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DOE OSTI2020

Sensitivity of Wind Turbine Array Downstream Effects to the Parameterization Used in WRF

The Weather Research and Forecasting (WRF) Model has been extensively used for wind energy applications, and current releases include a scheme that can be applied to examine the effects of wind turbine arrays on the atmospheric flow and electricity generation from wind turbines. Herein we present a high-resolution simulation using two different wind farm parameterizations: 1) the “Fitch” parameterization that is included in WRF releases and 2) the recently developed Explicit Wake Parameterization (EWP) scheme. We compare the schemes using a single yearlong simulation for a domain centered on the highest density of current turbine deployments in the contiguous United States (Iowa). Pairwise analyses are applied to diagnose the downstream wake effects and impact of wind turbine arrays on near-surface climate conditions. On average, use of the EWP scheme results in small-magnitude wake effects within wind farm arrays and faster recovery of full WT array wakes. This in turn leads to smaller impacts on near-surface climate variables and reduced array–array interactions, which at a systemwide scale lead to summertime capacity factors (i.e., the electrical power produced relative to nameplate installed capacity) that are 2%–3% higher than those from the more commonly applied Fitch parameterization. It is currently not possible to make recommendations with regard to which wind farm parameterization exhibits higher fidelity or to draw inferences with regard to whether the relative performance may vary with prevailing climate conditions and/or wind turbine deployment configuration. However, the sensitivities documented herein to the wind farm parameterization are of sufficient magnitude to potentially influence wind turbine array siting decisions. Thus, our research findings imply high value in undertaking combined long-term high-fidelity observational studies in support of model validation and verification.

17 WIND ENERGY↗

DOE OSTI2026

Wake-Resolving Acoustic Tomography: Advances through Numerical Covariance Methods

Acoustic tomography offers path-integrated measurements of atmospheric velocity and temperature fluctuations with high spatial resolution. Classical implementations of time-dependent stochastic inversion rely on homogeneous, isotropic covariance models that are poorly suited to the anisotropic structure of wind turbine wakes. By directly estimating heterogeneous covariances from large-eddy simulations (LESs) into the time-dependent stochastic inversion operator, we relax implicit assumptions in the analytical models used historically. Retrievals using these LES-informed models improve agreement with true fields in variance, turbulent kinetic energy, and spectral content compared to analytical and precursor-based covariance models. The results indicate that LES-informed covariance models can enhance the accuracy of acoustic tomography retrievals in complex, anisotropic flows such as wind turbine wakes in some cases and highlight instances where analytical models still offer competitive performance, despite their simplifying assumptions.

17 WIND ENERGY↗

DOE OSTI2022

Parked aeroelastic field rotor response for a 20% scaled demonstrator of a 13‐MW downwind turbine

Abstract Aeroelastic parked testing of a unique downwind two‐bladed subscale rotor was completed to characterize the response of an extreme‐scale 13‐MW turbine in high‐wind parked conditions. A 20% geometric scaling was used resulting in scaled 20‐m‐long blades, whose structural and stiffness properties were designed using aeroelastic scaling to replicate the nondimensional structural aeroelastic deflections and dynamics that would occur for a lightweight, downwind 13‐MW rotor. The subscale rotor was mounted and field tested on the two‐bladed Controls Advanced Research Turbine (CART2) at the National Renewable Energy Laboratory's Flatiron Campus (NREL FC). The parked testing of these highly flexible blades included both pitch‐to‐run and pitch‐to‐feather configurations with the blades in the horizontal braked orientation. The collected experimental data includes the unsteady flapwise root bending moments and tip deflections as a function of inflow wind conditions. The bending moments are based on strain gauges located in the root section, whereas the tip deflections are captured by a video camera on the hub of the turbine pointed toward the tip of the blade. The experimental results are compared against computational predictions generated by FAST, a wind turbine simulation software, for the subscale and full‐scale models with consistent unsteady wind fields. FAST reasonably predicted the bending moments and deflections of the experimental data in terms of both the mean and standard deviations. These results demonstrate the efficacy of the first such aeroelastically scaled turbine test and demonstrate that a highly flexible lightweight downwind coned rotor can be designed to withstand extreme loads in parked conditions.

17 WIND ENERGY↗

DOE OSTI2021

DOE WPTO FY2021 Seedling End Report: Coupling Soil-Foundation Models to MHK Device Dynamic Models to Tighten the Design Envelope

The purpose of this Seedling project is to couple a marine renewable energy (MRE) dynamics simulation software with the soil-foundation models in the OC6 Phase II project [Bergua et al., 2021] and evaluate the software’s performance. This is a first step to accurately evaluating soil-foundation impacts on other types of MRE, like wave or current energy converters (WECs, CECs). OC6 Phase II compares offshore wind turbine (OWT) simulations using several different soil-foundation models to identify and fill key gaps in soil-foundation analyses. WEC-Sim was chosen to model the OC6 Phase II offshore wind turbine and various load cases because of its adaptability, accuracy of hydrodynamic loads, and ability to apply an arbitrary wind loading. Of the four methods used in OC6, the apparent fixity soil-foundation method was coupled with WEC-Sim. Technical challenges with flexible hydrodynamic bodies, added mass and external function libraries inhibited the ability to compare the WEC-Sim results to other OC6 participants. These challenges required that the WEC-Sim model of the OC6 OWT use a combination of rigid and flexible bodies to ensure a numerically stable solution. The rigid monopile creates a more stiff system and causes smaller amplitude motion under hydrodynamic loading and higher dominant frequency of motion under wind loading. These discrepancies are expected based on the increased stiffness of the WEC-Sim case.

16 TIDAL AND WAVE POWER↗

NASA NTRS1980

Stability of large horizontal-axis axisymmetric wind turbines

The stability of large horizontal axis, axi-symmetric, power producing wind turbines was examined. The analytical model used included the dynamic coupling of the rotor, tower and power generating system. The aerodynamic loading was derived from blade element theory. Each rotor blade was permitted tow principal elastic bending degrees of freedom, one degree of freedom in torsion and controlled pitch as a rigid body. The rotor hub was mounted in a rigid nacelle which may yaw freely or in a controlled manner. The tower can bend in two principal directions and may twist. Also, the rotor speed can vary and may induce perturbation reactions within the power generating equipment. Stability was determined by the eigenvalues of a set of linearized constant coefficient differential equations. All results presented are based on a 3 bladed, 300 ft. diameter, 2.5 megawatt wind turbine. Some of the parameters varied were; wind speed, rotor speed structural stiffness and damping, the effective stiffness and damping of the power generating system and the principal bending directions of the rotor blades. Unstable or weakly stable behavior can be caused by aerodynamic forces due to motion of the rotor blades and tower in the plane of rotation or by mechanical coupling between the rotor system and the tower.

Hirschbein, M. S.↗

DOE OSTI2020

Computational analysis of deployable wind turbine systems in defense operational energy applications.

The U.S. military has been exploring pathways to reduce the logistical burden of fuel on virtually all their missions globally. Energy harvesting of local resources such as wind and solar can help increase the resilience and operational effectiveness of military units, especially at the most forward operating bases where the fuel logistics are most challenging. This report considers the potential benefits of wind energy provided by deployable wind turbines as measured by a reduction in fuel consumption and supply convoys to a hypothetical network of Army Infantry Brigade Combat Team bases. Two modeling and simulation tools are used to represent the bases and their operations and quantify the impacts of system design variables that include wind turbine technologies, battery storage, number of turbines, and wind resource quality. The System of Systems Analysis Toolkit Joint Operational Energy Model serves as a baseline scenario for comparison. The Hybrid Optimization of Multiple Energy Resources simulation tool is used to optimize a single base within the larger Joint Operational Energy Model. The results of both tools show that wind turbines can provide significant benefits to contingency bases in terms of reduced fuel use and number of convoy trips to resupply the base. The match between the turbine design and wind resource, which is statistically low across most of the global land area, is a critical design consideration. The addition of battery storage can enhance the benefits of wind turbines, especially in systems with more wind turbines and higher wind resources. Wind turbines may also provide additional benefits to other metrics such as resilience that may be important but not fully considered in the current analysis. ACKNOWLEDGEMENTS The authors would like to thank the following individuals for their helpful support, feedback and review to improve this report: U.S. Department of Energy Wind Energy Technologies Office, Patrick Gilman and Bret Barker; Idaho National Laboratory, Jake Gentle and Bradley Whipple; The National Renewable Energy Laboratory, Robert Preus and Tony Jimenez; Sandia National Laboratories, Alan Nanco, Dennis Anderson, and Hai Le. In addition, numerous discussions with military and industry stakeholders over the year were invaluable in focusing the efforts represented in this report.

17 WIND ENERGY↗

DOE OSTI2025

Graph Neural Networks for Surrogate Modeling of Offshore Floating Platforms

Floating offshore wind turbines (FOWTs) present an significant opportunity to increase renewable energy generation. However, significant challenges remain before FOWTs can be widely commercialized and deployed. In particular, hydrodynamic loading on the platforms can stress the overall structure, damage the mooring systems, and impact power generation. Studying these loads is difficult and often relies on computationally expensive models or experiments. In this work, we explore the use of graph neural networks (GNNs) to construct flexible, data-driven surrogates for hydrodynamic loads on platforms. We leverage the natural graph-like structure of offshore wind platform designs to enable the GNN model to learn to approximate the loads for different wave conditions and structural designs. We demonstrate potential uses for the surrogate by performing parameter sweeps and ridge analysis on the trained model to identify the impacts of different wave and structural features on the loads.

floating offshore wind turbines↗

DOE OSTI2020

New vortex‐lift and tangential‐force models for HAWT aerodynamic load prediction

Abstract Horizontal axis wind turbines (HAWTs) experience three‐dimensional rotational and unsteady aerodynamic phenomena at the rotor blades sections. These highly unsteady three‐dimensional effects have a dramatic impact on the aerodynamic load distributions on the blades, in particular, when they occur at high angles of attack due to stall delay and dynamic stall. Unfortunately, there is no complete understanding of the flow physics yet at these unsteady 3D flow conditions, and hence, the existing published theoretical models are often incapable of modelling the impact on the turbine response realistically. The purpose of this paper is to provide an insight on the combined influence of the stall delay and dynamic stall on the blade load history of wind turbines in controlled and uncontrolled conditions. New dynamic stall vortex and nonlinear tangential force coefficient modules, which integrally take into account the three dimensional rotational effect, are also proposed in this paper. This module along with the unsteady influence of turbulent wind speed and tower shadow is implemented in a blade element momentum (BEM) model to estimate the aerodynamic loads on a rotating blade more accurately. This work presents an important step to help modelling the combined influence of the stall delay and dynamic stall on the load history of the rotating wind turbine blades which is vital to have lighter turbine blades and improved wind turbine design systems.

Elgammi, Moutaz↗

DOE OSTI2024

Analyzing the Effects of Atmospheric Turbulent Fluctuations on the Wake Structure of Wind Turbines and Their Blade Vibrational Dynamics

In recent trends, a rising demand for renewable energy has driven wind turbines to larger proportions, where lighter blade designs are often adopted to reduce the costs associated with logistics and production. This causes modern utility-scale wind turbine blades to be inherently more flexible, and their amplified aeroelastic sensitivity results in complex multi-physics reactions to variant atmospheric conditions, including dynamic patterns of aerodynamic loading at the rotor and vortex structure evolutions within the wake. In this paper, we analyze the influence of inflow variance for wind turbines with large, flexible rotors through simulations of the National Rotor Testbed (NRT) turbine, located at Sandia National Labs’ Scaled Wind Farm Technology (SWiFT) facility in Lubbock, Texas. The Common Ordinary Differential Equation Framework (CODEF) modeling suite is used to simulate wind turbine aeroelastic oscillatory behavior and wind farm vortex wake interactions for a range of flexible NRT blade variations, operating in differing conditions of variant atmospheric flow. CODEF solutions of turbine operation in Steady-In-The-Average (SITA) wind conditions are compared to SITA wind conditions featuring a controlled gust-like pulse overimposed, to isolate the effects of typical wind fluctuations. Finally, simulations of realistic time-varying wind conditions from SWiFT meteorological tower measurements are compared to the solutions of SITA wind conditions. These increasingly complex atmospheric inflow variations are tested to show the differing effects evoked by various patterns of spatiotemporal atmospheric flow fluctuations. An analysis is presented for solutions of wind turbine aeroelastic response and vortex wake evolution, to elucidate the consequences of variant inflow, which pertain to wind turbine dynamics at an individual and farm-collective scale. The comparisons of simulated farm flow for SITA and measured fluctuating wind conditions show that certain regions of the wake contain up to a 12% difference in normalized axial velocity, due to the introduction of wind fluctuations. The findings of this study prove valuable for practical applications in wind farm control and optimization strategies, with particular significance for modern utility-scale wind power plants operating in variant atmospheric conditions.

Farrell, Alayna (ORCID:000000023555720X)↗

DOE OSTI2020

Mobile Sensing for Wind Field Estimation in Wind Farms: Preprint

This paper introduces a novel approach for estimating the wind field over an entire wind farm using a mobile sensor to collect limited amounts of data. The proposed method estimates the boundary conditions of a simplified turbine wake model by computing the model sensitivity matrix and using a recursive least-squares algorithm to recover the model parameters from the wind field measurements. To address the fact that it is not practical to take measurements across the entire wind farm, the proposed method classifies each area on the map based on its sensitivity to parameter variations. This classification is then used to generate a suitable path for a mobile sensor, which is charged with collecting data for the recursive least-squares algorithm. The proposed framework can successfully estimate the model boundary conditions using just the measurements collected along the path of the mobile sensor. This preliminary result paves the way for using real-time wind field estimates for the coordinated control of all the turbines within a wind farm.

estimation↗

DOE OSTI2020

Uncertainty Assessment of CFD Investigation of the Nonlinear Difference-Frequency Wave Loads on a Semisubmersible FOWT Platform

Current mid-fidelity modeling approaches for floating offshore wind turbines (FOWTs) have been found to underpredict the nonlinear, low-frequency wave excitation and the response of semisubmersible FOWTs. To examine the cause of this underprediction, the OC6 project is using computational fluid dynamics (CFD) tools to investigate the wave loads on the OC5-DeepCwind semisubmersible, with a focus on the nonlinear difference-frequency excitation. This paper focuses on assessing the uncertainty of the CFD predictions from simulations of the semisubmersible in a fixed condition under bichromatic wave loading and on establishing confidence in the results for use in improving mid-fidelity models. The uncertainty for the nonlinear wave excitation is found to be acceptable but larger than that for the wave-frequency excitation, with the spatial discretization error being the dominant contributor. Further, unwanted free waves at the difference frequency have been identified in the CFD solution. A wave-splitting and wave load-correction procedure are presented to remove the contamination from the free waves in the results. A preliminary comparison to second-order potential-flow theory shows that the CFD model predicted significantly higher difference-frequency wave excitations, especially in surge, suggesting that the CFD results can be used to better calibrate the mid-fidelity tools.

17 WIND ENERGY↗

DOE OSTI2020

Validation of a Generalized Formulation for Load Sharing Behavior in Epicyclic Gears for Wind Turbines

In an ideal epicyclic gear set every parallel gear path transmits the same amount of torque. However, it is well known that certain manufacturing variations result in unequal load sharing between the parallel gear paths. Previous works have developed and validated a general closed-form analytical model of this phenomenon that describes the load sharing characteristics of epicyclic gear sets from three to six planets at any torque level. More recently, this analytical model has been reformulated to include the effects of gravity, carrier bearing clearance, and external applied moments, all of which are relevant to most gearboxes and their mounting configuration in horizontal-axis wind turbines. In this paper, the reformulated model is compared to load measurements collected from two similar wind turbine gearboxes with three-planet epicyclic gear sets. The resulting load sharing values are also compared to the mesh load factor requirements in the AGMA 6006 and IEC 61400-4 wind turbine gearbox design standards. Load sharing factors as high as 1.16 at extreme rotor moments and 1.08 with no moment were measured for the gearbox with cylindrical roller bearings, but the load sharing factor remained below 1.10 for the gearbox with tapered roller bearings The results show that in the wind turbine application, load sharing is not equal - even for three-planet systems with a floating central member because of the effects of gravity, rotor moments, and the resulting relative motions among the epicyclic gear components within the carrier bearing clearance.

closed-form analytical model↗

DOE OSTI2020

Validation of a Generalized Formulation for Load-Sharing Behavior in Epicyclic Gears for Wind Turbines: Preprint

closed-form analytical model↗

DOE OSTI2022

Challenges and Possible Solutions in Aeroelastic Modeling for the Distributed Wind Industry

Aeroelastic modeling (AM) is the primary methodology for structural and performance assessment of any wind turbine; it provides an understanding of the impact of design parameters on turbine loading and power response before witnessing it in the field. Despite these advantages, the use of AM in the distributed wind technology (DWT) sector is limited. This article represents a short summary of an in-depth assessment by the authors of the status of AM and its role within the distributed wind technology design standards. The research gathered input and feedback from a large number of U.S. and international stakeholders, reviewed technical strengths and weaknesses of the current edition of the design standards, analyzed the minutes from recent industry workshops and meetings, collected publicly available AM templates, and provided an evaluation of the existing AM codes. Several goals were achieved including providing strategies for the load assessment categorization of turbines based on rotor swept area and archetype, and guidance for AM verification and validation. Recommendations within this study will advance the value and the ease-of-use of AM, thereby allowing the industry to better capitalize this underutilized tool, resulting in a more efficient design process, an easier path to certification, and overall better and more reliable distributed wind technology products.

17 WIND ENERGY↗

DOE OSTI2021

Network Based Estimation of Wind Farm Power and Velocity Data Under Changing Wind Direction

This paper describes an estimation algorithm for velocity and power output signals in a wind farm under changing wind direction. A graph-theoretic definition describes the wind farm as a collection of nodes (turbines) and time-varying weighted edges (inter-turbine wake propagation) that change as a function of incoming wind direction. The velocity at each turbine is determined through a discrete input-output model. Changes in wind direction serve as the input and the output is defined in terms of a time-varying weighted adjacency matrix that depends on the time-delay of information propagation between turbines. These delays, which are defined in terms of the advection speed of the wind and the distance between the turbines, capture the delayed effect of wind direction changes on the inter-connectivity of the graph as the wind conditions at the farm inlet propagate through the turbine array. An event-based update framework is employed to capture time-dependent topology changes due to shifts in wind direction. Simulation results for dynamically changing wind inlet directions to a circular wind farm are compared to predictions from both the static and dynamic versions of the FLOw Redirection and Induction in Steady State (FLORIS) model. The approach is shown to enable real-time tracking of dynamic changes to wind farm power output within a framework that can be easily integrated into real-time, horizon-based, control strategies that typically do not account for wind direction changes.

distributed↗

DOE OSTI2022

Region-based convolutional neural network for wind turbine wake characterization from scanning lidars

A convolutional neural network is applied to lidar scan images from three experimental campaigns to identify and characterize wind turbine wakes. Initially developed as a proof-of-concept model and applied to a single data set in complex terrain, the model is now improved and generalized and applied to two other unique lidar data sets, one located near an escarpment and one located offshore. The model, initially developed using lidar scans collected in predominantly westerly flow, exhibits sensitivity to wind flow direction. The model is thus successfully generalized through implementing a standard rotation process to scan images before input into the convolutional neural network to ensure the flow is westerly. The sample size of lidar scans used to train the model is increased, and along with the generalization process, these changes to the model are shown to enhance accuracy and robustness when characterizing dissipating and asymmetric wakes. Applied to the offshore data set in which nearly 20 wind turbine wakes are included per scan, the improved model exhibits a 95% success rate in characterizing wakes and a 74% success rate in characterizing dissipating wake fragments. The improved model is shown to generalize well to the two new data sets, although an increase in wake characterization accuracy is offset by an increase in model sensitivity and false positive wake identifications.

17 WIND ENERGY↗

NASA NTRS2008

Models of Lift and Drag Coefficients of Stalled and Unstalled Airfoils in Wind Turbines and Wind Tunnels

Equations are developed with which to calculate lift and drag coefficients along the spans of torsionally-stiff rotating airfoils of the type used in wind turbine rotors and wind tunnel fans, at angles of attack in both the unstalled and stalled aerodynamic regimes. Explicit adjustments are made for the effects of aspect ratio (length to chord width) and airfoil thickness ratio. Calculated lift and drag parameters are compared to measured parameters for 55 airfoil data sets including 585 test points. Mean deviation was found to be -0.4 percent and standard deviation was 4.8 percent. When the proposed equations were applied to the calculation of power from a stall-controlled wind turbine tested in a NASA wind tunnel, mean deviation from 54 data points was -1.3 percent and standard deviation was 4.0 percent. Pressure-rise calculations for a large wind tunnel fan deviated by 2.7 percent (mean) and 4.4 percent (standard). The assumption that a single set of lift and drag coefficient equations can represent the stalled aerodynamic behavior of a wide variety of airfoils was found to be satisfactory.

Spera, David A.↗

NASA NTRS1981

Wind turbulence inputs for horizontal axis wind turbines

Wind turbine response characteristics in the presence of atmospheric turbulence was predicted using two major modeling steps. First, the important atmospheric sources for the force excitations felt by the wind turbine system were identified and characterized. Second, a dynamic model was developed which describes how these excitations are transmitted through the structure and power train. The first modeling step, that of quantifying the important excitations due to the atmospheric turbulence was established. The dynamic modeling of the second step was undertaken separately.

Holley, W. E.↗