A site-specific design of a fixed-pitch fixed-speed wind turbine blade for energy optimization using surrogate models

This work seeks to add a new approach to optimize a wind turbine blade's performance by implementing a surrogate model using the Kriging function with the chord, twist and the use of 3 different airfoils as design variables for the maximization of the Annual Energy Production. A combination of Genetic Algorithms and the SQP method for Local Search are used to exploit the model. A baseline design of the blade starts with a replica of the Phase VI blade utilized in a NASA-Ames experiment and a MatLab script utilizes the Blade Element Momentum Theory (BEM) for the aerodynamic analysis. Results show a 23% improvement in energy production by using this method.