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DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence B - Raw Data

Sequences B, C, and D: Downwind Baseline (F), Downwind Low Pitch (F), Downwind High Pitch (F) This test sequence used a downwind, teetered turbine with a 3.4° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Yaw angles of ±180° were achieved at low wind speeds, and yaw angles of -20° to 10° were achieved for high wind speeds. The blade tip pitch was 3° for sequence B, 0° for sequence C, and 6° for sequence D. These three sequences were interleaved during testing because the pitch angle change was easily made by the turbine operator. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected.

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DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence C - Raw Data

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DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence D - Raw Data

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DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence L - Raw Data

Sequence L: Step AOA, Parked (P) This sequence was designed to quantify the 3-D blade static angle-of-attack response in the absence of rotational influences by varying the blade pitch angle. This test sequence used an upwind, rigid turbine with a 0° cone angle. Wind speeds of 20 m/s and 30 m/s were used, and all data were collected at a yaw angle of 0°. The rotor was parked with the instrumented blade fixed at 0° azimuth, and the rotor lock was installed (see Appendix A). Blade and probe pressure measurements were collected. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to -99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. The blade pitch angle ramped continuously at 0.18°/s over a wide range of increasing and decreasing pitch angles. A step sequence was also performed. The blade pitch was stepped 5°, the flow was allowed to stabilize, and the pitch angle was held for 8 seconds. Then the pitch angle step was repeated. Again, a wide range of pitch angles was obtained, both increasing and decreasing. The file lengths for this sequence varied from 5 to 10 minutes, depending on the pitch angle range. The file name convention used the initial letter L followed by two digits specifying wind speed, followed by 00 for yaw angle, followed by RU, RD, or ST, followed by the repetition digit. The angle-of-attack motion was differentiated by RU (ramp up), RD (ramp down), and ST (step down, then step up). This sequence is related to sequences K and R.

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DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence N - Raw Data

Sequence N: Sin AOA, Rotating (P) This sequence was designed to quantify the blade 3-D unsteady aerodynamic response in the presence of rotational influences by varying blade pitch angle. Test sequence N used an upwind, rigid turbine with a 0° cone angle. The wind speed was 15 m/s, and the yaw angle was 0° throughout the sequence. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. Sinusoidal angle-of-attack histories were designed to emulate 2-D S809 dynamic data obtained at the Ohio State University (OSU) wind tunnel (Reuss Ramsey et al. 1995) and the 1P yawed flow angle-of-attack variations the turbine could be expected to encounter in routine operation. The reduced frequency (K), mean angle of attack (αm), and oscillation amplitude (αω) were computed for each of the five primary span locations. The file lengths varied according to the time required to complete 40 oscillations at the specified frequency. The file name convention used the sequence designation N, followed by two digits for the span location (30, 47, 63, 80, or 95), followed by two digits representing the condition specified in the test matrix, followed by the repetition digit. Due to time constraints, most of the test conditions corresponding to the 63% span location were eliminated. Test points with a static pitch angle of 3° were collected throughout the sequence to ascertain instrumentation fidelity.

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DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence O - Raw Data

Sequence O: Sin AOA, Parked (P) This sequence was designed to quantify the blade 3-D unsteady aerodynamic response in the absence of rotational influences by varying blade pitch angle. This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 18.9 m/s to 39.3 m/s, and the yaw angle was 0° throughout the sequence. The rotor was parked with the instrumented blade fixed at 0° azimuth, and the rotor lock was installed (see Appendix A). Blade and probe pressure measurements were collected. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to -99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. Sinusoidal angle-of-attack histories were designed to emulate 2-D S809 dynamic data obtained at the OSU wind tunnel (Reuss Ramsey et al. 1995) as well as 1P yawed flow angle-of-attack variations the turbine could be expected to encounter in routine operation. The reduced frequency (K), mean angle of attack (αm), and oscillation amplitude (αω) were computed for each of the five primary span locations. The file lengths varied according to the time required to complete 40 oscillations at the specified frequency. The file name convention used the sequence designation O, followed by two digits for the span location (30, 47, 80, or 95), followed by two digits representing the condition specified in the test matrix, followed by the repetition digit. Due to time constraints, the test conditions corresponding to the 63% span location were eliminated. Test points with a static pitch angle of 3° were collected throughout the sequence to ascertain instrumentation fidelity.

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DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence P - Raw Data

Sequence P: Wake Flow Visualization, Upwind (P) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 15 m/s. Yaw angles of 0° to –60° were achieved. The blade tip pitch was 3°. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. The aluminum blade tip designed to contain a smoke generator was installed, and counterweights were installed in the non-instrumented blade tip to compensate. The turbine was positioned at the appropriate yaw angle, and the smoke generator was ignited remotely. The campaign duration was 3 minutes for all tests except P1000000, which was 2 minutes. The file name convention was the standard format except for P10000A0, which indicated a 3° pitch angle. File P1000000 used a 12° pitch angle. After these two campaigns were collected, it was determined that all subsequent data should be collected with a 3° pitch angle. Pressure data were not acquired during this sequence, so all associated data values were flagged as not applicable by setting the measured values in the data file to 0.000 Pa. Corresponding pressure data are available from Sequence H for the 3° pitch angle test points. Flow visualization data obtained from wall- and ceiling-mounted video cameras were recorded to videotape. The camera locations and calibration procedures are described in Appendix J.

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DOE OSTI2021

Assessment of the Amplification Factor Transport Transition Model for High-Mach Number Flows

In its present state, the Amplification Factor Transport (AFT) model provides an efficient alternative for high-fidelity stability methods for complex geometries subject to low-speed conditions considered in the industrial-production CFD environment. Its performance has not yet been documented for the typical transition scenarios in hypersonic conditions. The goal of the present study is to apply the AFT model to a yawed- and flared-cone configuration, for which the laminar flows respectively support the crossflow and second-mode instability mechanisms, and to compare the amplification results against high-fidelity results computed with Linear Parabolized Stability Equations (LPSE). High-resolution viscous-flow solutions are provided with OVERFLOW and COFFE. For the yawed-cone case, the AFT model yields the largest amplification in a region of the flow where the expected crossflow instability is not amplified (in the leeward symmetry plane) according to LPSE. For the flared-cone case with a wall-temperature slightly lower than the adiabatic value, the AFT model yields extremely large amplification factors (in excess of 100), exceeding the computed LPSE amplification of second-mode instability results by a factor 14. Upon considering a cold-wall condition, the model shows much smaller amplification factors, which is the opposite with respect to the expected behavior of the second mode. The AFT model does not adequately capture the crossflow and second-mode instability mechanisms in its present state.

Groot, Koen J.↗

DOE OSTI2023

Sensitivity Analysis of Modal Parameters of a Jacket Offshore Wind Turbine to Operational Conditions

Accurate estimation of offshore wind turbine (OWT) modal parameters has a prominent effect on the design loads, lifetime prediction, and dynamic response of the system. Modal parameters can vary during the operation of OWTs. This paper studies the variation and sensitivity analysis of an OWT’s modal parameters with respect to operational and environmental conditions. Three finite element models of a jacket-supported OWT at the Block Island Wind Farm are created within the OpenSees, SAP2000, and OpenFAST platforms and validated using experimental measurements. The OpenFAST model is used to simulate the modal parameters of the turbine under various wind speed, rotor speed, power, yaw angle, mean sea level, blade pitch angle, and soil spring values. The model-predicted modal parameters of the first fore–aft (FA) and side–side (SS) modes are compared to those identified from experimental measurements. Results from the simulations show that the first FA natural frequency and damping ratio mostly depend on the rotor speed and wind speed, respectively, while yaw angle and mean sea level do not have a visible effect. It is observed that there is about 8% stiffening in the first FA frequency and an aerodynamic damping of 7.5% during the operation of the OWT.

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DOE OSTI2025

Comparison of wind farm control strategies under realistic offshore wind conditions: turbine quantities of interest

Abstract. Wind farm flow control is a strategy to increase the efficiency and therefore lower the levelized cost of energy of a wind farm. This is done using turbine settings such as the yaw angle, blade pitch angles, or generator torque to manipulate the flow behind the turbine, affecting downstream turbines in the farm. Two inherently different wind farm flow control methods have been identified in the literature: wake steering and wake mixing. This paper focuses on comparing the turbine quantities of interest between these methods for a simple two-turbine wind farm setup, while a companion article (Brown et al., 2025) focuses on the wake quantities of interest for a single wind turbine setup. Both papers use the same set of wind farm simulations based on high-fidelity large-eddy simulations (LESs) coupled with OpenFAST turbine models. First, precursor simulations are executed in order to match wind conditions measured with lidars in an offshore wind farm off the east coast of the USA. These measurements show general wind conditions that exhibit substantially higher vertical wind shear and veer than any of the LES studies performed with wind farm flow control strategies currently available in the literature. The precursors are used to evaluate the effectiveness of the control methods. In the LES, the wind veer leads to highly skewed wakes, which have considerable influence on the power uplift of wind farm flow control strategies. In addition to a baseline controller, four different control strategies, each of which uses either pitch or yaw control, are performed on the upstream turbine of a simple two-turbine wind farm. Assuming that the wind direction is known and constant over time, the simulations show that wake steering is generally the superior wind farm flow control strategy, considering both wind farm power production and turbine damage equivalent loads when substantial wind veer is present. This result is consistent over different wind speeds and wind directions. On the other hand, for similar wind conditions with lower veer, wake mixing was found to yield the highest power production, although at the expense of generally higher loads. This leads us to conclude that the effect of wind veer, which has so far not usually been considered, can not be neglected when determining the optimal wind farm flow control strategy.

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DOE OSTI2021

Control-Oriented Model for Secondary Effects of Wake Steering

This paper presents a model to incorporate the secondary effects of wake steering in large arrays of turbines. Previous models have focused on the aerodynamic interaction of wake steering between two turbines. The model proposed in this paper builds on these models to include yaw-induced wake recovery and secondary steering seen in large arrays of turbines when wake steering is performed. Turbines operating in yaw-misaligned conditions generate counter-rotating vortices that entrain momentum and contribute to the deformation and deflection of the wake at downstream turbines. Rows of turbines can compound the effects of wake steering that benefit turbines far downstream. This model quantifies these effects and demonstrates that wake steering has greater potential to increase the performance of a wind farm due to these counter-rotating vortices especially for large rows of turbines. This is validated using numerous large-eddy simulations for three-turbine, five-turbine, and wind farm scenarios.

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DOE OSTI2023

Progress in the validation of rotor aerodynamic codes using field data

Within the framework of the fourth phase of the International Energy Agency (IEA) Wind Task 29, a large comparison exercise between measurements and aeroelastic simulations has been carried out featuring three simulation cases in axial, sheared and yawed inflow conditions. Results were obtained from more than 19 simulation tools originating from 12 institutes, ranging in fidelity from blade element momentum (BEM) to computational fluid dynamics (CFDs) and compared to state-of-the-art field measurements from the 2 MW DanAero turbine. More than 15 different variable types ranging from lifting-line variables to blade surface pressures, loads and velocities have been compared for the different conditions, resulting in over 250 comparison plots. The result is a unique insight into the current status and accuracy of rotor aerodynamic modeling. For axial flow conditions, a good agreement was found between the various code types, where a dedicated grid sensitivity study was necessary for the CFD simulations. However, compared to wind tunnel experiments on rotors featuring controlled conditions, it remains a challenge to achieve good agreement of absolute levels between simulations and measurements in the field. For sheared inflow conditions, uncertainties due to rotational and unsteady effects on airfoil data result in the CFD predictions standing out above the codes that need input of sectional airfoil data. However, it was demonstrated that using CFD-synthesized airfoil data is an effective means to bypass this shortcoming. For yawed flow conditions, it was observed that modeling of the skewed wake effect is still problematic for BEM codes where CFD and free vortex wake codes inherently model the underlying physics correctly. The next step is a comparison in turbulent inflow conditions, which is featured in IEA Wind Task 47. Doing this analysis in cooperation under the auspices of the IEA Wind Technology Collaboration Program (TCP) has led to many mutual benefits for the participants. The large size of the consortium brought ample manpower for the analysis where the learning process by combining several complementary experiences and modeling techniques gave valuable insights that could not be found when the analysis is carried out individually.

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DOE OSTI2024

Measurement-driven large-eddy simulations of a diurnal cycle during a wake-steering field campaign

Abstract. High-fidelity flow modeling with data assimilation enables accurate representation of the wind farm operating environment under realistic, nonstationary atmospheric conditions. Capturing the temporal evolution of the turbulent atmospheric boundary layer is critical to understanding the behavior of wind turbines under operating conditions with simultaneously varying inflow and control inputs. This paper has three parts: the identification of a case study during a field evaluation of wake steering; the development of a tailored mesoscale-to-microscale coupling strategy that resolved local flow conditions within a large-eddy simulation (LES), using observations that did not completely capture the wind and temperature fields throughout the simulation domain; and the application of this coupling strategy to validate high-fidelity aeroelastic predictions of turbine performance and wake interactions with and without wake steering. The case study spans 4.5 h after midnight local time, during which wake steering was toggled on and off five times, achieving yaw offset angles ranging from 0 to 17°. To resolve nonstationary nighttime conditions that exhibited shear instabilities, the turbulence field was evolved starting from the diurnal cycle of the previous day. These background conditions were then used to drive wind farm simulations with two different models: an LES with actuator disk turbines and a steady-state engineering wake model. Subsequent analysis identified two representative periods during which the up- and downstream turbines were most nearly aligned with the mean wind direction and had observed yaw offsets of 0 and 15°. Both periods corresponded to partial waking on the downstream turbine, which had errors in the LES-predicted power of 4 % and 6 %, with and without wake steering. The LES was also able to capture conditions during which an upstream turbine wake induced a speedup at a downstream turbine and increased power production by up to 13 %.

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DOE OSTI2022

Impacts of wind field characteristics and non-steady deterministic wind events on time-varying main-bearing loads

Abstract. This work considers the characteristics and drivers of the loads experienced by wind turbine main bearings. Simplified load response models of two different hub and main-bearing configurations are presented, representative of both inverting direct-drive and four-point-mounted geared drivetrains. The influences of deterministic wind field characteristics, such as wind speed, shear, yaw offset, and veer, on the bearing load patterns are then investigated for similarity scaled 5, 7.5, and 10 MW reference wind turbine models. Main-bearing load response in cases of deterministic gusts and extreme changes in wind direction are also considered for the 5 MW model. Perhaps surprisingly, veer is identified as an important driver of main-bearing load fluctuations. Upscaling results indicate that similar behaviour holds as turbines become larger, but with mean loads and load fluctuation levels increasing at least cubically with the turbine rotor radius. Strong links between turbine control and main-bearing load response are also observed.

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DOE OSTI2020

Assessing the blockage effect of wind turbines and wind farms using an analytical vortex model

Wind farm blockage effects are currently neglected in the prediction of wind farm energy yield, typically leading to an overestimation of the production. This work presents a novel method to assess wind farm production, while accounting for blockage effects. We apply a vortex model, based on a cylindrical wake, to assess induction effects. We present variations of the model to account for finite wake length, finite tip-speed ratios, and the proximity to the ground. The results are applied to single rotors in aligned and yawed conditions and to different wind farm layouts. We provide far-field approximations for faster estimates of the velocity field. Further, this article includes a new methodology to couple the induction model to engineering wake models, such as the ones present in the FLOw Redirection and Induction in Steady State (FLORIS). We compare the results to actuator disk simulations for various operating conditions of a single turbine and different wind farm layouts. We found that the mean relative error of the model in the induction zone is typically around 0.2% compared with actuator disk simulations. The computational time of the velocity field using the analytical vortex model is three orders of magnitude less than the one obtained with the actuator disk simulation.

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DOE OSTI2021

Challenges, opportunities, and a research roadmap for downwind wind turbines

This study investigates the challenges and opportunities presented by downwind wind turbines and offers a roadmap of future research pathways to maximize their potential. Multidisciplinary design, analysis, and optimization comparison studies between upwind and downwind configurations on a modern 10-MW offshore wind turbine are presented to support the discussion. On one hand, the downwind rotor is found to consistently have a smaller swept area under loading. As a result, the downwind design produces less annual energy production (-1.2%). On the other hand, lighter blades for the downwind configuration lead to lower capital costs (-1.7%), so there is little difference in the levelized cost of energy between the two. Key ultimate and fatigue loads are compared, with some values increasing in the downwind configuration, while others decrease. The impact of a downwind configuration on the tower and the impacts of cone and tilt angles and free-yaw system on the levelized cost of energy are also investigated. The results show a mix of some advantages and disadvantages. Given these results, four areas of research in advanced controls, highly tilted rotors, higher fidelity aerodynamic models, and floating wind are proposed for downwind wind turbines.

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DOE OSTI2021

Design of a 3.4-MW wind turbine with integrated plasma actuator-based load control

Historically, cost reduction in wind energy has been accomplished by increasing hub heights and rotor diameters to capture more energy per turbine. The growth in rotor and turbine costs with increasing turbine sizes is also driven by the additional structure that must be added to withstand unsteady aerodynamic loads caused by turbulence, gusts, wind shear, misaligned yaw, upwind wakes, and the tower shadow. In this paper, we present a holistic design solution to integrate active load control using a controllable Gurney flap based on plasma actuators. We illustrate the design solution for a land-based 3.4-MW wind turbine rotor. Comparisons to a baseline reference 3.4-MW wind turbine show significant load reduction (15–18% DEL reduction for flap-wise blade root moments), rotor mass reduction (5–8%), and LCOE reduction (1.16–3.11%). To achieve these results, a comprehensive sequential-iterative design procedure is introduced to integrate the controllable Gurney flap into the turbine design and to drive the design solution toward the best LCOE reduction solution. Results are presented for mapping fatigue load reductions into cost reductions. In addition, an evaluation of active load control extended from Region-III to also include Region-II showed a further 34% reduction in DEL.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Idealized Offshore Low‐Level Jets for Turbine Structural Impact Considerations

Low-level jets (LLJs) describe conditions in which the wind speed reaches a local maximum with respect to altitude near the surface; they have been observed intermittently in the US mid-Atlantic offshore environment. LLJs pose unique operating conditions for future wind turbines operating in the region, such as negative shear and locally strong veer, but they are not typically considered in existing turbine standards. This work builds upon recent research that explains the formation and evolution of the US mid-Atlantic LLJs through a simple analytical governing equation. We generate several LLJ inflow conditions with varying jet characteristics based on this analytical model and create monotonically sheared (MS) analogues with matched veer to assess the impacts of the LLJ on turbine performance and loading. Using aeroelastic simulations with these inflow conditions on the International Energy Agency 15-MW reference turbine, we find that the LLJ leads to a greater range of tower-top pitching and yawing moments, which could contribute to larger accumulated structural fatigue in components compared to MS inflow. These preliminary results demonstrate a path toward a unified set of test cases for low-level wind maxima that can inform the International Electrotechnical Commission standards related to offshore wind turbine design.

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