Performance enhancement of small-scale wind turbine based on artificial neural network

Abstract

Small-scale wind turbine is typically designed to resisted extreme wind; this work aims to adjust their pitch angle based on simulations that use standardization codes for wind turbines. Proportional integral derivative (PID) and artificial neural network (ANN) controllers are used to control the speed of wind turbines. The ideal action for controlling the blade pitch angle can be attained by providing the controller with speed information ahead of time, allowing the controller to provide the best action for blade pitch angle control. The results of this work represent the relationship between the turbine speed with respect to time at different pitch angle. It has been concluded that the ANN controller produced the best time response as compared with the PID controller.