A Research on Image Quality Assessment Based Wind Turbine Blade Control Algorithm

Abstract Blade control is one of the core technologies of wind turbines. Research on blade control algorithms of wind turbines has important theoretical and practical values. Due to the randomness and unbalance of the wind speed, the output power of the wind turbine unit in the high wind speed sections is easily fluctuated, and unbalance loads such as the swinging vibration is brought to the entire wind turbine. In order to reduce the fatigue load and improve the system performance, we combine the deep learning techniques with weight coefficient control, and propose an independent blade control strategy based on both the blade image quality and the analysis of the load dynamic model in the constant power operation area of the wind power generation system. We build a control system model for permanent magnet direct drive wind power generation system and conducted simulation experiments on MATLAB platform. The simulation results show that the proposed method achieves stable power output as well as smooth adjustment of blade angles.