Wind turbine feedback linearization power control method based on radial basis function neural network

Abstract

The invention provides a large-size wind turbine feedback linearization power control method based on a radial basis function (RBF) neural network, and relates to the field of wind turbine power control. The control method comprises the steps that 1, on the basis that a wind turbine state space is built, an affine nonlinear model of a variation paddle controller is put forward, and the feedback linearization control law is designed; 2, an affine nonlinear model of a torque controller is built, and the feedback control law is designed; 3, on the basis of analyzing blade force vibration and tower vibration, the threshold value definition of a dual-loop controller is put forward for serving as the basis of controller transformation; and 4, the RBF neural network is designed to serve as a compensation control method for controlling errors. According to the dual-loop controller based on feedback linearization provided by the invention, the constant power control problems that the wind speed change is large, small, and fast after the rated wind speed is exceeded can be solved, the control precision is also improved through error compensation, and the robust performance of the system is improved.

Description

technical field [0001] The invention belongs to the technical field of wind turbine constant power control, in particular to a feedback linearization constant power control method based on RBF radial basis neural network, Background technique [0002] When the wind speed exceeds the rated value, it is necessary to control the output power of the wind turbine, which is usually carried out by using the aerodynamic characteristics of the blades to control the stall or adjust the pitch angle of the blades. With the development of variable speed technology, for large wind turbines, not only the power can be adjusted by changing the pitch angle, but also the power output can be changed by adjusting the electromagnetic torque. [0003] Due to the complexity of the wind turbine system, which has the characteristics of time delay and nonlinearity, the modeling and control algorithm based on the wind turbine system is a research hotspot. Feedback linearization control is simple in st...

AI Technical Summary

Problems solved by technology

When the wind speed exceeds the rated value, if the range of change is large, it is difficult to adjust the speed only by directly controlling the electromagnetic torque, and then achieve constant power control.

When the wind speed exceeds the rated value and changes rapidly, the real-time and accuracy of pitch control cannot meet the system requirements.

In addition, because the structure and parameters of the wind turbine system are difficult to accurately determine, the model will produce deviations, and the compensation of system errors is also a problem worth studying.

Images