Design optimization of a wind turbine using artificial intelligence

This chapter examines the capability of Support Vector Machine (SVM), Relevance Vector Machine (RVM) and Genetic Programming (GP) for the optimal design of wind turbine. The excellent design has been influenced by various factors, such as profile of the blade, number of blades, power factor and tip speed ratio. The key to design a wind turbine is to Assessing the optimal tip speed ratio (TSR) is the key for designing the wind turbine. This chapter handles the Artificial Intelligence techniques in predicting the optimal TSR and the power factor based on the parameters engaged for NACA 4415 and LS-1 profile types with 3 and 4 blades. The organized machine learning framework is anticipated to be lucrative than the traditional way in foretelling the TSR and power factor. The machine learning models are then compared with the existing Neural Network model and the pros and cons of the various models are inferred from the results. © 2017 by IGI Global. All rights reserved.