考虑非线性不确定因素的风电机组多目标优化控制

MULTI-OBJECTIVE OPTIMIZATION CONTROL OF WIND TURBINE CONSIDERING NONLINEAR AND UNCERTAIN FACTORS

针对功率和载荷两个优化目标设计基于卡尔曼滤波器的线性二次型高斯最优控制器。该控制器将系统的非线性因素和不确定性因素归结为系统噪声,通过卡尔曼滤波器进行实时估计,根据估计的系统状态计算控制器的动态最优增益,以适应系统工作点的变化,增强控制器的鲁棒性。以3 WM双馈风电机组为研究对象的仿真分析结果表明,与传统PID控制器相比,本文设计的控制器不仅保证了最大风能捕获,抑制了风电机组的功率波动,同时还明显减小了齿轮箱的转矩波动,从而提高了机组输出电能的质量、降低了齿轮箱等关键部件的载荷。

Aiming at two optimization objectives-power and load, the linear quadratic Gaussian optimal controller was designed based on Kalman filter. Nonlinear and uncertain factors of the system were attributed to system noise in the controller, calculating the dynamic optimal to the changes of the system operating po gain of the controller according to real-time estimate of Kalman filter to adapt int, and enhance the robustness of the controller. A 3 MW doubly-fed wind turbine was taken as the control object in the simulation, the results indicate that the designed controller not only can ensure the maximum capture of wind energy, but also improve the quality of wind turbines＇ output power and reduce the fatigue load of gearbox, thus reduce the load of gearbox and other key load.