Research On Drive Chain System Control Of Offshore Wind Turbine Based On Predicted Of Wind Speed

Wind energy,as one of the cleanest renewable energy sources,is developing rapidly in the background of realizing sustainable energy security strategy,and it has become a trend for wind turbines to be develop into large-scale,intelligent and from land to sea.The wind turbine drive shaft is the structure of wind turbine energy transmission,and the effective control of it is an important guarantee to reduce the torsional load of the transmission system and enhance the structural safety of the wind turbine.It is great of significance to improve the output power of wind turbine,increase the economic benefits of wind power and promote the efficient utilization of wind energy.However,affected by the harsh environment of the offshore wind field,the wind speed has the special characteristics of strong randomness,instability and high volatility,which is an important reason for the resonance of wind turbine transmission system.Therefore,in order to accurately predict the wind speed and realize the load reduction control of the wind turbine drive chain system,the vibration control research of the wind power generation system based on wind speed prediction propose in this paper has certain practical value for its engineering application.Firstly,the formation process of wind energy,the characteristics of wind speed and wind energy,the influence of unstable wind speed on wind speed prediction and wind turbine system are introduced;In addition,the basic theory of wind turbine dynamics and the operating state of wind turbine are analyzed in detail,and on this basis,the dynamic model of the wind turbine drive chain system is established;Combined with the factors of affecting the vibration of the wind turbine drive chain system,the vibration reduction and load reduction control strategy of the drive chain system is analyzed in detail.Secondly,in view of the problem that the accuracy of wind speed prediction,a hybrid method is proposed to predict the special wind speed with the added down burst wind speed.In order to reduce the influence of the high volatility and other particularities of the original wind speed data on the prediction accuracy,complete ensemble empirical mode decomposition with adaptive noise method is designed to decompose the originalwind speed data according to different fluctuation scales;Then,the extreme learning machine algorithm optimized by the particle swarm optimization algorithm with strong generalization ability,easy parameter adjustment and small prediction error is designed to predict the decomposed sequence;Finally,the set of corresponding prediction results is taken as the final wind speed prediction result by applying the set principle,and the simulation results verify the effectiveness of the hybrid method.Finally,in view of the vibration problem of the wind turbine drive shaft system caused by unstable wind speed and the problem that the actuator may produce voltage over-saturation and damage the whole wind power system in engineering application,the tracking differentiator is designed to arrange the transient process to avoid the output overshoot caused by excessive initial tracking error;The extended state observer is designed to estimate the strong non-linear and “total disturbance” in real time and compensates it into the error feedback controller to avoid adverse effects on the system;Actuator saturation is used to protect the entire system from over-saturation of the generator.Finally,based on the predicted wind speed data,the superiority of the control scheme is demonstrated by simulation.