Improvement of Power Output of the Wind Turbine by Pitch Angle Control Using RBF Neural Network

Abstract

In order to obtain maximum power output of wind turbine systems, it is necessary to control the wind turbine such as pitch angles and torques by several methods. In this paper, the radial basic function (RBF) neural network is used to control the variability of blade pitch angles. The controller will adjust the blade angles of wind turbine suiting with the variability of wind speeds. The controlled system can help to run the wind turbine very efficient and give the maximum power output. A simulation system for the Mitsubishi’s 2.4 MW wind turbine model has been developed in MATLAB® Simulink to estimate the power output while controlling the blade pitch angles reasonably changed with variable wind speeds. Simulation results indicated that the turbine is operating with maximum power output while the wind speed is higher than the norm value and the blade angle is increased to maintain the power output at 2.4 MW as well as the speed of the generator remains at 188.5 rad/s.