Advanced Pitch Angle Control Based on Genetic Algorithm and Particle Swarm Optimisation on FAST Turbine Systems

Abstract

In this paper, the increase in the quality of the rotor speed of wind turbines and the decrease in mechanical loads on the turbines are investigated. Adjusting the angle of the blade to the nominal wind speed, the rotor speed of the wind turbine is maintained at its nominal value. Using control methods (such as proportional integral (PI), genetic algorithms (GAs), and particle swarm optimisation (PSO)), different results can be recovered. In addition, individual control of the blade tilt angle allows us to reduce the mechanical loads on the turbine with the control methods. The wind turbine was modelled in Matlab/Simulink. The simulation results show that individual control of the blade tilt angle ensures the quality of the rotor speed of the wind turbine and reduces the balanced periodic loads on the wind turbine. In the first part, we study the wind turbine in a global way, as well as the method used to calculate them. Then, we discuss the FAST system, which was used to model the wind turbine, as well as the design of individual pitch angle control. As a result, it is possible to reduce the fatigue of the mechanical wind turbine parts. According to the study, the mechanical load for all three blades was reduced by an average of 44 % compared to the PI and PSO methods and by 1 % compared to the PI and GA methods. The control of the pitch angle in wind energy systems is performed with different control methods. The study analysis of the mechanical loads found that they are largely balanced. Winds that blow perpendicular to the turbine blades on the x-axis provide these loads.

Keywords

• wind power generation
• genetic algorithms
• particle swarm optimisation
• pi control
• fast system