大型变速风力发电机组的自适应模糊控制

Adaptive Fuzzy Control for Large-scale Variable Speed Wind Turbines

控制技术是风力发电机组安全高效运行的关键。风力发电机组是复杂多变量非线性系统,具有不确定性和多干扰等特点。本文提出使用模糊逻辑推理系统得到低风速时的发电机参考转速,该方法无需测量风速,避免了风速测量的不精确性。根据机组的运动方程,采用最近邻聚类学习算法建立发电机电磁转矩自适应最优模糊控制,低风速时获得最大风能利用系数。算法综合考虑风力发电机组的机械特性和电气特性,系统辨识作为控制算法的一部分自动执行。高风速时,变论域自适应模糊控制器控制桨距角,机组能准确地保持在额定功率发电。仿真结果表明了本文提出方法的有效性。

Automatic control is crucial to the efficiency and reliability of wind power generating systems. Wind turbine systems have strong nonlinear multivariable with many uncertain factors and disturbances. A new method for estimating the optimal rotating speed at low wind speed is proposed by an application of fuzzy inference system. The method avoids the inaccuracy by measuring the wind speed. Based on the motion equation of wind turbine and generator, adaptive optimal fuzzy system for generator torque control is presented by using the algorithm of the nearest-neighbour clustering learning. The maximum wind energy performance coefficient is realized by this way at low wind speed. This algorithm synthesizes the mechanical and electrical characteristics. System identification is part of the controller. At high wind speed, pitch angle is adjusted to keep rated output power using adaptive fuzzy control based on variable universe. Simulation shows the effectiveness of the proposed methods.