory is combined with an integral boundary layer code in order to calculate the aerodynamic characteristics of blade airfoils when accounting for viscous effects
Summary
To obtain efficient wind turbine blades that lead to acceptable economical performance of the turbines during their lifetime involves a complex aerodynamic design process. This paper proposes an approach to carry out this task by means of evolutionary techniques within an automatic design environment. For this purpose, a simple, fast, and robust aerodynamic simulator has been developed and embedded within a design environment. In order to reduce computational cost, some simplifications are contemplated in the airfoil performance estimation and the results corrected by means of the application of neural network based approximations. The evolutionary design environment approximation to the design problem is based on work carried out by other authors in the application of evolution for the design and optimization of different types of systems in other realms. Examples of applications in this line are described by Kirsch and Rozvany for the structural optimization of bridges and transmission towers [1], by Keane et al [2], Song et al [3] or Ong et al [4] in airplane and airfoil design optimization
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