A new artificial neural network–power law model for vertical wind speed extrapolation for improving wind resource assessment

This work is intended as a contribution toward a possible harmonization of methods and techniques, aimed at extrapolating wind speed for wind energy purposes. Through the years, different methods have been used to this end, such as power law which is used in many studies and softwares worldwide. Wind shear coefficient cannot be fixed at one value. It has been found that wind shear coefficient varies with parameters such as time of day, season, nature of the terrain, wind speed, temperature, and various thermal and mechanical mixing. This article uses an artificial neural network approach to generate the wind shear coefficient for a given site. The outputs of the models are compared with the real measured data. The results show a good accuracy