Power Adaptive And Robust Tracking Control Of Wind Farm Based On Neural Networks

The development technology in all aspects of wind energy is very rapid,and the effective energy usage is focus of modern control researches.With the increasing scale of wind power grid connection,wind farm power control becomes the key technology for stable operation.This paper is on the output power tracking control methods of wind farm.Besides stochastic fluctuations of the wind speed,adjacent wind turbines dynamic coupling and influence is also considered,and then the wind farm model is established and coordinated control method is also discussed.Moreover,this paper also considers the practical problem that almost existing schemes ignored,that is about uncertainty and unpredictability of user side power demand,which is transformed into an unknown ideal power curve,and corresponding solutions are proposed.This idea not only has the significance of theoretical innovation,but also has important practical value.Considering complex nonlinear dynamics characteristics and unknown ideal power trajectory,this article designs two power tracking controllers below rated wind speed to control the output power of wind farm.By adjusting the output power of each turbine,the total output power is adjusted to ensure steady output power tracking of wind farm.The major contents can be summarized as follows:Firstly,the research background of the wind power project is stated.Then the distributed power control scheme of wind farm is proposed,and the power characteristics of wind turbine are introduced and wind turbine mathematical model is established,and then the dynamic model of wind farm is established.In addition,unknown ideal power trajectory is considered,which is a practical problem that almost existing schemes ignored.This brings challenge to design effective power tracking controllers later.Then,the neuroadaptive tracking control strategy is proposed,and then is modified based on a Barrier Lyapunov Function.The stability of control algorithms are analyzed and verified by selecting the appropriate Lyapunov function.Another control method is proposed,that is robust adaptive tracking controller.The stability of the developed controller is analyzed by Lyapunov stability theory.The two controllers are computationally inexpensive and structurally simple and have simple structure,and its proportional parameters can be self-learning and modified online.Lastly,the control effect in power tracking is verified by Simulink software,which ensures the output power stable tracking of wind farm.