Open AccessPitch angle control using neural network in wind turbines
Author(s) -
Ahmed Harb Najd,
Goksu Gorel,
Husam Faisal Hammood
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/928/2/022118
Subject(s) - blade pitch , pitch angle , wind power , pitch control , turbine , angle of attack , artificial neural network , controller (irrigation) , wind speed , chord (peer to peer) , matlab , renewable energy , computer science , aerodynamics , control theory (sociology) , engineering , marine engineering , aerospace engineering , control (management) , electrical engineering , meteorology , geology , physics , artificial intelligence , agronomy , distributed computing , geophysics , biology , operating system
Wind energy is a growing renewable energy resource. Wind power can be improved or restricted by adjusting the pitch angles of the wind turbine blade. The wind turbine model is non-linear. Therefore, a smart controller must be designed to adjust the angles of the blade. In this study, the simulated and code method was with the MatLab program to control the angle between the chord line of the blade and incoming wind direction using a type of the neural network (NN) control. The results from the simulation show that the NN proposed controller is very effective for adjusting the pitch angles.