基于PSO与模糊PI控制结合的最大风能捕获研究

MAXIMUM WIND ENERGY CAPTURE BASED ON PSO AND FUZZY PI CONTROL

针对风速突变引起风力机转速、转矩、功率等跟踪效果差问题,提出一种基于粒子群优化算法和模糊PI转矩控制器方法。根据低风速、高风速下风力机产生的功率是否达到额定功率,将风力发电机的运行区域划分为低负荷和满负荷。在低负荷区控制发电机最优转矩控制,保持最佳叶尖比运行能较好地跟踪功率,实现风能的最大捕获。将该策略应用于一个5 MW风力机模型中,并与前馈空气转矩(ATF)和传统模糊控制(CMPPT)两种策略比较。仿真结果表明,该策略在低风速情况下能很好地跟踪风速,实现最大风能的捕获。

Aiming at the poor tracking effect of wind turbine speed,torque and power caused by sudden change of wind speed,we proposed a method based on particle swarm optimization(PSO)and fuzzy PI torque controller.The operating area of wind turbine was divided into low load and full load according to whether the power generated by wind turbines under low wind speed and high wind speed reached the rated power.In the low load area,the optimal torque of the generator was controlled,and the optimal blade tip ratio was maintained to track the power better,so as to achieve the maximum capture of wind energy.We applied the method into a 5 MW wind turbine model,and compared it with feed forward air torque control(ATF)and CMPPT.The simulation results show that the strategy can track the wind speed well in low wind speed and achieve maximum wind capture.