大型风力机变桨系统前馈反馈复合控制仿真研究
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摘要
针对风力机系统的非线性和时滞特性,设计一种将预测前馈和反馈控制相结合的复合控制方法。根据电磁转矩和风轮转速,采用卡尔曼滤波器预测风轮气动转矩。根据气动转矩,采用牛顿拉夫逊算法估计有效风速,并以最小二乘法拟合风速和变桨角度的映射关系,得到前馈的变桨角度。采用粒子群算法优化PID控制器参数,得到反馈控制中的变桨角度。仿真结果表明,采用前馈反馈结合的方式,可以有效提高系统控制性能。通过Simulink仿真实验,不仅能够加深学生对理论知识的理解,而且能够提高学生的实践能力,这种理论加实践的方法,能够有效提高教学效果。
Due to the nonlinear and time-delay characteristics of the wind turbine system,a composite control method combining predictive feedforward with feedback control is designed. Firstly,the Kalman filter is adopted to predict the aerodynamic torque of the wind turbine according to the electromagnetic torque and the rotational speed of the wind wheel. And the Newton-Raphson algorithm is used to estimate the effective wind speed based on aerodynamic torque.Then the least square method is employed to fit the mapping relationship from the wind speed to pitch angle in order to obtain the feedforward angle. On the other hand,the particle swarm algorithm is used to optimize the parameters of the PID controller to obtain the pitch angle in the feedback control. The simulation results show that the system control performance can be effectively improved by combining feedforward with feedback. Using Simulink experiments can not only deepen students' understanding of theoretical knowledge,but also improve students' practical ability. The method includes theory and practice,and can effectively improve the teaching effect.
Due to the nonlinear and time-delay characteristics of the wind turbine system,a composite control method combining predictive feedforward with feedback control is designed. Firstly,the Kalman filter is adopted to predict the aerodynamic torque of the wind turbine according to the electromagnetic torque and the rotational speed of the wind wheel. And the Newton-Raphson algorithm is used to estimate the effective wind speed based on aerodynamic torque.Then the least square method is employed to fit the mapping relationship from the wind speed to pitch angle in order to obtain the feedforward angle. On the other hand,the particle swarm algorithm is used to optimize the parameters of the PID controller to obtain the pitch angle in the feedback control. The simulation results show that the system control performance can be effectively improved by combining feedforward with feedback. Using Simulink experiments can not only deepen students' understanding of theoretical knowledge,but also improve students' practical ability. The method includes theory and practice,and can effectively improve the teaching effect.
引文
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[10]王晓兰,唐慧敏,包广清,等.抑制载荷的风力机扰动前馈与预测反馈复合控制[J].电工技术学报,2016,31(2):230-235,251.
[11]何玉林,黄帅,杜静,等.基于前馈的风力发电机组变桨距控制[J].电力系统保护与控制,2012,40(3):15-20.
[12] Muhando E B,Senjyu T,Urasaki N,et al. Gain scheduling control of variable speed WTG under widely varying turbulence loading[J].Renewable Energy,2007,32:2407-2423.
[13]于树海,王建立,董磊,等.基于最小二乘法拟合估计傅里叶望远镜的缺失分量[J].光学精密工程,2015,23(1):282-287.
[14]程珩,张水明,权龙.基于约束主导混合粒子群算法的风力机叶片优化方法研究[J].机械工程学报,2015,51(1):176-181.
[2]何玉林,秦敏,谢双义,等.风力发电机组优化变桨距控制研究[J].中国电力,2013,46(3):19-23.
[3]郭鹏.模糊前馈与模糊PID结合的风力发电机组变桨距控制[J].中国电机工程学报,2010,30(8):123-128.
[4]秦斌,周浩,杜康,等.基于RBF网络的风电机组变桨距滑模控制[J].电工技术学报,2013,28(5):37-41.
[5]殷秀兴,林勇刚,李伟,等.基于电液行星锥齿马达的变桨距控制[J].浙江大学学报(工学版),2014,48(2):206-213.
[6]孙晓明,马青,曹虎,等.自适应模糊PID控制在PLC变频调速同步测试中的应用[J].实验室研究与探索,2014,33(6):16-18,64.
[7]俞海珍,史旭华,徐建瑜.模糊自适应PID控制在过程控制实验系统上的应用[J].实验技术与管理,2010,27(1):69-72.
[8]蒋鼎国.基于改进型BP神经网络PID控制器的温室温度控制技术[J].实验室研究与探索,2015,34(1):9-13.
[9]傅晓云,方旭,杨钢,等.基于遗传算法的PID控制器设计及仿真[J].华中科技大学学报(自然科学版),2012,40(5):1-5.
[10]王晓兰,唐慧敏,包广清,等.抑制载荷的风力机扰动前馈与预测反馈复合控制[J].电工技术学报,2016,31(2):230-235,251.
[11]何玉林,黄帅,杜静,等.基于前馈的风力发电机组变桨距控制[J].电力系统保护与控制,2012,40(3):15-20.
[12] Muhando E B,Senjyu T,Urasaki N,et al. Gain scheduling control of variable speed WTG under widely varying turbulence loading[J].Renewable Energy,2007,32:2407-2423.
[13]于树海,王建立,董磊,等.基于最小二乘法拟合估计傅里叶望远镜的缺失分量[J].光学精密工程,2015,23(1):282-287.
[14]程珩,张水明,权龙.基于约束主导混合粒子群算法的风力机叶片优化方法研究[J].机械工程学报,2015,51(1):176-181.