Individual Pitch Learning Control Based on Support Vector Machine Weight Coefficient

Because of the random and irregular nature of wind speed, the output power generated by wind turbines can be unsteady in high-speed regions; thus, an entire wind turbine experiences unbalanced loads and wave vibration. To mitigate load fatigue and improve system performance, we propose an individual pitch control strategy for wind turbines based on an analysis of dynamic load models of wind turbine systems when operating at constant power combined with a support vector machine with weight coefficient control. We then developed an individual pitch control system mode for wind turbine systems with a permanent magnet synchronous generator and simulated it on an RT-LAB real-time simulation system. The simulation results show that the proposed control strategy ensures a stable power output, achieves a smooth regulation of the pitch angle, and reduces the unbalanced load as well as the fatigue and wear on components. Thus, the correctness and effectiveness of the proposed control strategy are verified.