Research On Nonlinear Model Predictive Control Method Of Large Wind Turbines

With the increasingly serious problem of global environmental pollution and the intensification of energy crisis,the country has put forward the development demand of energy strategy "carbon peak and carbon neutralization".In this context,in order to improve the power generation performance advantages of large-scale wind turbines and reduce the impact of unbalanced aerodynamic torque on component loads,wind turbines are upgraded in the direction of intelligence,and traditional controllers are difficult to meet the development needs of the industry.Model predictive control is considered to be the most ideal advanced control method of large-scale wind turbine which can fuse lidar wind measurement information.However,due to the strong nonlinearity and large inertia of large-scale wind turbine,it is difficult to be directly applied.Therefore,this paper makes a more in-depth application research on the nonlinear model predictive control method of large-scale wind turbine.The main work includes:(1)Using the traditional way to solve the control problem of nonlinear system,a model predictive control method of wind turbine based on multi operating point linearization is proposed.Small signal analysis is used to linearize the wind turbine at multiple operating points,and the overall affine model of wind turbine suitable for model predictive control is obtained.Then,from the three aspects of output prediction,cost function and constraints,the model predictive control problem is transformed into a simple quadratic programming problem with constraints.The simulation results show that the control performance of this method is significantly better than the reference PI method at high wind speed,but the influence of modeling error on the controller design is more serious at low wind speed,so its control performance still needs to be improved.(2)In order to solve the problem of limited improvement of control performance under low wind speed caused by low modeling accuracy of traditional working point linearization method,a nonlinear model predictive control method of wind turbine based on discrete long-period framework is proposed.The nonlinear model of large-scale wind turbine is directly established,on this basis,the discrete long-period nonlinear predictive control framework is constructed,and the solution algorithm suitable for the framework is explored.In this paper,two different solutions are proposed: one is to reduce the scope of the optimization solution by discretization and obtain the approximate solution of the nonconvex optimization problem by enumeration method;The second way is to use intelligent optimization algorithm.The simulation results show that the above method has better control performance than the working point linearization method.(3)In order to combine the advantages of linear model predictive control and nonlinear model predictive control,a linear model predictive control method of nonlinear wind turbine based on Koopman operator is proposed.The nonlinear wind turbine system is promoted to an infinite dimensional linear system by Koopman operator,and the finite dimensional approximation of the operator is obtained by using the extended dynamic mode decomposition method,so that the wind turbine model approximation has the form of linear system,which is convenient to control the wind turbine by using the linear model predictive control method.This method has the advantages of simple calculation and easy implementation.The simulation results show that this method has better control performance than the working point linearization method.