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。     

复杂地形环境下多机器人编队控制方法

针对复杂地形地面崎岖起伏的特点,提出了一种多机器人系统编队控制方法.首先,分析了复杂地形环境下的系统队形模型.通过建立三维地形环境下编队系统的误差模型,并运用空间投影法将其映射到二维平面上,对系统的编队误差进行分析.然后利用李雅普诺夫函数构造控制器,并根据环境中的特定地形设计相应的编队行驶策略,实现了多机器人系统在复杂地形环境下的编队控制.最后,通过3种典型复杂地形环境下两种非完整移动机器人的编队仿真,验证了该方法的有效性.     

大型风力发电机组控制器优化设计

风力发电机组是复杂多变量非线性系统,具有不确定性和多干扰等特点.目前国内应用的风力发电机组大多采用变桨变速恒频系统,具有风能利用系数高、安全可靠、改善整机受力等优点,然而依然面临载荷过大、功率波动大和变桨过于频繁等问题,因此,在大型风力发电机组系统中,选择最适合控制策略的控制器的优化设计就显得尤为重要.在此提出基于模糊性能评估器的控制方法,建立非线性控制模型并设计模糊控制器,介绍了控制器的优化设计步骤,仿真结果表明了这种方法的有效性.     

基于有效风速估计与预测的风电机组自适应最大风能跟踪控制

针对如何在有效风速未知情况下实现风电机组最大风能跟踪(MPPT)的问题,本文使用支持向量回归(SVR)和自适应控制原理,提出基于有效风速估计与预测的自适应MPPT控制方案.首先,使用机组的历史运行数据,训练得到基于SVR的风速估计与预测模型,为MPPT控制提供实时参考输入.其次,结合在线学习估计器(OLA)和减小转矩增益(DTG)控制原理,设计自适应MPPT控制器,该控制器能够较好应对系统未知动态特性和干扰,且能降低传动链载荷.最后,使用李雅普诺夫原理证明闭环系统所有信号都是有界的.仿真结果表明本文提出的方法能够获得良好的MPPT效果,进而提高机组产能.     

行波故障测距装置现场校验技术研究

为解决行波故障测距装置的现场检测问题,本文讨论了行波测距装置的测距原理,分析了行波测距装置内双端测距的测距方法,研究了故障行波信号特性及电流互感器及二次电缆等二次传变回路对故障行波传递的影响,探究了一套针对行波测距装置的现场校验平台和方法。检测平台主要包括基于高频线性电流放大器为基础的故障行波再现装置、电磁暂态仿真软件以及GPS卫星同步装置。高频线性电流放大器作为故障行波再现装置,至少能同时输出多路高频电流且配备GPS卫星同步系统,以及考虑了二次传变回路的基于电磁暂态仿真软件的故障模拟仿真系统。检测结果验证了现场校验方法和平台的可行性和正确性。行波测距装置现场校验能够有效发现行波测距装置的技术缺陷、检测行波测距装置测距精度及可靠性。     

Calculation and characteristics analysis of blade pitch loads for large scale wind turbines

Based on the electric pitch system of large scale horizontal-axis wind turbines,the blade pitch loads coming mainly from centrifugal force,aerodynamic force and gravity are analyzed,and the calculation models for them are established in this paper.For illustration,a 1.2 MW wind turbine is introduced as a practical sample,and its blade pitch loads from centrifugal force,aerodynamic force and gravity are calculated and analyzed separately and synthetically.The research results showed that in the process of ro...     

A control strategy for variable-speed variable-pitch wind turbines within the regions of partial- and full-load operation without wind speed feedback

In this paper, the control of a variable-speed variable-pitch wind turbine in the whole wind speed range is addressed, without any feedback measurement of wind speed. In addition to an aerodynamic torque observer able to ensure the tracking of the maximum delivered power in the partial-load region, a novel wind speed observer is proposed for power regulation in the full-load region, along with a sliding surface ensuring finite-time set-point stabilization of the speed tracking error. The proposed control solution has been validated on the National Renewable Energy Laboratory 5-MW three-blade wind turbine model using the recognized high-fidelity simulation tool FAST.     

ICARO: a package for wind field studies over complex terrain

ICARO is a software package developed to construct, examine, and compare wind fields in complex terrain. The user may interactively run mathematical models to evaluate three dimensional wind fields from available experimental measurements. Graphics and post-processing programs are implemented in ICARO to analyze and intercompare wind field results, as well as verify results with measurements. These features may be extended to results from other fluid-dynamic models. Different vertical grid resolutions are possible for verification of models performance. ICARO has proved to be a very quick and useful tool for both case studies and field experiments. The package is written in FORTRAN 77 and runs on DEC-VAX computers with a VMS operating system using NCAR graphics routines.     

Design of low noise airfoil with high aerodynamic performance for use on small wind turbines

Wind power is one of the most reliable renewable energy sources and internationally installed capacity is increasing radically every year.Although wind power has been favored by the public in general,the problem with the impact of wind turbine noise on people living in the vicinity of the turbines has been increased.Low noise wind turbine design is becoming more and more important as noise is spreading more adverse effect of wind turbine to public.This paper demonstrates the design of 10 kW class wind turbi...     

Combination of model-based observer and support vector machines for fault detection of wind turbines

Support vector machines and a Kalman-like observer are used for fault detection and isolation in a variable speed horizontalaxis wind turbine composed of three blades and a full converter. The support vector approach is data-based and is therefore robust to process knowledge. It is based on structural risk minimization which enhances generalization even with small training data set and it allows for process nonlinearity by using flexible kernels. In this work, a radial basis function is used as the kernel. Different parts of the process are investigated including actuators and sensors faults. With duplicated sensors, sensor faults in blade pitch positions,generator and rotor speeds can be detected. Faults of type stuck measurements can be detected in 2 sampling periods. The detection time of offset/scaled measurements depends on the severity of the fault and on the process dynamics when the fault occurs. The converter torque actuator fault can be detected within 2 sampling periods. Faults in the actuators of the pitch systems represents a higher difficulty for fault detection which is due to the fact that such faults only affect the transitory state(which is very fast) but not the final stationary state. Therefore, two methods are considered and compared for fault detection and isolation of this fault: support vector machines and a Kalman-like observer. Advantages and disadvantages of each method are discussed. On one hand, support vector machines training of transitory states would require a big amount of data in different situations, but the fault detection and isolation results are robust to variations in the input/operating point. On the other hand, the observer is model-based, and therefore does not require training, and it allows identification of the fault level, which is interesting for fault reconfiguration. But the observability of the system is ensured under specific conditions, related to the dynamics of the inputs and outputs. The whole fault detection and isolation scheme is evaluated using a wind     

大型海上风力发电高塔系统一体化分析建模研究

大型海上风力发电高塔系统的精细化建模与整体可靠性设计对保障风能资源开发的安全性与经济性日益重要.本文结合柔体动力学与有限元建模,考虑气动耦合效应、桩土相互作用、塔体前后运动控制和非线性转矩控制,建立了大型海上风力发电高塔系统一体化分析模型(Sto DRAOWT模型).与国际上通用的风机分析软件分析结果对比表明,本文建立的Sto DRAOWT模型分析结果可信,建模更为全面合理,计算效率更高.在此基础上,实现了风浪联合作用下海上风力发电高塔整体系统的动力响应分析,为大型海上风力发电高塔系统的随机响应分析与可靠性设计奠定了基础.     

基于参考输入优化的变速风电机组最大化风能捕获方法

变速风电机组在额定风速以下应用最大功率点跟踪实现最大化风能捕获. 然而, 大惯量风电机组在面对快速波动的湍流风速时, 因转速调节慢而难以保持运行于最大功率点. 本文研究进一步发现, 平均转速跟踪误差与整体的风能捕获效率并非单调关系, 这使得当前以减小转速跟踪误差为目标的控制器设计难以有效提升风电机组的发电效率. 为此, 本文以提升风能捕获效率(而非减小转速跟踪误差)为目标, 提出一种基于参考输入优化的风电机组最大化风能捕获方法. 考虑到参考转速对风能捕获效率的复杂影响难以准确建模, 本文借助深度确定性策略梯度(DDPG)强化学习算法实现参考输入优化. 仿真结果表明该方法能够有效提升湍流风下变速风电机组的风能捕获效率.     

Mass-consistent models for wind fields over complex terrain: The state of the art

Among the diagnostic models for wind field simulation, mass-consistent models play an important role, thanks to the simplicity of the physics involved and their capacity to accept several measurements of wind at different points of the domain. The general procedure and mathematical supports for this kind of simulation, with particular reference to the approximation that characterize the different models developed, are analyzed. Evidently, a large number of simulations is required if one needs to know the average wind over a region, with a consequent long calculation time. Some methods reducing this time, without losing fundamental information, are described.     

双馈感应风力发电机组的滑模直接电压控制

为解决PI矢量控制动态响应慢且依赖电机精确参数的问题, 本文将滑模控制与空间矢量调制结合, 提出了一种开关频率固定的滑模直接电压控制(SMDVC)方法, 以实现双馈感应电机(DFIG)的电网同步控制. 实验结果表明, 提出的SMDVC方法具有比PI矢量控制更好的动态性能, 即使在电网电压不平衡工况下, 也能较好地控制DFIG定子电压实现对电网电压的精确跟踪.     

Fault diagnosis for wind turbines based on LSTM and feature optimization strategies

High penetration of renewable energy is the development trend of the future power system. As one of the clean energy sources, wind power generation has an increasing share in the energy market. However, due to the harsh working environment, the high fault rate and poor accessibility of the wind farms, resulting in the difficult maintenance process and high cost. This article proposes a fault diagnosis (FD) method based on long short-term memory (LSTM) and feature optimization strategies for wind turbines (WTs), thus reducing the operation and maintenance costs of WTs. First, Pearson correlation coefficient analysis is performed on the collected data features to remove redundant features, and wavelet transform is adopted to remove the redundant data, so as to optimize the fault features and fault data. Then the selected features samples are used to train LSTM-based FD model. Finally, the actual production data is adopted to verify the proposed method. The proposed method can effectively locate the faults, and provide data support for wind farms, thus improving the reliability, safety, and economic benefits of wind farms.     

A novel control solution for improved trajectory tracking and LVRT performance in DFIG-based wind turbines

This paper presents a new control strategy for the rotor side converter of Doubly-Fed Induction Generator based Wind Turbine systems, under severe voltage dips. The main goal is to fulfill the Low Voltage Ride Through performance, required by modern grid codes. In this respect, the key point is to limit oscillations (particularly on rotor currents) triggered by line faults, so that the system keeps operating with graceful behavior. To this aim, a suitable feedforward-feedback control solution is proposed for the DFIG rotor side. The feedforward part exploits oscillation-free reference trajectories, analytically derived for the system internal dynamics. State feedback, designed accounting for control voltage limits, endows the system with robustness and further tame oscillations during faults. Moreover, improved torque and stator reactive power tracking during faults is achieved, proposing an exact mapping between such quantities and rotor-side currents, which are conventionally used as controlled outputs. Numerical simulations are provided to validate the capability of the proposed approach to effectively cope with harsh faults.     

基于FIR神经网络的风电场虚拟风速传感器

风电机组风速传感器易发故障,故障可能导致机组安全风险和发电量损失。针对现行的故障处理方法因与机组控制策略紧密耦合而日益面临挑战,提出了一种基于数据处理的虚拟风速传感器原理与方法：由风电场上风向测量风速计算下风向推算风速,用推算风速取代故障传感器。着重讨论了基于FIR神经网络的推算风速计算方法和计算模型,探讨了系统实现的关键技术。实验证明了虚拟传感器的误差在机组控制系统可接受的程度内。提出的方法独立于机组自身属性,具有普遍适用性,可部署在任意类型的场,在物理传感器故障时向机组提供风速信号,支撑风电机组持续安全运行。     

低风速风力机最大风能追踪的互补滑模控制

针对风力机系统在最大功率点跟踪(MPPT)阶段易受风速等不确定因素的影响,为了进一步提高风力机的风能捕获效率,本文在滑模控制的基础上提出了一种互补滑模控制方法.首先,建立了含有干扰项的风力机系统的线性化模型,采用广义滑模面与互补滑模面相结合的方法设计了互补滑模控制器,并在理论上证明了此控制方法能够有效保证风力机转速跟踪误差的收敛性,且能提高转速跟踪精度.其次,采用风力机专业仿真软件FAST对美国可再生能源实验室(NREL)的600 kW风力机进行了仿真实验,结果表明本文所提出的控制方法不但能提高风力机的风能捕获效率,而且能有效减小转速跟踪误差.最后,将本文所提方法与现有常见的几种控制方法相比较发现:风力机系统在互补滑模控制策略下,具有更高的风能捕获效率和更小的转速跟踪误差.     

基于数值风洞的光伏支架阵列风载荷分布

用计算流体力学方法分析光伏支架阵列风场,研究各倾角和风向角情况下支架阵列中风载荷的分布,提出支架阵列的区域划分和风载荷体型系数取值建议。研究成果对光伏支架阵列结构设计和工程建设具有较好的应用价值。该方法有利于节省材料,降低光伏发电的成本。