额定风速以上风力发电机组的恒功率H∞鲁棒控制

风力发电机组由于机械结构以及电气负荷承受能力的限制存在着转速限制和功率限制, 额定风速以上时,需要通过控制桨距角来实现额定恒功率输出, 同时保持转速在额定转速处. 本文建立了风力发电机组的详细机理模型, 将H_∞控制理论应用到额定风速以上时风力发电机组的恒功率输出的控制器设计, 建立了标准H_∞恒功率控制问题. 利用LMI方法求解, 得到了桨距角的H_∞控制器. 仿真结果表明该H_∞控制器能够成功实现额定风速以上时的恒功率输出控制, 并且具有良好的鲁棒性.     

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.     

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.     

基于反馈线性化的液压型风力发电机组最佳功率追踪控制

液压型风力发电机组在额定风速以下时为获得最多电能,需随风速变化追踪最佳功率点.建立并网液压型风力发电机组仿射非线性数学模型,基于反馈线性化方法,分别以风力机转速和液压系统传输功率为输出,以变量马达摆角为控制输入,线性化系统,设计最佳转速与最佳功率追踪控制器,实现机组在额定风速以下随风速变化输出最佳功率.仿真结果表明,以液压系统传输功率为控制输出的功率追踪过程动静态特性较好.理论分析表明,控制器中高压腔压力变化率是否可以规划,是影响功率追踪过程稳定性的关键因素.     

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。     

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。     

变速风力发电机组出功控制策略研究

变速风力发电机组通常采用转速控制和变桨距控制相结合的方法,在额定风速以下主要调节发电机的转矩使转速跟随风速变化而变化,以获得最佳叶尖速比;在额定风速以上通过调整桨叶节距,改变气流对叶片攻角,从而改变风力发电机组获得的空气动力转矩,才能使功率输出保持稳定传统PID控制方案在风电控制中仍然发挥重要的作用,先进的控制算法与传...     

兆瓦级同步风力发电机变桨距控制策略研究

变桨距风力发电机已成为风力发电机组的主要研究和发展方向,结合长星集团同步风力发电机组,对变桨距控制技术进行了研究,在额定风速以下时实行变速运行,控制发电机的励磁电流从而控制发电机的转速,使得风力机转速能够跟随风速变化,保持最佳叶尖速比使系统获得最大的风能利用系数;额定风速以上时,采用PID控制算法控制桨距角,使发电机输出功率恒定,并提出了实现方法;通过仿真工具进行计算机仿真,验证了本方法的有效性。     

风力发电技术与功率控制策略研究

对风力发电技术进行综述,分析研究了变速恒频双馈风力发电机组实现风能最大捕获的功率控制策略,即当风速在切入风速和额定风速之间时,控制发电机转子励磁电流及频率,追踪最佳功率曲线;在额定风速和切出风速之间时,调节风力机叶片桨距角,保持额定功率不变.研究表明,基于风速的功率控制方法,提高了风力发电机组风能利用效率;同时,基于风向标和输出功率的偏航控制策略,能缩短风力机对风时间,提高风力机对风精度和使用寿命.     

风轮机桨距角的数据驱动预测控制

数据驱动预测控制方法是数据驱动和预测控制相结合而产生的一种新型控制策略.传统的模型预测控制(MPC)方法使用的预测模型一般都是近似线性系统预测模型.在具有强非线性的工业过程中,数据驱动预测控制方法对系统模型要求更低,控制效果更好.针对额定风速以上风轮机桨距角的控制问题,利用输入输出数据在线设计控制器,将数据驱动预测控制方法较好的应用于风力发电系统中,实现额定风速以上系统的恒功率控制.仿真结果表明该方法能够成功控制风轮机桨距角,达到系统恒功率输出的控制目标,同时保持转速在额定值附近.     

Kalman filter-based wind speed estimation for wind turbine control

To improve power production and reduce loads on turbine components, exact wind speed information is required in modern wind turbine controllers. However, the wind speed measured on the nacelle is imprecise because of its drawbacks of single point measurement and non-immunity to disturbances. To solve this problem, the EWS (Effective Wind Speed) estimator has been proposed as an alternative. According to the literatures, there are two kinds of EWS estimator, that is, the KF-based estimator and the EKF-based one. Where, the former is applied to estimate the aerodynamic torque, then the EWS is numerically calculated; and the latter directly estimate the EWS. Since the estimate EWS significantly affect the controller’s effectiveness, their performance needs to be clarified. To fully investigate the two estimators, there is a need to evaluate their performance on an even platform. In this paper, we present comparative studies on these two methods. Their advantages and drawbacks are investigated on the commercial turbine design software-bladed and compared through detailed simulation results. Finally, we demonstrate some simulation results and differences between the KF-based estimator and the EKF-based one.     

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.     

二维超声波风速风向传感器设计

风是气象预报中的一个重要的要素,准确地预报风速,对人们的生产生活都有一定的影响。二维超声风传感器是气象与工业中最重要的风速测量方式之一,在传统的超声波测风仪器的基础上,通过测量空气温湿度来进行准确的调节,补偿了雨雾等环境因素的影响,设计一种基于STM32处理器的200 kHz全天候超声测风仪,通过实验证明：该装置可以实现全天候精确测量风速风向,测量误差小。     

Gain-scheduling control of a floating offshore wind turbine above rated wind speed

This paper presents an application of gain-scheduling(GS) control techniques to a floating offshore wind turbine on a barge platform for above rated wind speed cases. Special emphasis is placed on the dynamics variation of the wind turbine system caused by plant nonlinearity with respect to wind speed. The turbine system with the dynamics variation is represented by a linear parameter-varying(LPV) model, which is derived by interpolating linearized models at various operating wind speeds. To achieve control objectives of regulating power capture and minimizing platform motions, both linear quadratic regulator(LQR) GS and LPV GS controller design techniques are explored. The designed controllers are evaluated in simulations with the NREL 5 MW wind turbine model, and compared with the baseline proportional-integral(PI) GS controller and non-GS controllers. The simulation results demonstrate the performance superiority of LQR GS and LPV GS controllers, as well as the performance trade-off between power regulation and platform movement reduction.     

Multiscale prediction of wind speed and output power for the wind farm

This paper focuses on establishing the multiscale prediction models for wind speed and power in wind farm by the average wind speed collected from the history records. Each type of the models is built with different time scales and by different approaches. There are three types of them that a short-term model for a day ahead is based on the least squares support vector machine (LSSVM), a medium-term model for a month ahead is on the combination of LSSVM and wavelet transform (WT), and a long-term model for a year ahead is on the empirical mode decomposition (EMD) and recursive least square (RLS) approaches. The simulation studies show that the average value of the mean absolute percentage error (MAPE) is 4.91%, 6.57% and 16.25% for the short-term, the medium-term and the long-term prediction, respectively. The predicted data also can be used to calculate the predictive values of output power for the wind farm in different time scales, combined with the generator’s power characteristic, meteorologic factors and unit efficiency under various operating conditions.     

A new wind retrieval algorithm for Jason-1 at high wind speeds

The altimeter wind speed algorithm at high wind speeds remains unsolved because of lack of observed data. In this study data at high wind speeds were generated using Yin's typhoon model, which consists of the Rankine vortex model and the angular momentum model with typhoon parameters, provided by the Joint Typhoon Warning Centre (JTWC). The accuracy of Yin's typhoon model can be validated by comparing it with recorded data from a weather station. By comparing the normalized radar backscatter cross‐section (NRCS) detected by the Jason‐1 altimeter with wind speed data inferred by Yin's typhoon model, an empirical algorithm valid for a range of wind speeds between 10 and 40 m s^–1 is developed and proposed. The proposed algorithm is compared with the Jason‐1 operational algorithm and Young's altimeter wind retrieval algorithm. The study shows that, for the proposed algorithm and the operational algorithm for Jason‐1, the root mean square (RMS) errors are 3.38 and 3.60 m s^–1, respectively, and the average relative errors are 18% and 19%, respectively, for wind speeds less than 27 m s^–1. Hence, the proposed algorithm is in agreement with the operational algorithm for the Jason‐1 altimeter for wind speeds in the range 10–27 m s^–1. However, the Jason‐1 operational algorithm is inaccurate for wind speeds above 27 m s^–1 because the wind speeds used in the algorithm training process came from scatterometer wind products, and are significantly lower than those in strong wind and heavy rain conditions. Comparison of the proposed algorithm and Young's algorithm shows that the RMS errors are 6.27 and 15.18 m s^–1, respectively, and the average relative errors are 16% and 59%, respectively, for wind speeds greater than 20 m s^–1. The Holland typhoon model cannot accurately determine the outer wind field of typhoons since it extends cyclonic wind speeds to infinity. Young's altimeter wind retrieval algorithm depends on the Holland typhoon model, and the latter results in some errors. Compared with Young's altimeter wind retrieval algorithm, the proposed algorithm retrieves wind speeds with better accuracy. Therefore, the proposed algorithm, suitable for retrieving sea surface wind speeds in typhoons and other strong wind conditions, can be considered as supplementary to the Jason‐1 operational algorithm.     

The virtual wind tunnel

The design and implementation of a virtual environment linked to a graphics workstation for the visualization of complex fluid flows are described. The system user wears a stereo head-tracked display, which effectively displays 3-D information, and an instrumented glove to intuitively position flow-visualization tools. The visualization structures and their interfaces in the virtual environment and the implementation hardware and software are described. The performance of the virtual wind tunnel is reviewed using the flow past a tapered cylinder as an example. Performance issues and future directions for the system are discussed     

Optimal wind velocity estimation

A new approach to remote wind velocity sensing is proposed, developed, and tested. Wind estimates were obtained from the spectral signature of an optical signal source. The signal was derived from the random scattering of a laser beam in the lower atmosphere. A quasi-supervised learning machine, using a minimal variance linear estimator, was used to produce the wind velocity estimate. New stopping rules, used to guarantee the convergence of the learning process, were also developed. Field experimentation indicates that the new system will perform well, even under extreme optical nonlinear conditions due to severe turbulence.     

一种自动校准多风表的风洞检测试验装置

针对传统风表校准方式需多次手动调节风量、操作复杂、人工读数与绘图费时费力且校准精度低等问题,设计了一种自动校准多风表的风洞检测试验装置,介绍了该装置的结构及检测试验原理。试验结果表明,该装置风流稳定,可自动调节风量,操作简单,可1次校准多个风表,校准精度高,并能对校准结果进行记录、存储、处理,适合于低、中、高3档多风表自动校准。