变速风力发电机组最大风能追踪与桨距控制

针对变速变桨风力发电机组(Variable Speed Variable Pitch,VSVP)如何在低风速时最大限度捕获风能以及在额定风速以上稳定输出功率进行研究。低风速时在传统风能追踪控制策略的基础上,提出通过改变最优增益系数来追踪最佳风能利用系数的自适应转矩控制策略。在额定风速以上,依据风机空气动力学原理、风轮扫及面内风速风切特性,提出基于桨叶方位角信号的独立变桨距控制策略。该策略通过权系数将统一变化的桨距角转化为3桨叶独立变化的桨距角。以国产某2 MW风力发电机组为验证对象,基于Bladed软件平台对所采用的控制策略进行仿真验证。结果表明,相对传统控制,所提出的控制策略在低风速时能够更好的追踪最大功率点。额定风速以上时,使风力发电机组能够在额定转速下保持稳定的电功率输出。     

变桨距风电机组仿真模型与控制

针对变桨距风力发电机组,建立了包含风、空气动力、发电机、偏航系统以及桨距系统的模型,并对变桨距风力发电机组模型设计了控制逻辑和控制回路.偏航和变桨是影响发电机组功率的主要因素,在偏航模型和控制系统中充分考虑了偏航角的解缆问题以及风向突变时风机偏转方向的算法设计;在变桨模型和控制系统中,根据叶片的气动特性,进行了仿真.控制结果表明,设计的仿真模型和控制方案能够合理地展现变桨距风电机组的动态变化过程.     

风机变桨距非线性预测控制算法

变桨控制技术是MW级大型变速变桨风力发电机组的核心控制技术之一,通过变桨控制可以保证风电机组输出功率恒定在额定功率附近.由于风轮的强非线性特性,采用常规的PID控制器往往面临参数难以设计以及参数缺乏自整定能力的问题.提出了基于遗传算法的变桨距非线性预测控制器设计方法,根据优化和反馈校正的预测控制思想,针对风轮非线性控制对象设计了一种基于智能搜索方法的带约束的非线性预测控制算法进行仿真.仿真结果表明算法对非线性对象控制中具有很好的约束预测控制性能.与传统PI算法相比,具有响应快速、超调小、抗干扰能力好的特点,并通过优化算法滚动局部寻优,减少了设计的工作量和提高了设计效率.     

风力机变桨距控制策略研究

作为目前大型风力发电机组中应用最广泛的控制技术之一,变桨距控制在风速高于额定风速时,可以有效提高系统效率以及输出功率的稳定性。然而,风力发电机系统的复杂性、非线性以及空气动力学的时变性对变桨距控制产生影响。因此,变桨距系统的控制策略成为了风力发电技术的关键。对变桨距控制的工作方式以及关键性问题进行了研究,针对风电机变桨距系统的非线性、多变量、强耦合和时变性等特点,总结归纳了变桨距系统控制策略的研究现状,分析了不同控制策略的优缺点。最后,对变桨距系统控制技术的发展趋势进行了分析。     

风电机组电动变桨距控制系统的优化研究

由于风速的随机性、不稳定性及气动效应的影响,使得风力发电机组变桨距控制系统具有非线性、参数时变性、强耦合等特点,难于实现高精度控制,导致风电机组输出电能质量较差。为了改善系统在恒功率输出运行区域内的动态性能,分析了风电机组变桨距控制系统的现状,建立了整个风电机组模型,提出了优化的变桨距控制策略,并设计了基于模糊控制的变桨距控制器。仿真结果表明,独立变桨距控制技术的控制效果比统一变桨距好,实现了风力机各叶片的优化独立变桨距控制,优化了风力发电系统在超过额定风速时的恒功率控制,具有抗干扰能力强、控制精度高的特点。     

兆瓦级风力发电机组变桨距系统

以ECSxA系列变桨变频器为硬件平台,以非线性PID变桨控制算法为核心,设计了一种新的兆瓦级风力发电机组变桨距系统.通过软硬件的设计,较理想地实现了变桨距系统的电气控制,在实际应用中获得了良好的控制效果,实现了兆瓦级风力发电机组变桨距系统的自主开发.     

变桨距风力发电机组恒功率反馈线性化控制

在额定风速以上时,为保证风电机组的安全稳定运行,需要降低风力机捕获风能,使风力机的转速及功率维持在额定值,基于微分几何反馈线性化方法,提出变桨距风力发电机组恒功率控制策略.建立了风力机的仿射非线性模型,采用微分几何反馈线性化变换实现全局精确线性化;根据新的线性化模型,以风力机转速为输出反馈变量,叶片桨距角为输入控制变量,设计桨距角控制器;在风速高于额定值时调节风力机维持在额定转速,从而实现额定风速以上的恒功率控制.仿真结果表明,所提控制策略能较好地解决变桨距风力发电机组额定风速以上的恒功率控制问题,控制方法具有较好的适应性和鲁棒性.     

风力发电系统独立变桨距载荷优化控制研究

对风力发电系统独立变桨距控制原理进行阐述。建立了风力发电机组桨叶载荷的数学模型,利用Coleman坐标变换实现了将桨叶上的载荷转换成轮毂处倾斜方向和偏航方向的疲劳载荷,并且实现了二者的解耦,简化了控制器的设计;之后利用Coleman逆变换实现了桨距角的微调。该控制系统根据随机风速的变化,利用独立变桨控制对风力机桨叶桨距角进行实时调节,以达到减小风电机组关键部件载荷的目的。仿真结果表明,当风速达到额定值以上时,该控制策略在统一变桨距控制的基础上,不仅保证输出功率近似相等,而且减小了桨叶所承受的疲劳载荷,也减小了风力机组其他关键部件的疲劳载荷。     

基于方位角权系数分配的独立变桨距控制

风力发电机组功率不断提升,风机桨叶随之增大,风机在额定风速以上运行时,桨叶所受气动载荷逐渐增大,为风机安全运行埋下了隐患,因此希望减小这一载荷。针对这一问题,在充分分析风电机组结构及其运行规律的基础上,依据空气动力学原理,提出了一种基于桨叶方位角权系数分配的独立变桨距控制方法。同时,针对风机输出功率要求稳定的目标,设计了一种模糊-PID控制器。仿真结果表明,风机在高于额定风速以上运行时,这种模糊-PID控制下,基于桨叶方位角权系数分配的独立变桨距控制策略,可以改善风机输出功率并有效地减小桨叶气动载荷。     

风力发电机组的变桨距复合控制

针对变桨距风力发电机组的强非线性和时滞特性,受参数变化和外部干扰严重,提出了基于前馈补偿和模糊PID的复合控制策略来实现变桨距功率控制.将模糊控制与常规的PID控制相结合,设计了模糊自整定PID控制器对控制参数进行在线调整.考虑风速是一个可测的主要扰动,设计了前馈补偿器,采用分段比例控制补偿一个适当的前馈桨距角,在额定风速以上时作用于系统,实现按扰动的快速补偿.变桨距控制系统采用S7-1200PLC作控制器,编写程序实现了变桨距复合控制.试验表明,系统抗扰能力强,控制效果良好.     

Intelligent control for large-scale variable speed variable pitch wind turbines

Large-scale wind turbine generator systems have strong nonlinear multivariable characteristics with many uncertain factors and disturbances. Automatic control is crucial for the efficiency and reliability of wind turbines. On the basis of simplified and proper model of variable speed variable pitch wind turbines, the effective wind speed is estimated using extended Kalman filter. Intelligent control schemes proposed in the paper mchde two loops which operate in synchronism with each other. At below-rated wind speed, the inner loop adopts adaptive fuzzy control based on variable universe for generator torque regulation to realize maximum wind energy capture. At above-rated wind speed, a controller based on least square support vector machine is proposed to adjust pitch angle and keep rated output power. The simulation shows the effectiveness of the intelligent control.     

An observer-based blade-pitch controller of wind turbines in high wind speeds

The paper focuses on variable-rotor-speed/variable-blade-pitch wind turbines operating in the region of high wind speeds, where blade pitch and generator torque controllers are aimed at limiting the turbine's energy capture to the rated power value. Coupled design is described of an observer-based blade-pitch control input and a generator torque controller, both of which not requiring the availability of wind speed measurements. Closed loop convergence of the overall control system is proved. The proposed control solution has been validated on a 5-MW three-blade wind turbine using the National Renewable Energy Laboratory (NREL) wind turbine simulator FAST (Fatigue, Aerodynamics, Structures, and Turbulence) code.     

基于微分几何的风力发电机组恒功率控制

当风速超过额定值时, 可以通过降低风力机的转速实现恒功率控制从而避免使用复杂的变桨距机构, 本文基于微分几何理论设计了非线性控制器, 实现了变速风力发电机组的恒功率控制. 首先, 分析了风力机的空气动力学特性, 这是所提出的恒功率控制方法的理论依据; 然后, 通过微分几何反馈线性化变换, 将风力机的非线性模型全局线性化; 最后, 基于新的线性化模型设计了非线性控制器, 实现了变速风力机的全局精确线性化控制. 仿真结果表明, 所提出的控制方法在风速大范围变化的情况下能有效的实现变速风力发电机组额定风速以上的恒功率控制.     

Design of adaptive robust guaranteed cost controller for wind power generator

According to the increasing requirement of the wind energy utilization and the dynamic stability in the variable speed variable pitch wind power generation system, a linear parameter varying (LPV) system model is established and a new adaptive robust guaranteed cost controller (AGCC) is proposed in this paper. First, the uncertain parameters of the system are estimated by using the adaptive method, then the estimated uncertain parameters and robust guaranteed cost control method are used to design a state feedback controller. The controller’s feedback gain is obtained by solving a set of linear matrix inequality (LMI) constraints, such that the controller can meet a quadratic performance evaluation criterion. The simulation results show that we can realize the goal of maximum wind energy capture in low wind speed by the optimal torque control and constant power control in high wind speed by variable pitch control with good dynamic characteristics, robustness and the ability of suppressing disturbance.     

Feedforward Control for Wind Turbine Load Reduction with Pseudo-LIDAR Measurement

A gain-scheduled feedforward controller, based on pseudo-LIDAR (light detection and ranging) wind speed measurement, is designed to augment the baseline feedback controller for wind turbine’s load reduction in above rated operation. The pseudo-LIDAR measurement data are generated from a commercial software – Bladed using a designed sampling strategy. The nonlinear wind turbine model has been simplified and linearised at a set of equilibrium operating points. The feedforward controller is firstly developed based on a linearised model at an above rated wind speed, and then expanded to the full above rated operational envelope by employing gain scheduling strategy. The combined feedforward and baseline feedback control is simulated on a 5 MW industrial wind turbine model. Simulation studies demonstrate that the proposed control strategy can improve the rotor and tower load reduction performance for large wind turbines.     

Adaptive back-stepping pitch angle control for wind turbine based on a new electro-hydraulic pitch system

A new electro-hydraulic pitch system is proposed to smooth the output power and drive-train torque fluctuations for wind turbine. This new pitch system employs a servo-valve-controlled hydraulic motor to enhance pitch control performances. This pitch system is represented by a state-space model with parametric uncertainties and nonlinearities. An adaptive back-stepping pitch angle controller is synthesised based on this state-space model to accurately achieve the desired pitch angle control regardless of such uncertainties and nonlinearities. This pitch angle controller includes a back-stepping procedure and an adaption law to deal with such uncertainties and nonlinearities and hence to improve the final pitch control performances. The proposed pitch system and the designed pitch angle controller have been validated for achievable and efficient power and torque regulation performances by comparative experimental results under various operating conditions.     

Robust Wind Speed Estimation and Control of Variable Speed Wind Turbines

In this work, a robust control scheme for variable speed wind turbine system that incorporates a doubly feed induction generator is described. The sliding mode controller is designed in order to track the optimum wind turbine speed value that produces the maximum power extraction for different wind speed values. A robust sliding mode observer for the aerodynamic torque is also proposed in order to avoid the wind speed sensors in the control scheme. The controller uses the estimated aerodynamic torque in order to calculate the reference value for the wind turbine speed. Another sliding mode control is also proposed in order to maintain the dc‐link voltage constant regardless of the direction of the rotor power flow. The stability analysis of the proposed controller under disturbances and parameter uncertainties is provided using the Lyapunov stability theory. Finally, the simulation results show that the proposed control scheme provides a high‐performance turbine speed control, in order to obtain the maximum wind power generation, and a high‐performance dc‐link regulation in the presence of system uncertainties.     

Nonlinear PI control for variable pitch wind turbine

Wind turbine uses a pitch angle controller to reduce the power captured above the rated wind speed and release the mechanical stress of the drive train. This paper investigates a nonlinear PI (N-PI) based pitch angle controller, by designing an extended-order state and perturbation observer to estimate and compensate unknown time-varying nonlinearities and disturbances. The proposed N-PI does not require the accurate model and uses only one set of PI parameters to provide a global optimal performance under wind speed changes. Simulation verification is based on a simplified two-mass wind turbine model and a detailed aero-elastic wind turbine simulator (FAST), respectively. Simulation results show that the N-PI controller can provide better dynamic performances of power regulation, load stress reduction and actuator usage, comparing with the conventional PI and gain-scheduled PI controller, and better robustness against of model uncertainties than feedback linearization control.