Pitch Angle Control for Variable Speed Wind Turbine Using Particle Swarm Optimization Based Fuzzy Logic Controller

Abstract

Electricity is a basic demand, especially for developing countries where the scarcity of electricity exist. To allow people all over the world to use electricity, many possibilities need to be used, such as the promotion of wind energy and other energy sources that maintain the greenhouse effect. In today's energy system, wind power is developing gradually and, as we all know, it is the cleanest source of energy and has the least impact on the environment. The use of wind energy is difficult because its production is not linear, especially when the wind speed is higher than the rated speed. When the wind speed surpasses the rated speed, this thesis study provides the steadiness of the generator output power and the robustness of the proposed controller by controlling the pitch angle method. A complete mathematical model of the system's components is constructed to analyze the pitch angle control of a wind turbine. The controllers applied in this thesis are PID controller, fuzzy logic controller, and PSO-based fuzzy logic controllers. For implementation purposes, the relevant models are developed using the MATLAB/Simulink software tool. The maximum pitch angle obtained by the controllers; the PID controller is 14.8 degrees, the fuzzy logic controller is 12.5 degrees, and the PSO Fuzzy controller is 12 degrees. The pitch angle deviates from 0 degrees to avoid the distraction of the wind turbine by turning away from the wind. As the pitch angle increases, the power coefficient decreases and causes the power drawn from the wind to decrease. As the power drawn from wind is decreased, the mechanical torque transmitted to the drive train will also decrease due to the ratio of the mechanical power divided by the rotor speed. This effect will reduce the stability of the output power of the generator during high wind speed. The rotational speed overshoot of the PID is MP 18.6167%, FLC is MP 18.214%, and PSO-FLC is MP 13.05% improved. The settling time of the PID is 310.5113second, FLC is 310.606second, and PSO-FLC is 309.234second. The rise time of the PID response is 8.7473second, FLC is 8.701second, and PSO-FLC is 8.1965second. The highest overshoot generator output power with PID controller reaches around 1.625MW which is 0.13% above the rated power, Fuzzy logic controller is 1.573MW (0.05%), and PSO-based fuzzy logic controller is 1.531MW (0.03%). In general PSO-based fuzzy logic controller shows better performance and better stability of the output power compared to other controllers used in this thesis work.