Model of wind shear conditional on turbulence and its impact on wind turbine loads

We analyse high‐frequency wind velocity measurements from two test stations over a period of several years and at heights ranging from 60 to 200 m, with the objective to validate wind shear predictions as used in load simulations for wind turbine design. A validated wind shear model is thereby proposed for flat terrain and that can significantly decrease the uncertainty associated with fatigue load predictions for wind turbines with large rotors. An essential contribution is the conditioning of wind shear on the 90% quantile of wind turbulence, such that the appropriate magnitude of the design fatigue load is achieved. The proposed wind shear model based on the wind measurements is thereby probabilistic in definition, with shear jointly distributed with wind turbulence. A simplified model for the wind shear exponent is further derived from the full stochastic model. The fatigue loads over different turbine components are evaluated under the full wind measurements, using the developed wind shear model and with standard wind conditions prescribed in the IEC 61400‐1 ed. 3. The results display the effect of the Wöhler exponent and reveal that under moderate turbulence, the effect of wind shear is most pronounced on the blade flap loads. It is further shown that under moderate wind turbulence, the wind shear exponents may be over‐specified in the design standards, and a reduction of wind shear exponent based on the present measurements can contribute to reduced fatigue damage equivalent loads on turbine blades. Although the influence of wind shear on extreme loads was found to be negligible, the IEC 61400‐1 wind shear definition was found to result in non‐conservative estimates of the 50 year extreme blade deflection toward the tower, especially under extreme turbulence conditions. 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.     

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.     

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.     

Effects of spatial and temporal resolution of the turbulent inflow on wind turbine performance estimation

The effects of spatial and temporal resolution of wind inflows generated using large eddy simulations (LES) on the scales of turbulence present in the wind inflow, and the resulting changes in wind turbine performance were investigated for neutral atmospheric boundary layer conditions. Wind inflows with four different spatial resolutions and five different temporal resolutions were used to produce different turbine responses. An aero‐elastic code assessed the dynamic response of two wind turbines to the different inflows. Auto‐spectral density functions (ASDF) of turbine responses, such as blade deflection and bending moment, that are representative of the turbine response were used to assess the effect of the inflow. The results indicated that, as additional turbulence scales were resolved, the wind turbines showed a similar increased response that was evident in both the ASDF and variance of the different wind turbine performance parameters. As a result, the amount to which turbulence is resolved in the inflow, particularly using tools such as LES, will be important to consider when using these inflows for wind turbine design and performance prediction. Copyright © 2015 John Wiley & Sons, Ltd.     

Large‐eddy simulation of stable boundary layer turbulence and estimation of associated wind turbine loads

Stochastic simulation of turbulent inflow fields commonly used in wind turbine load computations is unable to account for contrasting states of atmospheric stability. Flow fields in the stable boundary layer, for instance, have characteristics such as enhanced wind speed and directional shear; these effects can influence loads on utility‐scale wind turbines. To investigate these influences, we use large‐eddy simulation (LES) to generate an extensive database of high‐resolution ( ～ 10 m), four‐dimensional turbulent flow fields. Key atmospheric conditions (e.g., geostrophic wind) and surface conditions (e.g., aerodynamic roughness length) are systematically varied to generate a diverse range of physically realizable atmospheric stabilities. We show that turbine‐scale variables (e.g., hub height wind speed, standard deviation of the longitudinal wind speed, wind speed shear, wind directional shear and Richardson number) are strongly interrelated. Thus, we strongly advocate that these variables should not be prescribed as independent degrees of freedom in any synthetic turbulent inflow generator but rather that any turbulence generation procedure should be able to bring about realistic sets of such physically realizable sets of turbine‐scale flow variables. We demonstrate the utility of our LES‐generated database in estimation of loads on a 5‐MW wind turbine model. More importantly, we identify specific turbine‐scale flow variables that are responsible for large turbine loads—e.g., wind speed shear is found to have a greater influence on out‐of‐plane blade bending moments for the turbine studied compared with its influence on other loads such as the tower‐top yaw moment and the fore‐aft tower base moment. Overall, our study suggests that LES may be effectively used to model inflow fields, to study characteristics of flow fields under various atmospheric stability conditions and to assess turbine loads for conditions that are not typically examined in design standards. Copyright © 2013 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.     

Effective turbulence and its implications in wind turbine fatigue assessment

The effective turbulence approximation is widely used in the wind energy industry for site‐specific fatigue assessment of wind turbines with reference to loads. It significantly reduces the amount of aero‐elastic simulations required to document structural integrity by integrating out the directional variation of turbulence. Deriving the effective turbulence involves assumptions related to load effect histories, structural dynamics, and material fatigue strength. These assumptions may lead to low accuracy of fatigue load assessments by the effective turbulence compared with full directional simulations. This paper quantifies the implications of the effective turbulence for a multimegawatt wind turbine during normal operation. Analyses based on wind measurements from almost one hundred international sites document that the effective turbulence provides accurate results compared with full sector‐wise simulations, but only when linear SN ‐curves are assumed. For a more advanced steel tower design approach using a bilinear SN ‐curve, a reduction of the cross‐sectional design parameters by almost 10% is achieved. Additional 10% reduction can be obtained if fatigue damage is estimated utilizing the wind direction information. By applying a probabilistic approach, it is shown that this reduction in the design parameter of the steel tower does not compromise the structural integrity when the current IEC 61400‐1 standard is followed. The results presented may improve decision making in site‐specific fatigue assessments of wind turbines and prevent overconservative design, which results from the use of the effective turbulence, and thereby reduce the cost of wind energy.     

Load alleviation of wind turbines by yaw misalignment

Vertical wind shear is one of the dominating causes of load variations on the blades of a horizontal axis wind turbine. To alleviate the varying loads, wind turbine control systems have been augmented with sensors and actuators for individual pitch control. However, the loads caused by a vertical wind shear can also be affected through yaw misalignment. Recent studies of yaw control have been focused on improving the yaw alignment to increase the power capture at below rated wind speeds. In this study, the potential of alleviating blade load variations induced by the wind shear through yaw misalignment is assessed. The study is performed through simulations of a reference turbine. The study shows that optimal yaw misalignment angles for minimizing the blade load variations can be identified for both deterministic and turbulent inflows. It is shown that the optimal yaw misalignment angles can be applied without power loss for wind speeds above rated wind speed. In deterministic inflow, it is shown that the range of the steady‐state blade load variations can be reduced by up to 70%. For turbulent inflows, it is shown that the potential blade fatigue load reductions depend on the turbulence level. In inflows with high levels of turbulence, the observed blade fatigue load reductions are small, whereas the blade fatigue loads are reduced by 20% at low turbulence levels. For both deterministic and turbulent inflows, it is seen that the blade load reductions are penalized by increased load variations on the non‐rotating turbine parts. Copyright © 2013 John Wiley & Sons, Ltd.     

Indicial lift response function: an empirical relation for finite‐thickness airfoils,and effects on aeroelastic simulations

The aeroelastic response of wind turbines is often simulated in the time domain by using indicial response techniques. Unsteady aerodynamics in attached flow are usually based on Jones's approximation of the flat plate indicial response, although the response for finite‐thickness airfoils differs from the flat plate one. The indicial lift response of finite‐thickness airfoils is simulated with a panel code, and an empirical relation is outlined connecting the airfoil indicial response to its geometric characteristics. The effects of different indicial approximations are evaluated on a 2D profile undergoing harmonic pitching motion in the attached flow region; the resulting lift forces are compared with computational fluid dynamics (CFD) simulations. The relevance for aeroelastic simulations of a wind turbine is also evaluated, and the effects are quantified in terms of variations of equivalent fatigue loads, ultimate loads, and stability limits. The agreement with CFD computations of a 2D profile in harmonic motion is improved by the indicial function accounting for the finite‐thickness of the airfoil. Concerning the full wind turbine aeroelastic behavior, the differences between simulations on the basis of Jones's and finite‐thickness indicial response functions are rather small; Jones's flat‐plate approximation results in only slightly larger fatigue and ultimate loads, and lower stability limits. Copyright © 2012 John Wiley & Sons, Ltd.     

Influence of atmospheric stability on wind turbine loads

Simulations of wind turbine loads for the NREL 5 MW reference wind turbine under diabatic conditions are performed. The diabatic conditions are incorporated in the input wind field in the form of wind profile and turbulence. The simulations are carried out for mean wind speeds between 3 and 16 m s ^{? 1} at the turbine hub height. The loads are quantified as the cumulative sum of the damage equivalent load for different wind speeds that are weighted according to the wind speed and stability distribution. Four sites with a different wind speed and stability distribution are used for comparison. The turbulence and wind profile from only one site is used in the load calculations, which are then weighted according to wind speed and stability distributions at different sites. It is observed that atmospheric stability influences the tower and rotor loads. The difference in the calculated tower loads using diabatic wind conditions and those obtained assuming neutral conditions only is up to 17%, whereas the difference for the rotor loads is up to 13%. The blade loads are hardly influenced by atmospheric stability, where the difference between the calculated loads using diabatic and neutral input wind conditions is up to 3% only. The wind profiles and turbulence under diabatic conditions have contrasting influences on the loads; for example, under stable conditions, loads induced by the wind profile are larger because of increased wind shear, whereas those induced by turbulence are lower because of less turbulent energy. The tower base loads are mainly influenced by diabatic turbulence, whereas the rotor loads are influenced by diabatic wind profiles. The blade loads are influenced by both, diabatic wind profile and turbulence, that leads to nullifying the contrasting influences on the loads. The importance of using a detailed boundary‐layer wind profile model is also demonstrated. The difference in the calculated blade and rotor loads is up to 6% and 8%, respectively, when only the surface‐layer wind profile model is used in comparison with those obtained using a boundary‐layer wind profile model. Finally, a comparison of the calculated loads obtained using site‐specific and International Electrotechnical Commission (IEC) wind conditions is carried out. It is observed that the IEC loads are up to 96% larger than those obtained using site‐specific wind conditions.Copyright © 2012 John Wiley & Sons, Ltd.     

Blade load mitigation control design for a wind turbine operating in the path of vortices

As wind turbine rotor size continues to increase, load mitigation becomes an important control objective. Turbines with hub heights of nearly 100m operate in the stable, nocturnal boundary layer where coherent turbulence can be generated by atmospheric phenomena outside the surface layer. These coherent turbulent structures may contribute to blade fatigue loads that can be mitigated with advanced control algorithms. Disturbance accommodating control (DAC) methods were implemented in a wind turbine structural dynamics simulation code to mitigate transient blade load response induced by a simple, Rankine vortex in the inflow. As a best‐case scenario, a full‐state feedback controller (which included a very detailed disturbance model) showed that blade flap damage equivalent load caused by the vortex passing through the rotor could be reduced by 30% compared to one that resulted from simulation of a typical proportional‐integral (PI) controller. A realizable DAC controller that incorporates only the vertical shear component of the vortex reduced loads by 9% compared to that resulting from simulation of a PI controller. The load reduction was even greater when the vortex was superimposed over full‐field, homogeneous turbulence. DAC methods have the flexibility to incorporate properties of coherent turbulent inflow structures in the controller design to mitigate blade fatigue loads. Further work must be done to develop disturbance models as more details about the turbulent structures are identified. Copyright © 2007 John Wiley & Sons, Ltd.     

Active load alleviation potential of adaptive wind turbine blades using shape memory alloy actuators

Upscaling of wind turbine blades calls for implementation of innovative active load control concepts that will facilitate the flawless operation of the machine and reduce the fatigue and ultimate loads that hinder its service life. Based on aeroelastic simulations that prove the enhanced capabilities of combined individual pitch and individual flap control at global wind turbine scale level, a shape adaptive concept that encompasses an articulated mechanism consisting of two subparts is presented. Shape memory alloy (SMA) actuators are investigated and assessed as means to control the shape adaptive mechanism at airfoil section level in order to alleviate the developed structural loads. The concept is embedded in the trailing edge region of the blade of a 10‐MW horizontal axis wind turbine and acts as a flap mechanism. Numerical simulations are performed considering various wind velocities and morphing target shapes and trajectories for both normal and extreme turbulence conditions. The results prove the potential of the concept, since the SMA controlled actuators can accurately follow the target trajectories. Power requirements are estimated at 0.22% of the AEP of the machine, while fatigue and ultimate load reduction of the flap‐wise bending moment at the blade root is 27.6% and 7.4%, respectively.     

The influence of the wind speed profile on wind turbine performance measurements

To identify the influence of wind shear and turbulence on wind turbine performance, flat terrain wind profiles are analysed up to a height of 160 m. The profiles' shapes are found to extend from no shear to high wind shear, and on many occasions, local maxima within the profiles are also observed. Assuming a certain turbine hub height, the profiles with hub‐height wind speeds between 6 m s^?1 and 8 m s^?1 are normalized at 7 m s^?1 and grouped to a number of mean shear profiles. The energy in the profiles varies considerably for the same hub‐height wind speed. These profiles are then used as input to a Blade Element Momentum model that simulates the Siemens 3.6 MW wind turbine. The analysis is carried out as time series simulations where the electrical power is the primary characterization parameter. The results of the simulations indicate that wind speed measurements at different heights over the swept rotor area would allow the determination of the electrical power as a function of an ‘equivalent wind speed’ where wind shear and turbulence intensity are taken into account. Electrical power is found to correlate significantly better to the equivalent wind speed than to the single point hub‐height wind speed. Copyright © 2008 John Wiley & Sons, Ltd.     

Coupled multi-body dynamics and CFD for wind turbine simulation including explicit wind turbulence

A high fidelity approach for wind turbine aero-elastic simulations including explicit representation of the atmospheric wind turbulence is presented. The approach uses a dynamic overset computational fluid dynamics (CFD) code for the aerodynamics coupled with a multi-body dynamics (MBD) code for the motion responses to the aerodynamic loads. Mann's wind turbulence model was implemented into the CFD code as boundary and initial conditions. The wind turbulence model was validated by comparing the theoretical one-point spectrum for the three components of the velocity fluctuations, and by comparing the expected statistics from the CFD simulated wind turbulent field with the explicit wind turbulence inlet boundary from Mann model. Extensive simulations based on the proposed coupled approach were conducted with the conceptual NREL 5-MW offshore wind turbine in an increasing level of complexity, analyzing the turbine behavior as elasticity, wind shear and atmospheric wind turbulence are added to the simulations. Results are compared with the publicly available simulations results from OC3 participants, showing good agreement for the aerodynamic loads and blade tip deflections in time and frequency domains. Wind turbulence/turbine interaction was examined for the wake flow. It was found that explicit turbulence addition results in considerably increased wake diffusion. The coupled CFD/MBD approach can be extended to include multibody models of the shaft, bearings, gearbox and generator, resulting in a promising tool for wind turbine design under complex operational environments.     

Active wake control: An approach to optimize the lifetime operation of wind farms

The wind turbines within a wind farm impact each other's power production and loads through their wakes. Wake control strategies, aiming to reduce wake effects, receive increasing interest by both the research community and the industry. A number of recent simulation studies with high fidelity wake models indicate that wake mitigation control is a very promising concept for increasing the power production of a wind farm and/or reducing the fatigue loading on wind turbines' components. The purpose of this paper is to study the benefits of wake mitigation control in terms of lifetime power production and fatigue loading on several existing full‐scale commercial wind farms with different scale, layouts, and turbine sizes. For modeling the wake interactions, Energy Research Centre of the Netherlands' FarmFlow software is used: a 3D parabolized Navier‐Stokes code, including a k‐? turbulence model. In addition, an optimization approach is proposed that maximizes the lifetime power production, thereby incorporating the fatigue loads into the optimization criterion in terms of a lifetime extension factor.     

The simulation error caused by input loading variability in offshore wind turbine structural analysis

Stochastic representations of turbulent wind and irregular waves are used in time domain simulations of offshore wind turbines. The variability due to finite sampling of this input loading is an important source of simulation error. For the OC4 reference jacket structure with a 5 MW wind turbine, an error of 12–34% for ultimate loads and 6–12% for fatigue loads can occur with a probability of 1%, for simulations with a total simulation length of 60 min and various load cases. In terms of fatigue life, in the worst case, the lifetime of a joint was thereby overestimated by 29%. The size of this error can be critical, i.e., ultimate or fatigue limits can be exceeded, with probability depending on the choice of number of random seeds and simulation length. The analysis is based on a large simulation study with about 30,000 time domain simulations. Probability density functions of response variables are estimated and analyzed in terms of confidence intervals; i.e., how probable it is to obtain results significantly different from the expected value when using a finite number of simulations. This simulation error can be reduced to the same extent, either using several short simulations with different stochastic representations of the wind field or one long simulation with corresponding total length of the wind field. When using several short‐term simulations, it is important that ultimate and fatigue loads are calculated based on the complete, properly combined set of results, in order to prevent a systematic bias in the estimated loads. Copyright © 2014 John Wiley & Sons, Ltd.     

Fatigue design load calculations of the offshore NREL 5 MW benchmark turbine using quadrature rule techniques

A novel approach is proposed to reduce, compared with the conventional binning approach, the large number of aeroelastic code evaluations that are necessary to obtain equivalent loads acting on wind turbines. These loads describe the effect of long‐term environmental variability on the fatigue loads of a horizontal‐axis wind turbine. In particular, Design Load Case 1.2, as standardized by IEC, is considered. The approach is based on numerical integration techniques and, more specifically, quadrature rules. The quadrature rule used in this work is a recently proposed “implicit” quadrature rule, which has the main advantage that it can be constructed directly using measurements of the environment. It is demonstrated that the proposed approach yields accurate estimations of the equivalent loads using a significantly reduced number of aeroelastic model evaluations (compared with binning). Moreover, the error introduced by the seeds (introduced by averaging over random wind fields and sea states) is incorporated in the quadrature framework, yielding an even further reduction in the number of aeroelastic code evaluations. The reduction in computational time is demonstrated by assessing the fatigue loads on the NREL 5 MW reference offshore wind turbine in conjunction with measurement data obtained at the North Sea, for both a simplified and a full load case.     

Impact of different forest densities on atmospheric boundary‐layer development and wind‐turbine wake

The aim of this work is to investigate the atmospheric boundary‐layer (ABL) flow and the wind turbine wake over forests with varying leaf area densities (LAD). The forest LAD profile used in this study is based on a real forest site, Ryningsnäs, located in Sweden. The reference turbine used to model the wake is a well‐documented 5‐MW turbine, which is implemented in the simulations using an actuator line model (ALM). All simulations are carried out with openFOAM using the Reynolds averaged Navier‐Stokes (RANS) approach. Twelve forest cases with leaf area index (LAI) ranging from 0.42 to 8.5 are considered. Results show that the mean velocity decreases with increasing LAI within the forest canopy, but increases with LAI above the hub height. Meanwhile, the turbulent kinetic energy (TKE) varies nonmonotonically with forest density. The TKE increases with forest density and reaches to its maximum at an average LAI of 1.70, afterwards, it decreases gradually as the density increases. It is also observed that the forest density has a clear role in the wake development and recovery. Comparisons between no‐forest and forest cases show that the forest characteristics help in damping the added turbulence from the turbine. As a consequence, the forest with the highest upstream turbulence has the shortest wake downstream of the turbine.