Research On Pitch Angle Control Strategy Of Wind Turbine Blade Distance Based On Learning Control

With the advantages of high conversion efficiency and flexible control,variable pitch wind turbine has become the main development direction of wind power generation.However,with the development of large-scale wind turbines,there is a higher requirement for the effect of variable propeller control.Not only the randomness of the changes in wind speed direction and intensity in the wind field will cause trouble to the wind power generation system,the increase of the tower height and blade length,the wind shear and the tower shadow effect brought by the change of the overhang distance,the troubles are becoming more and more not to be ignored.Aiming at the research problem of pitch control of wind turbines,the following research is done in this paper:This paper analyzes the operation principle of wind turbines and further studies the variable pitch control technology.A large-scale variable-pitch wind turbine model was established to discuss the control of pitch angle,and the role of PID controller in variable pitch control was analyzed.The traditional PID controller is simulated and analyzed.The results show that in the pitch control system,the traditional PID control effect is not ideal.In order to weaken the periodic disturbances caused by wind shear and tower shadow effects on wind turbines,an improved iterative learning control algorithm was designed using the repetitive characteristics of the system operation and the advantages of iterative learning control in dealing with repetitive motions.Aiming at open-loop P-type,closed-loop D-type learning law and open-closed PD-type learning law,the algorithm design is proposed,the convergence proof is given and the convergence conditions are given.Compared with the traditional algorithm,this algorithm can not only achieve the stability and fast tracking of the system,but also solve the problem of uncertain system model,so that the wind turbine has better dynamic performance when the wind speed changes.Simulation experiments illustrate the theoretical feasibility of the algorithm.