基于粒子群优化的无载荷传感器风电机组独立变桨距控制

PSO-based Individual Pitch Control for Wind Turbines Without Load Sensor

提出一种利用预测载荷进行独立变桨距控制的方法,应用叶素理论进行载荷预测,对测量风速以及受风剪效应和塔影效应影响的轮毂风速进行修正,使载荷计算更加准确;应用粒子群算法进行桨距角优化控制,优化搜索中通过对目标函数的选取和相关参数的设定保证控制的实时性.应用Bladed软件对某1.5MW变桨距风电机组进行仿真.结果表明:所提出的独立变桨距控制方法可在保证功率控制的同时实现载荷控制,能有效减小风轮不均衡载荷,降低机组疲劳载荷.

An individual pitch control(IPC)approach for wind turbines without load sensor was proposed based on loads pridicted by blade element theory.To make the load calculation more accurate,corrections were made to the measured wind speed and the hub wind speed affected by wind shear and tower shadow.The pitch angle was then controlled by partical swarm optimization(PSO)according to previous load prediction,and the real-time control was achieved by selecting the objective function and setting relevant parameters in optimization search.Simulations were made to a 1.5MW variable pitch wind turbine by Bladed software.Results show that the proposed individual pitch control strategy helps to not only guarantee power control objectives,but also realize load control purposes,which can simultaneously reduce both the load imbalance of wind wheel and the fatigue load of wind turbines.