Application of simulated lidar scanning patterns to constrained Gaussian turbulence fields for load validation

We demonstrate a method for incorporating wind velocity measurements from multiple‐point scanning lidars into three‐dimensional wind turbulence time series serving as input to wind turbine load simulations. Simulated lidar scanning patterns are implemented by imposing constraints on randomly generated Gaussian turbulence fields in compliance with the Mann model for neutral stability. The expected efficiency of various scanning patterns is estimated by means of the explained variance associated with the constrained field. A numerical study is made using the hawc2 aeroelastic software, whereby the constrained turbulence wind time series serves as input to load simulations on a 10 MW wind turbine model using scanning patterns simulating different lidar technologies—pulsed lidar with one or multiple beams—and continuous‐wave lidars scanning in three different revolving patterns. Based on the results of this study, we assess the influence of the proposed method on the statistical uncertainty in wind turbine extreme and fatigue loads. The main conclusion is that introducing lidar measurements as turbulence constraints in load simulations may bring significant reduction in load and energy production uncertainty, not accounting for any additional uncertainty from real measurements. The constrained turbulence method is most efficient for prediction of energy production and loads governed by the turbulence intensity and the thrust force, while for other load components such as tower base side‐to‐side moment, the achieved reduction in uncertainty is minimal. Copyright © 2016 John Wiley & Sons, Ltd.     

Wind shear estimation model using load measurement of wind turbine tower and surrogate model

A wind shear estimation method based on fore‐aft moment is proposed to estimate wind shear strength without a Doppler lidar. We construct wind shear estimation models (WSEMs) using surrogate models whose input is the time‐averaged fore‐aft moment and various supervisory control and data acquisition (SCADA) system data. Learning data for the WSEMs are generated by numerical simulation or field measurement of a real turbine using SCADA, strain gauges, and Doppler lidar. By using simulation data, we construct 20 WSEMs with various input combinations and surrogate methods to select a model with the highest accuracy. The best WSEM is constructed with the universal Kriging surrogate model and uses the fore‐aft moment and wind speed as its input. Subsequently, the best WSEM is applied to a real turbine to validate its accuracy in real wind conditions, and we confirm that the WSEM has reasonable accuracy. However, the estimation error in the real wind condition is about twice as high as that in the simulation due to the real wind shear not completely corresponding to the assumed wind profile and a large yaw error. Further improvement in wind shear estimation accuracy will be achieved by adding yaw error and turbulence intensity to the input variables and applying the WSEM to wind farms on simple terrain or offshore wind farms where wind profile error decreases.     

Optimization‐based load reduction during rapid shutdown of multi‐megawatt wind turbine generators

This paper describes an optimization‐based approach to reducing extreme structural loads during rapid or emergency shutdown of multi‐megawatt wind turbine generators. The load reduction problem is cast into an optimal control formulation, and a simple, low‐order model is developed in order for this optimization problem to be tractable in reasonable time using state‐of‐the‐art numerical methods. To handle the variations in wind speed and turbulence inherent to wind turbine operation as well as the presence of model mismatch, a real‐time optimization strategy based on fast sensitivity updates is also considered, whose online computational burden is limited to the repeated solution of quadratic programs that are designed offline. The low‐order model and both the open‐loop and closed‐loop optimal control strategies are validated against a high‐fidelity model in the simulation environment Bladed ? for an industrial 3 MW wind turbine. Under favorable shutdown scenarios, i.e. when the wind turbine is operating properly and the actuators and sensors are not faulty, large reductions of the first compressive peak and subsequent compressive/tensile peaks of the tower load pattern are obtained at various above‐rated wind speeds compared with normal pitch control shutdown. Extension to more challenging shutdown scenarios are also discussed. Copyright © 2013 John Wiley & Sons, Ltd.     

Testing and validation of multi‐lidar scanning strategies for wind energy applications

Several factors cause lidars to measure different values of turbulence than an anemometer on a tower, including volume averaging, instrument noise and the use of a scanning circle to estimate the wind field. One way to avoid the use of a scanning circle is to deploy multiple scanning lidars and point them toward the same volume in space to collect velocity measurements and extract high‐resolution turbulence information. This paper explores the use of two multi‐lidar scanning strategies, the tri‐Doppler technique and the virtual tower technique, for measuring 3‐D turbulence. In summer 2013, a vertically profiling Leosphere WindCube lidar and three Halo Photonics Streamline lidars were operated at the Southern Great Plains Atmospheric Radiation Measurement site to test these multi‐lidar scanning strategies. During the first half of the field campaign, all three scanning lidars were pointed at approximately the same point in space and a tri‐Doppler analysis was completed to calculate the three‐dimensional wind vector every second. Next, all three scanning lidars were used to build a ‘virtual tower’ above the WindCube lidar. Results indicate that the tri‐Doppler technique measures higher values of horizontal turbulence than the WindCube lidar under stable atmospheric conditions, reduces variance contamination under unstable conditions and can measure high‐resolution profiles of mean wind speed and direction. The virtual tower technique provides adequate turbulence information under stable conditions but cannot capture the full temporal variability of turbulence experienced under unstable conditions because of the time needed to readjust the scans. Copyright © 2016 John Wiley & Sons, Ltd.     

Gaussian vs non‐Gaussian turbulence: impact on wind turbine loads

From large‐eddy simulations of atmospheric turbulence, a representation of Gaussian turbulence is constructed by randomizing the phases of the individual modes of variability. Time series of Gaussian turbulence are constructed and compared with its non‐Gaussian counterpart. Time series from the two types of turbulence are then used as input to wind turbine load simulations under normal operations with the HAWC2 software package. A slight increase in the extreme loads of the tower base fore‐aft moment is observed for high wind speeds when using non‐Gaussian turbulence but is insignificant when taking into account the safety factor for extreme moments. Other extreme load moments as well as the fatigue loads are not affected because of the use of non‐Gaussian turbulent inflow. It is suggested that the turbine thus acts like a low‐pass filter that averages out the non‐Gaussian behaviour, which is mainly associated with the fastest and smallest scales. Copyright © 2016 John Wiley & Sons, Ltd.     

Empirical modeling of single‐wake advection and expansion using full‐scale pulsed lidar‐based measurements

In the present paper, single‐wake dynamics have been studied both experimentally and numerically. The use of pulsed lidar measurements allows for validation of basic dynamic wake meandering modeling assumptions. Wake center tracking is used to estimate the wake advection velocity experimentally and to obtain an estimate of the wake expansion in a fixed frame of reference. A comparison shows good agreement between the measured average expansion and the Computational Fluid Dynamics (CFD) large eddy simulation–actuator line computations. Frandsen's expansion model seems to predict the wake expansion fairly well in the far wake but lacks accuracy in the outer region of the near wake. An empirical relationship, relating maximum wake induction and wake advection velocity, is derived and linked to the characteristics of a spherical vortex structure. Furthermore, a new empirical model for single‐wake expansion is proposed based on an initial wake expansion in the pressure‐driven flow regime and a spatial gradient computed from the large‐scale lateral velocities, and thus inspired by the basic assumption behind the dynamic wake meandering model. Copyright © 2014 John Wiley & Sons, Ltd.     

Wind turbine main‐bearing loading and wind field characteristics

This paper investigates the relationship between wind turbine main‐bearing loads and the characteristics of the incident wind field in which the wind turbine is operating. For a 2‐MW wind turbine model, fully aeroelastic multibody simulations are performed in 3D turbulent wind fields across the wind turbine's operational envelope. Hub loads are extracted and then injected into simplified drivetrain models of three types of main‐bearing configuration. The main‐bearing reaction loads and load ratios from the simplified model are presented and analysed. Results indicate that there is a strong link between wind field characteristics and the loading experienced by the main bearing(s), with the different bearing configurations displaying very different loading behaviours. Main‐bearing failure rates determined from operational data for two drivetrain configurations are also presented.     

Validation of a CFD model with a synchronized triple‐lidar system in the wind turbine induction zone

A novel validation methodology allows verifying a CFD model over the entire wind turbine induction zone using measurements from three synchronized lidars. The validation procedure relies on spatially discretizing the probability density function of the measured free‐stream wind speed. The resulting distributions are reproduced numerically by weighting steady‐state Reynolds averaged Navier‐Stokes simulations accordingly. The only input varying between these computations is the velocity at the inlet boundary. The rotor is modelled using an actuator disc. So as to compare lidar and simulations, the spatial and temporal uncertainty of the measurements is quantified and propagated through the data processing. For all velocity components the maximal difference between measurements and model are below 4.5% relative to the average wind speed for most of the validation space. This applies to both mean and standard deviation. One rotor radius upstream the difference reaches maximally 1.3% for the axial component. © 2017 The Authors. Wind Energy Published by John Wiley & Sons, Ltd.     

Load analysis of hydraulic‐pneumatic flywheel configurations integrated in a wind turbine rotor

In this paper, the impact on the mechanical loads of a wind turbine due to a previously proposed hydraulic‐pneumatic flywheel system is analysed. Load simulations are performed for the National Renewable Energy Laboratory (NREL) 5‐MW wind turbine using fatigue, aerodynamics, structures, and turbulence (FAST). It is discussed why FAST is applied although it cannot simulate variable rotor inertia. Several flywheel configurations, which increase the rotor inertia of the 5‐MW wind turbine by 15%, are implemented in the 61.5‐m rotor blade. Load simulations are performed twice for each configuration: Firstly, the flywheel system is discharged, and secondly, the flywheel is charged. The change in ultimate and fatigue loads on the tower, the low speed shaft, and the rotor blades is juxtaposed for all flywheel configurations. As the blades are mainly affected by the flywheel system, the increase in ultimate and fatigue loads of the blade is evaluated. Simulation results show that the initial design of the flywheel system causes the lowest impact on the mechanical loads of the rotor blades although this configuration is the heaviest.     

Wind turbine fatigue loads as a function of atmospheric conditions offshore

In recent years, there has been a growing interest by the wind energy community to assess the impact of atmospheric stability on wind turbine performance; however, up to now, typically, stability is considered in several distinct arbitrary stability classes. As a consequence, each stability class considered still covers a wide range of conditions. In this paper, wind turbine fatigue loads are studied as a function of atmospheric stability without a classification system, and instead, atmospheric conditions are described by a continuous joint probability distribution of wind speed and stability. Simulated fatigue loads based upon this joint probability distribution have been compared with two distinct different cases, one in which seven stability classes are adopted and one neglecting atmospheric stability by following International Electrotechnical Commission (IEC) standards. It is found that for the offshore site considered in this study, fatigue loads of the blade root, rotor and tower loads significantly increase if one follows the IEC standards (by up to 28% for the tower loads) and decrease if one considers several stability classes (by up to 13% for the tower loads). The substantial decrease found for the specific stability classes can be limited by considering one stability class that coincides with the mean stability of a given hub height wind speed. The difference in simulated fatigue loads by adopting distinct stability classes is primarily caused by neglecting strong unstable conditions for which relatively high fatigue loads occur. Combined, it is found that one has to carefully consider all stability conditions in wind turbine fatigue load simulations. Copyright © 2016 John Wiley & Sons, Ltd.     

An experimental and numerical study of the atmospheric stability impact on wind turbine wakes

In this paper, the impact of atmospheric stability on a wind turbine wake is studied experimentally and numerically. The experimental approach is based on full‐scale (nacelle based) pulsed lidar measurements of the wake flow field of a stall‐regulated 500 kW turbine at the DTU Wind Energy, Risø campus test site. Wake measurements are averaged within a mean wind speed bin of 1 m s^?1 and classified according to atmospheric stability using three different metrics: the Obukhov length, the Bulk–Richardson number and the Froude number. Three test cases are subsequently defined covering various atmospheric conditions. Simulations are carried out using large eddy simulation and actuator disk rotor modeling. The turbulence properties of the incoming wind are adapted to the thermal stratification using a newly developed spectral tensor model that includes buoyancy effects. Discrepancies are discussed, as basis for future model development and improvement. Finally, the impact of atmospheric stability on large‐scale and small‐scale wake flow characteristics is presently investigated. Copyright © 2015 John Wiley & Sons, Ltd.     

Prediction of wind‐turbine fatigue loads in forest regions based on turbulent LES inflow fields

Large‐eddy simulations (LES) were used to predict the neutral atmospheric boundary layer over a sparse and a dense forest, as well as over grass‐covered flat terrain. The forest is explicitly represented in the simulations through momentum sink terms. Turbulence data extracted from the LES served then as inflow turbulence for the simulation of the dynamic structural response of a generic wind turbine. In this way, the impact of forest density, wind speed and wind‐turbine hub height on the wind‐turbine fatigue loads was studied. Results show for example significantly increased equivalent fatigue loads above the two forests. Moreover, a comparison between LES turbulence and synthetically generated turbulence in terms of load predictions was made and revealed that synthetic turbulence was able to excite the same spectral peaks as LES turbulence but lead to consistently lower equivalent fatigue loads. Copyright © 2016 John Wiley & Sons, Ltd.     

Impact of fault ride‐through requirements on fixed‐speed wind turbine structural loads

The emphasis in this article is on the impact of fault ride‐through requirements on wind turbines structural loads. Nowadays, this aspect is a matter of high priority as wind turbines are required more and more to act as active components in the grid, i.e. to support the grid even during grid faults. This article proposes a computer approach for the quantification of the wind turbines structural loads caused by the fault ride‐through grid requirements. This approach, exemplified for the case of a 2MW active stall wind turbine, relies on the combination of knowledge from complimentary simulation tools, which have expertise in different specialized wind turbines design areas. Two complimentary simulation tools are considered i.e. the detailed power system simulation tool PowerFactory from DIgSILENT and the advanced aeroelastic computer code HAWC2, in order to assess of the dynamic response of wind turbines to grid faults. These two tools are coupled sequently in an offline approach, in order to achieve a thorough insight both into the structural as well as the electrical wind turbine response during grid faults. The impact of grid requirements on wind turbines structural loads is quantified by performing a rainflow and a statistical analysis for fatigue and ultimate structural loads, respectively. Two cases are compared i.e. one where the turbine is immediately disconnected from the grid when a grid fault occurs and one where the turbine is equipped with a fault ride‐through controller and therefore it is able to remain connected to the grid during the grid fault. Copyright copy; 2010 John Wiley & Sons, Ltd.     

Simplified fatigue load assessment in offshore wind turbine structural analysis

The estimation of fatigue lifetime for an offshore wind turbine support structure requires a large number of time‐domain simulations. It is an important question whether it is possible to reduce the number of load cases while retaining a high level of accuracy of the results. We present a novel method for simplified fatigue load assessments based on statistical regression models that estimate fatigue damage during power production. The main idea is to predict the total fatigue damage only and not also the individual damage values for each load case. We demonstrate the method for a jacket‐type support structure. Reducing the number of simulated load cases from 21 to 3, the total fatigue damage estimate exhibited a maximum error of about 6% compared with the complete assessment. As a consequence, a significant amount of simulation time can be saved, in the order of a factor of seven. This quick fatigue assessment is especially interesting in the application of structural optimization, with a large number of iterations. Copyright © 2015 John Wiley & Sons, Ltd.     

Planetary gear load sharing of wind turbine drivetrains subjected to non‐torque loads

An analytical formulation was developed to estimate the load‐sharing and planetary loads of a three‐point suspension wind turbine drivetrain considering the effects of non‐torque loads, gravity and bearing clearance. A three‐dimensional dynamic drivetrain model that includes mesh stiffness variation, tooth modifications and gearbox housing flexibility was also established to investigate gear tooth load distribution and non‐linear tooth and bearing contact of the planetary gears. These models were validated with experimental data from the National Renewable Energy Laboratory's Gearbox Reliability Collaborative. Non‐torque loads and gravity induce fundamental excitations in the rotating carrier frame, which can increase gearbox loads and disturb load sharing. Clearance in the carrier bearings reduces the bearing stiffness significantly. This increases the amount of pitching moment transmitted from the rotor to the gear meshes and disturbs the planetary load share, thereby resulting in edge loading. Edge loading increases the likelihood of tooth pitting and planet‐bearing fatigue, leading to reduced gearbox life. Additionally, at low‐input torque, the planet‐bearing loads are often less than the minimum recommended load and thus susceptible to skidding. Copyright © 2014 John Wiley & Sons, Ltd.     

On wind turbine loads during the evening transition period

The late afternoon hours in the diurnal cycle precede the development of the nocturnal stable boundary layer. This “evening transition” (ET) period is often when energy demand peaks. This period also corresponds to the time of day that is a precursor to late‐afternoon downbursts, a subject of separate interest. To capture physical characteristics of wind fields in the atmospheric boundary layer (ABL) during this ET period, particularly the interplay of shear and turbulence, stochastic simulation approaches, although more tractable, are not suitable. Large‐eddy simulation (LES), on the other hand, may be used to generate high‐resolution ABL turbulent flow fields. We present a suite of idealized LES four‐dimensional flow fields that define a database representing different combinations of large‐scale atmospheric conditions (characterized by associated geostrophic winds) and surface boundary conditions (characterized by surface heat fluxes). Our objective is to evaluate the performance of wind turbines during the ET period. Accordingly, we conduct a statistical analysis of turbine‐scale wind field variables. We then employ the database of these LES‐based inflow wind fields in aeroelastic simulations of a 5‐MW wind turbine. We discuss how turbine loads change as the ET period evolves. We also discuss maximum and fatigue loads on the rotor and tower resulting from different ABL conditions. Results of this study suggest that, during the ET period, the prevailing geostrophic wind speed affects the mean and variance of longitudinal winds greatly and thus has significant influence on all loads except the yaw moment which is less sensitive to uniform and symmetric incoming flow. On the other hand, surface heat flux levels affect vertical turbulence and wind shear more and, as a result, only affect maximum blade flapwise bending and tower fore‐aft bending loads.     

IEC standard based virtual wind turbine mechanical load test system

In order to conduct a systematic test over the mechanical load of the wind turbine, load measurement principles and methods have been studied according to the International Electro- technical Commission (IEC) standard, and wind turbine test scheme has been proposed. Combined with modern virtual instrument technology, a practical and reliable system for wind turbine mechanical load test has been developed. In addition to collecting various wind turbine parameters, the system can also yield a series of curves and charts ruled by IEC standards such as the capture matrix, the relation between load and wind speed, the equivalent load and load spectrum.     

A spinner‐integrated wind lidar for enhanced wind turbine control

A field test with a continuous wave wind lidar (ZephIR) installed in the rotating spinner of a wind turbine for unimpeded preview measurements of the upwind approaching wind conditions is described. The experimental setup with the wind lidar on the tip of the rotating spinner of a large 80 m rotor diameter, 59 m hub height 2.3 MW wind turbine (Vestas NM80), located at Tjæreborg Enge in western Denmark is presented. Preview wind data at two selected upwind measurement distances, acquired during two measurement periods of different wind speed and atmospheric stability conditions, are analyzed. The lidar‐measured speed, shear and direction of the wind field previewed in front of the turbine are compared with reference measurements from an adjacent met mast and also with the speed and direction measurements on top of the nacelle behind the rotor plane used by the wind turbine itself. Yaw alignment of the wind turbine based on the spinner lidar measurements is compared with wind direction measurements from both the nearby reference met mast and the turbine's own yaw alignment wind vane. Furthermore, the ability to detect vertical wind shear and vertical direction veer in the inflow, through the analysis of the spinner lidar data, is investigated. Finally, the potential for enhancing turbine control and performance based on wind lidar preview measurements in combination with feed‐forward enabled turbine controllers is discussed. Copyright © 2012 John Wiley & Sons, Ltd.     

Simulating the dynamics of wind turbine blades: part II,model validation and uncertainty quantification

Verification and validation (V&V) offers the potential to play an indispensable role in the development of credible models for the simulation of wind turbines. This paper highlights the development of a three‐dimensional finite element model of the CX‐100 wind turbine blade. The scientific hypothesis that we wish to confirm by applying V&V activities is that it is possible to develop a fast‐running model capable of predicting the low‐order vibration dynamics with sufficient accuracy. A computationally efficient model is achieved by segmenting the geometry of the blade into six sections only. It is further assumed that each cross section can be homogenized with isotropic material properties. The main objectives of V&V activities deployed are to, first, assess the extent to which these assumptions are justified and, second, to quantify the resulting prediction uncertainty. Designs of computer experiments are analyzed to understand the effects of parameter uncertainty and identify the significant sensitivities. A calibration of model parameters to natural frequencies predicted by the simplified model is performed in two steps with the use of, first, a free–free configuration of the blade and, second, a fixed–free configuration. This two‐step approach is convenient to decouple the material properties from parameters of the model that describe the boundary condition. Here, calibration is not formulated as an optimization problem. Instead, it is viewed as a problem of inference uncertainty quantification where measurements are used to learn the uncertainty of model parameters. Gaussian process models, statistical tests and Markov chain Monte Carlo sampling are combined to explore the (true but unknown) joint probability distribution of parameters that, when sampled, produces bounds of prediction uncertainty that are consistent with the experimental variability. An independent validation assessment follows the calibration and is applied to mode shape vectors. Despite the identification of isolated issues with the simulation code and model developed, the overarching conclusion is that the modeling strategy is sound and leads to an accurate‐enough, fast‐running simulation of blade dynamics. This publication is Part II of a two‐part effort that highlights the V&V steps required to develop a robust model of a wind turbine blade, where Part I emphasizes code verification and the quantification of numerical uncertainty. Approved for unlimited public release on August 26, 2011, LA‐UR‐11‐4997. Copyright © 2012 John Wiley & Sons, Ltd.