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.     

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.     

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.     

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.     

Wind gust detection and load mitigation using artificial neural networks assisted control

The design of a wind turbine implies the simulation of definite conditions as specified in the standards. Among those operational conditions, rare events such as extreme gusts or external faults are included, which may cause high structural loads. Such extreme design load cases usually drive the design of some of the main components of the wind turbine: tower, blades and mainframe. Two different strategies are hence presented to mitigate the loads, deriving from extreme load cases, on the basis of the detection of wind gusts by means of ad hoc synthesized artificial neural networks. This tool is embedded into the main control algorithm and allows it to detect the gust in advance, to anticipate the control reaction, and by doing so reducing extreme loads. One of the strategies performs a controlled stop when wind gust is detected. The other rides through wind gusts without stopping, i.e., without affecting the wind turbine normal operation. Aeroelastic simulations of the Alstom Wind's wind turbines using these techniques have shown significant reductions in the extreme loads for all standard IEC 61400‐1, edition 2 DLC 1.6 cases. In particular, the overall ultimate loads are largely reduced for blade root and tower base bending moments, with a direct impact on the structural design of those components. Copyright © 2013 John Wiley & Sons, Ltd.     

A Monte Carlo simulation study of wind turbine loads in thunderstorm downbursts

The simulation of thunderstorm downbursts and associated loads on a utility‐scale wind turbine is the focus of this study. Using a deterministic–stochastic hybrid model, downburst‐related wind fields are generated separately from non‐turbulent and turbulent parts. The non‐turbulent part builds on available analytical models developed from field data that include recorded downburst events; the turbulent part is simulated as a stochastic process using standard turbulence power spectral density functions and coherence functions adjusted by information on parameters such as the downburst's translation velocity. Key thunderstorm downburst‐related parameters include the maximum radial velocity, the height and radial distance to the maximum radial velocity, the downburst intensity, the downburst translation velocity and the downburst translation direction. In addition, the streamwise ambient (environmental) velocity and the downburst touchdown location relative to the wind turbine are also important in turbine load computation. A utility‐scale 5‐MW wind turbine model is selected, and loads are generated using stochastic simulation of the aeroelastic response. Information available in the literature on recorded downbursts is used to define the cases studied. A single downburst simulation and associated turbine response simulation is first discussed to illustrate loads computation and highlight downburst‐related parameters of interest. Next, a Monte Carlo simulation study is performed to investigate the influence of touchdown locations and translation direction on turbine extreme loads. Copyright © 2014 John Wiley & Sons, Ltd.     

Wind turbine extreme gust control

This paper focuses on the problem of extreme wind gust and direction change recognition (EG&DR) and control (EEC). An extreme wind gust with direction change can lead to large loads on the turbine (causing fatigue) and unnecessary turbine shutdowns by the supervisory system caused by rotor overspeed. The proposed EG&DR algorithm is based on a non‐linear observer (extended Kalman filter) that estimates the oblique wind inflow angle and the blade effective wind speed signals, which are then used by a detection algorithm (cumulative sum test) to recognize extreme events. The non‐linear observer requires that blade root bending moments measurements (in‐plane and out‐of‐plane) are available. Once an extreme event is detected, an EEC algorithm is activated that: (i) tries to prevent the rotor speed from exceeding the overspeed limit by fast collective blade pitching; and (ii) reduces 1p blade loads by means of individual pitch control algorithm, designed in an ?_∞ optimal control setting. The method is demonstrated on a complex non‐linear test turbine model. Copyright © 2009 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.     

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.     

Overcoming fundamental limitations of wind turbine individual blade pitch control with inflow sensors

Individual pitch control (IPC) provides an important means of attenuating harmful fatigue and extreme loads upon the load bearing structures of a wind turbine. Conventional IPC architectures determine the additional pitch demand signals required for load mitigation in response to measurements of the flap‐wise blade‐root bending moments. However, the performance of such architectures is fundamentally limited by bandwidth constraints imposed by the blade dynamics. Seeking to overcome this problem, we present a simple solution based upon a local blade inflow measurement on each blade. Importantly, this extra measurement enables the implementation of an additional cascaded feedback controller that overcomes the existing IPC performance limitation and hence yields significantly improved load reductions. Numerical demonstration upon a high‐fidelity and nonlinear wind turbine model reveals (1) 60% reduction in the amplitude of the dominant 1P fatigue loads and (2) 59% reduction in the amplitude of extreme wind shear‐induced blade loads, compared with a conventional IPC controller with the same robust stability margin. This paper therefore represents a significant alternative to wind turbine IPC load mitigation as compared with light detection and ranging‐based feedforward control approaches.     

Effects of wind shear on wind turbine rotor loads and planetary bearing reliability

Recent studies suggest that wind shear and the resulting pitch moments increase bearing loads and thereby contribute to premature wind turbine gearbox failure. In this paper, we use momentum‐based modeling approaches to predict the pitch moments from wind shear. The non‐dimensionalized results, which have been validated against accepted aeroelastic results, can be used to determine thrust force, pitch moment and power of a general rotor as a function of the wind shear exponent. Even in extreme wind shear (m = 1), the actual thrust force and power for a typical turbine (R* < 0.5) were within 8% and 20% of the nominal values (those without wind shear), respectively. The mean pitch moment increased monotonically with turbine thrust, rotor radius and wind shear exponent. For extreme wind shear (m = 1) on a typical turbine (R* = 0.5), the mean pitch moment is ~25% the product of thrust force and rotor radius. Analysis of wind shear for a typical 750 kW turbine revealed that wind shear does not significantly affect bearing loads because it counteracts the effects of rotor weight. Furthermore, even though general pitch moments did significantly increase bearing loads, they were found to be unlikely to cause bearing fatigue. Analyses of more common low wind‐speed cases suggest that bearing under‐loading and wear are more likely to contribute to premature bearing failure than overloading and classical surface contact fatigue. Copyright © 2015 John Wiley & Sons, Ltd.     

Validation of the dynamic wake meander model for loads and power production in the Egmond aan Zee wind farm

This paper investigates wake effects on load and power production by using the dynamic wake meander (DWM) model implemented in the aeroelastic code HAWC2. The instationary wind farm flow characteristics are modeled by treating the wind turbine wakes as passive tracers transported downstream using a meandering process driven by the low frequent cross‐wind turbulence components. The model complex is validated by comparing simulated and measured loads for the Dutch Egmond aan Zee wind farm consisting of 36 Vestas V90 turbine located outside the coast of the Netherlands. Loads and production are compared for two distinct wind directions—a free wind situation from the dominating southwest and a full wake situation from northwest, where the observed turbine is operating in wake from five turbines in a row with 7D spacing. The measurements have a very high quality, allowing for detailed comparison of both fatigue and min–mean–max loads for blade root flap, tower yaw and tower bottom bending moments, respectively. Since the observed turbine is located deep inside a row of turbines, a new method on how to handle multiple wakes interaction is proposed. The agreement between measurements and simulations is excellent regarding power production in both free and wake sector, and a very good agreement is seen for the load comparisons too. This enables the conclusion that wake meandering, caused by large scale ambient turbulence, is indeed an important contribution to wake loading in wind farms. Copyright © 2012 John Wiley & Sons, Ltd.     

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.     

Teeter design for lowest extreme loads during end impacts

Two bladed wind turbines are discussed as a possible turbine alternative for offshore use as they show a potential to save cost of energy. But compared to three‐bladed turbines, their dynamic behavior is much more challenging. A possible solution to handle these larger dynamic loads is the use of a teeter hinge, which can significantly reduce fatigue loads. In contrast to that, extreme loads, coming from teeter end impacts, are often described as a problem for teetered turbines. There are different design parameters of the teeter system of a turbine, which have an influence on extreme loads during teeter end impacts. Despite numerous studies on teeter movement and load reduction potentials of operational loads, scientific literature does not give information about suitable load‐reducing combinations of teeter design parameters and their influence on extreme loads. This paper, which is a summary of a PhD thesis, 1 analyses which combination of teeter parameters has the largest load‐reducing influence on extreme loads. Aeroelastic load simulations of the teetered turbine CART2 from the NREL test site and one of today's commercial two‐bladed turbines, the SCD3MW from aerodyn (both pitch controlled upwind turbines), will be used.     

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.     

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.     

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.     

Wind turbine measurement technique—an open laboratory for educational purposes

As part of the International Master of Science Programme in Wind Energy at the Technical University of Denmark (DTU), a complete interactive wind turbine measurement laboratory (WTMLAB) was developed. A 500kW stall regulated wind turbine was instrumented with sensors for recording (i) turbine operational parameters, (ii) meteorological conditions, (iii) electrical quantities and (iv) mechanical loads. The data acquisition system was PC based, and it was combined with a MySQL® database for data management. The system enabled online access for real‐time recordings, which were used both for demonstration purposes, for individual student exercises and for scientific investigations. The automatic data acquisition system furthermore enabled recording of extreme and fatigue loads together with a long‐term event registration. Long‐term registration of wind turbine loads resulted in a unique database of non‐commercial time series, which would be available for practicing fatigue calculations and extreme load estimation in basic wind turbine courses. Power quality analysis was carried out based on high‐speed‐sampled, three‐phase voltage and current signals. The wide spectrum of sensors enabled a detailed study of the correlation between meteorological, mechanical and electrical quantities. Measurements were recorded with a PC placed at the wind turbine site at Risø. The PC could be remotely controlled from DTU, which gave the students the opportunity to work on an operating wind turbine. The WTMLAB was included in a new course entitled Wind Turbine Measurement Techniques. Copyright © 2007 John Wiley & Sons, Ltd.     

Short‐term extreme response analysis of a jacket supporting an offshore wind turbine

Wind turbines must be designed in such a way that they can survive in extreme environmental conditions. Therefore, it is important to accurately estimate the extreme design loads. This paper deals with a recently proposed method for obtaining short‐term extreme values for the dynamic responses of offshore fixed wind turbines. The 5 MW NREL wind turbine is mounted on a jacket structure (92 m high) at a water depth of 70 m at a northern offshore site in the North Sea. The hub height is 67 m above tower base or top of the jacket, i.e. 89 m above mean water level. The turbine response is numerically obtained by using the aerodynamic software HAWC2 and the hydrodynamic software USFOS . Two critical responses are discussed, the base shear force and the bending moment at the bottom of the jacket. The extreme structural responses are considered for wave‐induced and wind‐induced loads for a 100 year return‐period harsh metocean condition with a 14.0 m significant wave height, a 16 s peak spectral period, a 50 m s ^{? 1} (10 min average) wind speed (at the hub) and a turbulence intensity of 0.1 for a parked wind turbine. After performing the 10 min nonlinear dynamic simulations, a recently proposed extrapolation method is used for obtaining the extreme values of those responses over a period of 3 h. The sensitivity of the extremes to sample size is also studied. The extreme value statistics are estimated from the empirical mean upcrossing rates. This method together with other frequently used methods (i.e. the Weibull tail method and the global maxima method) is compared with the 3 h extreme values obtained directly from the time‐domain simulations. Copyright © 2012 John Wiley & Sons, Ltd.