Wind turbine response to parameter variation of analytic inflow vortices

As larger wind turbines are placed on taller towers, rotors frequently operate in atmospheric conditions that support organized, coherent turbulent structures. It is hypothesized that these structures have a detrimental impact on the blade fatigue life experienced by the wind turbine. These structures are extremely difficult to identify with sophisticated anemometry such as ultrasonic anemometers. This study was performed to identify the vortex characteristics that contribute to high‐amplitude cyclic blade loads, assuming that these vortices exist under certain atmospheric conditions. This study does not attempt to demonstrate the existence of these coherent turbulent structures. In order to ascertain the idealized worst‐case scenario for vortical inflow structures impinging on a wind turbine rotor, we created a simple, analytic vortex model. The Rankine vortex model assumes that the vortex core undergoes solid body rotation to avoid a singularity at the vortex centre and is surrounded by a two‐dimensional potential flow field. Using the wind turbine as a sensor and the FAST wind turbine dynamics code with limited degrees of freedom, we determined the aerodynamic loads imparted to the wind turbine by the vortex structure. We varied the size, strength, rotational direction, plane of rotation, and location of the vortex over a wide range of operating parameters. We identified the vortex conformation with the most significant effect on the blade root bending moment cyclic amplitude. Vortices with radii on the scale of the rotor diameter or smaller caused blade root bending moment cyclic amplitudes that contribute to high damage density. The rotational orientation, clockwise or counter‐clockwise, produces little difference in the bending moment response. Vortices in the XZ plane produce bending moment amplitudes significantly greater than vortices in the YZ plane. Published in 2005 by John Wiley & Sons, Ltd.     

Using Wavelet Analysis to Assess Turbulence/Rotor Interactions

Large loading events on wind turbine rotor blades are often associated with transient bursts of coherent turbulent energy in the turbine inflow. These coherent turbulent structures are identified as peaks in the three‐dimensional, instantaneous, turbulent shearing stress field. Such organized inflow structures and the accompanying rotor aeroelastic responses typically have timescales of only a few seconds and therefore do not lend themselves to analysis by conventional Fourier spectral techniques. Wavelet analysis offers the ability to study more closely the spectral decomposition of short‐period events such as the interaction of coherent turbulence with a moving rotor blade. In this paper we discuss our initial progress in the application of wavelet analysis techniques to the decomposition and interpretation of turbulence/rotor interaction. We discuss the results of using both continuous and discrete wavelet transforms for our application. Several examples are given of the techniques applied to both observed turbulence and turbine responses and those generated using numerical simulations. We found that the presence of coherent turbulent structures, as revealed by the inflow Reynolds stress field, is a major contributor to large load excursions. These bursts of coherent turbulent energy induce a broadband aeroelastic response in the turbine rotor as it passes through them. Copyright © 2001 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.     

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.     

Analysis of light detection and ranging wind speed measurements for wind turbine control

Light detection and ranging (LIDAR) systems are able to measure the speed of incoming wind before it reaches a wind turbine rotor. These preview wind measurements can be used in feedforward control systems designed to reduce turbine structural loads. However, the degree to which such preview‐based control techniques can reduce loads by reacting to turbulence depends on how accurately the incoming wind field can be measured. This study examines the accuracy of different measurement scenarios that rely on coherent continuous‐wave or pulsed Doppler LIDAR systems, in terms of root‐mean‐square measurement error, to determine their applicability to feedforward control. In particular, the impacts of measurement range, angular offset of the LIDAR beam from the wind direction, and measurement noise are studied for various wind conditions. A realistic simulation case involving a scanning LIDAR unit mounted in the spinner of a MW‐scale wind turbine is studied in depth, with emphasis on preview distances that provide minimum measurement error for a specific scan radius. Measurement error is analyzed for LIDAR‐based estimates of point wind speeds at the rotor as well as spanwise averaged blade effective wind speeds. The impact of turbulence structures with high coherent turbulent kinetic energy on measurement error is discussed as well. Copyright © 2013 John Wiley & Sons, Ltd.     

Wind turbine robust disturbance accommodating control using non-smooth H∞ optimization

Disturbance accommodating control (DAC) has been developed in the last decades for wind turbines to control the rotor/generator speed and to reduce structural loads. The method allows accommodating unknown disturbance effects by using the combination of disturbance observers and disturbance rejection controllers. The actual main problem of DAC is to define suitable disturbance observer and controller gain matrices to achieve the desired overall performance including turbine speed regulation in combination with structural load mitigation. The disturbance rejection controller is often designed and tuned separately for individual applications and operating conditions. The closed-loop system stability and uncertainties due to the use of the linearized reduced-order model in controller synthesis procedure are not fully considered. This paper introduces a method to design DAC by optimizing the observer and controller parameters simultaneously to guarantee system performance respecting to structural loads mitigation, power regulation, and robustness. To eliminate the rotor speed control steady-state error due to model uncertainties, partial integral action is included. Simulation results using NREL reference wind turbine models show that the proposed method successfully regulates the rotor speed without error despite the presence of the model uncertainties. Structural loads are also reduced using proposed method compared to DAC designed by Kronecker product method. The proposed approach is able to define a stable and robust DAC controller by solving a non-smooth H_∞ optimization problem with structure and stability constraints.     

极端风况下双转子风力机降载复合控制策略

为降低双转子风力机在极端风况下的大波动载荷,基于双转子风力机气动与控制仿真系统,提出了基于独立变桨自抗扰控制器和偏航模糊控制器的降载复合控制策略,并分析了正常风况和极端风况下该策略的控制效果。结果表明：与传统PID独立变桨控制相比,在极端运行阵风和极端湍流模型下,独立变桨自抗扰控制方法使叶根挥舞弯矩标准差减小18%以上;与传统恒速偏航控制相比,在极端风向变化下,偏航模糊控制方法使偏航轴承滚动力矩标准差减小约27%。降载复合控制策略有效降低了极端风况下双转子风力机的大载荷,抑制了功率波动。     

Preventing wind turbine overspeed in highly turbulent wind events using disturbance accommodating control and light detection and ranging

Light detection and ranging (LIDAR) systems can be used to provide wind inflow information to a wind turbine controller before the wind reaches the turbine. Both fatigue and extreme load reduction are possible as a result; in this research, we propose a LIDAR‐based controller designed to prevent emergency shutdowns caused by rotor overspeed. This switching controller consists of a disturbance accommodating control (DAC)‐based baseline controller and a different DAC linearized about a reduced generator speed for extreme events, also referred to as an extreme event controller. Switching between the controllers was performed using linear interpolation over various transition times, depending on how early the extreme event could be detected. If a gust of wind is detected using LIDAR measurements evaluated by a one‐sided cumulative summation algorithm, a relatively long transition time can be used. Switching can also be based on a large output estimation error, ε_y, in which case the transition time is shorter. Once the extreme event passed, control is switched from the extreme event controller back to the baseline DAC. This switching controller resulted in fewer overspeeds when compared with the modified baseline controller, which is a gain scheduled DAC. By preventing overspeeds, the switching controller increased the mean power the wind turbine generated over a simulated 10 min period. Copyright © 2014 John Wiley & Sons, Ltd.     

Simulating Feedback Linearization control of wind turbines using high‐order models

As wind turbines are becoming larger, wind turbine control must now encompass load control objectives as well as power and speed control to achieve a low cost of energy. Due to the inherent non‐linearities in a wind turbine system, the use of non‐linear model‐based controllers has the potential to increase control performance. A non‐linear feedback linearization controller with an Extended Kalman Filter is successfully used to control a FAST model of the controls advanced research turbine with active blade, tower and drive‐train dynamics in above rated wind conditions. The controller exhibits reductions in low speed shaft fatigue damage equivalent loads, power regulation and speed regulation when compared to a Gain Scheduled Proportional Integral controller, designed for speed regulation alone. The feedback linearization controller shows better rotor speed regulation than a Linear Quadratic Regulator (LQR) at close to rated wind speeds, but poorer rotor speed regulation at higher wind speeds. This is due to modeling inaccuracies and the addition of unmodeled dynamics during simulation. Similar performance between the feedback linearization controller and the LQR in reducing drive‐train fatigue damage and power regulation is observed. Improvements in control performance may be achieved through increasing the accuracy of the non‐linear model used for controller design. Copyright © 2009 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.     

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.     

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.     

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.     

Nonlinear model predictive control of wind turbines using LIDAR

LIDAR systems are able to provide preview information of wind disturbances at various distances in front of wind turbines. This technology paves the way for new control concepts in wind energy such as feedforward control and model predictive control. This paper compares a nonlinear model predictive controller with a baseline controller, showing the advantages of using the wind predictions in the optimization problem to reduce wind turbine extreme and fatigue loads on tower and blades as well as to limit the pitch rates. The wind information is obtained by a detailed simulation of a LIDAR system. The controller design is evaluated and tested in a simulation environment with coherent gusts and a set of turbulent wind fields using a detailed aeroelastic model of the wind turbine over the full operation region. Results show promising load reduction up to 50% for extreme gusts and 30% for lifetime fatigue loads without negative impact on overall energy production. This controller can be considered as an upper bound for other LIDAR assisted controllers that are more suited for real time applications. Copyright © 2012 John Wiley & Sons, Ltd.     

Investigation of the theoretical load alleviation potential using trailing edge flaps controlled by inflow data

A novel control concept for fatigue load reduction with trailing edge flaps based on the measurement of the inflow locally on the blade was presented. The investigation was conducted with the aeroelastic code HAWC2. The aerodynamic modelling in the code is based on blade element momentum theory. The simulations were carried out for the NREL 5MW reference wind turbine, and the mean wind speed at hub height was 8 m s^?1. The turbine was operated with fixed rotational speed. The energy at the blade is concentrated in spectral bands centred at multiples of the rotational frequency up to three times the rotational frequency. The highest fatigue load reduction was achieved when the inflow sensor was placed at the outer parts of the blade. In the best case, the reduction of the local fatigue loads induced by the blade sectional normal force was 60%. The control method gave the highest fatigue load reductions in conditions with strong wind shear. The demands for the flap actuator in terms of deflection angles was ±10°. The requirements in terms of the flap deflection velocity depend mainly on the inflow turbulence intensity. The maximum value was ±40°s^?1 for 20% inflow turbulence intensity. Unsteady aerodynamic effects seem to be negligible. 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.     

On the proof of concept of a ‘Smart’ wind turbine rotor blade for load alleviation

The trend with offshore wind turbines is to increase the rotor diameter as much as possible to decrease the costs per kilowatt‐hour. The increasing dimensions have led to the relative increase of the loads on the wind turbine structure. Because of the increasing rotor size and the spatial load variations along the blade, it is necessary to react to turbulence in a more detailed way; each blade separately and at several separate radial distances. In this paper, a proof of concept study is performed to show the feasibility of the load alleviation abilities of a ‘Smart’ blade, i.e. a blade equipped with a number of control devices that locally change the lift profile on the blade, combined with appropriate sensors and feedback controllers. Theoretical and experimental models are developed of a scaled non‐rotating rotor blade which is equipped with two trailing edge flaps and strain sensors to facilitate feedback control. A pitch actuator is used to induce disturbances with a similar character as a gust or turbulence. A feedback controller based on classical loop shaping is designed that minimizes the root bending moment in the flapping direction. We show that with appropriate control techniques, the loads for periodic disturbances and for turbulence generated disturbances can be reduced up to 90 and 55%, respectively. Copyright © 2008 John Wiley & Sons, Ltd.     

Individual blade pitch control of floating offshore wind turbines

Floating wind turbines offer a feasible solution for going further offshore into deeper waters. However, using a floating platform introduces additional motions that must be taken into account in the design stage. Therefore, the control system becomes an important component in controlling these motions. Several controllers have been developed specifically for floating wind turbines. Some controllers were designed to avoid structural resonance, while others were used to regulate rotor speed and platform pitching. The development of a periodic state space controller that utilizes individual blade pitching to improve power output and reduce platform motions in above rated wind speed region is presented. Individual blade pitching creates asymmetric aerodynamic loads in addition to the symmetric loads created by collective blade pitching to increase the platform restoring moments. Simulation results using a high‐fidelity non‐linear turbine model show that the individual blade pitch controller reduces power fluctuations, platform rolling rate and platform pitching rate by 44%, 39% and 43%, respectively, relative to a baseline controller (gain scheduled proportional–integral blade pitch controller) developed specifically for floating wind turbine systems. Turbine fatigue loads were also reduced; tower side–side fatigue loads were reduced by 39%. Copyright © 2009 John Wiley & Sons, Ltd.     

Load reduction on a clipper liberty wind turbine with linear parameter‐varying individual blade pitch control

The increasing size of modern wind turbines also increases the structural loads caused by effects such as turbulence or asymmetries in the inflowing wind field. Consequently, the use of advanced control algorithms for active load reduction has become a relevant part of current wind turbine control systems. In this paper, an individual blade pitch control law is designed using multivariable linear parameter‐varying control techniques. It reduces the structural loads both on the rotating and non‐rotating parts of the turbine. Classical individual blade pitch control strategies rely on single‐control loops with low bandwidth. The proposed approach makes it possible to use a higher bandwidth since it accounts for coupling at higher frequencies. A controller is designed for the utility‐scale 2.5 MW Liberty research turbine operated by the University of Minnesota. Stability and performance are verified using the high‐fidelity nonlinear simulation and baseline controllers that were directly obtained from the manufacturer. Copyright © 2017 John Wiley & Sons, Ltd.