Design of Wind Turbine Torque Controller with Second‑Order Integral Sliding Mode Based on VGWO Algorithm

基于VGWO算法的风力机二阶积分滑模转矩控制器设计

A robust control strategy using the second-order integral sliding mode control(SOISMC)based on the variable speed grey wolf optimization(VGWO)is proposed.The aim is to maximize the wind power extraction of wind turbine.Firstly,according to the uncertainty model of wind turbine,a SOISMC torque controller with fast convergence speed,strong robustness and effective chattering reduction is designed,which ensures that the torque controller can effectively track the reference speed.Secondly,given the strong local search ability of the grey wolf optimization(GWO)and the fast convergence speed and strong global search ability of the particle swarm optimization(PSO),the speed component of PSO is introduced into GWO,and VGWO with fast convergence speed,high solution accuracy and strong global search ability is used to optimize the parameters of wind turbine torque controller.Finally,the simulation is implemented based on Simulink/SimPowerSystem.The results demonstrate the effectiveness of the proposed strategy under both external disturbance and model uncertainty.

提出了一种基于变速灰狼优化算法(Variable speed grey wolf optimization,VGWO)的二阶积分滑模(Second-order integral sliding mode control,SOISMC)鲁棒控制策略。该策略的目的是实现风力机的最大风能捕获,提高风力机的发电量。首先,根据风力机的不确定性模型,设计了一种收敛速度快、鲁棒性强且能有效抑制抖振的二阶积分滑模转矩控制器,保证了转矩控制器能够有效地跟踪参考转速。其次,考虑到灰狼优化算法(Grey wolf optimization,GWO)具有较强的局部搜索能力和粒子群优化算法(Particle swarm optimization,PSO)具有较快的收敛速度和较强的全局搜索能力,将PSO的速度分量引入GWO中,使改进的VGWO具有较快的收敛速度、较高的求解精度和较强的全局搜索能力。然后,利用VGWO对风力机转矩控制器的参数进行优化。最后,在Simulink/SimPowerSystem平台上进行了仿真,结果表明了该策略在存在外部干扰和模型不确定性情况下的有效性。