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At least 19 records

Ensemble‐Based, Large‐Eddy Reconstruction of Wind Turbine Inflow in a Near‐Stationary Atmospheric Boundary Layer Through Generative Artificial Intelligence

ABSTRACT To validate the second‐by‐second dynamics of turbines in field experiments, it is necessary to accurately reconstruct the winds going into the turbine. Current time‐resolved inflow reconstruction techniques estimate wind behavior in unobserved regions using relatively simple spectral‐based models of the atmosphere. Here, we develop a technique for time‐resolved inflow reconstruction that is rooted in a large‐eddy simulation model of the atmosphere. Our “large‐eddy reconstruction” technique blends observations and atmospheric model information through a diffusion model machine learning algorithm, allowing us to generate probabilistic ensembles of reconstructions for a single 10‐min observational period. Our generated inflows can be used directly by aeroelastic codes or as inflow boundary conditions in a large‐eddy simulation. We verify the second‐by‐second reconstruction capability of our technique in three synthetic field campaigns, finding positive Pearson correlation coefficient values () between ground‐truth and reconstructed streamwise velocity, as well as smaller positive correlation coefficient values for unobserved fields (spanwise velocity, vertical velocity, and temperature). We validate our technique in three real‐world case studies by driving large‐eddy simulations with reconstructed inflows and comparing to independent inflow measurements. The reconstructions are visually similar to measurements, follow desired power spectra properties, and track second‐by‐second behavior ().

17 WIND ENERGY↗

Effect of the integral length scales of turbulent inflows on wind turbine loads

As wind turbines become larger, the fluctuations in the inflow become increasingly influential in the turbine structural loading. These fluctuations are characterized by the integral length scale, which represents the average size of the largest energy-containing turbulent eddies. Current design standards neglect the varying integral length scales that characterize inflows of wind turbines in operation. Using large-eddy simulations, we generate turbulent inflows of varying integral length scales and quantify the loads of the IEA 15-MW reference wind turbine. Results illustrate that the impact of turbulence on rotor and tower loads is up to 10 times greater than the impact of the mean shear profile. Increasing integral length scales from 0.3x to 0.5x the rotor diameter reduces blade root flapwise moments and rotor and tower loads. Increasing integral length scales from 0.5x to 1.7x the rotor diameter increases the rotor aerodynamic thrust force and the blade root flapwise shear loads and decreases the tower base torsional moment and the tilting and yawing rotor aerodynamic moments. Additionally, turbulence intensity has a greater impact on wind turbine loads than integral length scales. In conclusion, findings indicate that design standards should consider varying integral length scales for accurate wind turbine loading characterization in turbulent inflow conditions.

17 WIND ENERGY↗

Comparison of free vortex wake and blade element momentum results against large-eddy simulation results for highly flexible turbines under challenging inflow conditions

Abstract. Throughout wind energy development, there has been a push to increase wind turbine size due to the substantial economic benefits. However, increasing turbine size presents several challenges, both physically and computationally. Modeling large, highly flexible wind turbines requires highly accurate models to capture the complicated aeroelastic response due to large deflections and nonstraight blade geometries. Additionally, the development of floating offshore wind turbines requires modeling techniques that can predict large rotor and tower motion. Free vortex wake methods model such complex physics while remaining computationally tractable to perform key simulations necessary during the turbine design process. Recently, a free vortex wake model – cOnvecting LAgrangian Filaments (OLAF) – was added to the National Renewable Energy Laboratory's engineering tool OpenFAST to allow for the aerodynamic modeling of highly flexible turbines along with the aero-hydro-servo-elastic response capabilities of OpenFAST. In this work, free vortex wake and low-fidelity blade element momentum (BEM) results are compared to high-fidelity actuator-line computational fluid dynamics simulation results via the Simulator fOr Wind Farm Applications (SOWFA) method for a highly flexible downwind turbine for varying yaw misalignment, shear exponent, and turbulence intensity conditions. Through these comparisons, it was found that for all considered quantities of interest, SOWFA, OLAF, and BEM results compare well for steady inflow conditions with no yaw misalignment. For OLAF results, this strong agreement with the SOWFA results was consistent for all yaw misalignment values. The BEM results, however, deviated significantly more from the SOWFA results with increasing absolute yaw misalignment. Differences between OLAF and BEM results were dominated by the yaw misalignment angle, with varying shear exponent and turbulence intensity leading to more subtle differences. Overall, OLAF results were more consistent than BEM results when compared to SOWFA results under challenging inflow conditions.

17 WIND ENERGY↗

Curled-Skewed Wakes behind Yawed Wind Turbines Subject to Veered Inflow

This work presents a new engineering analytical model that predicts the effect of both the turbine yaw misalignment and the inflow wind veer on the wake flow distribution downwind of a wind turbine. To consider the veered inflow, two methods were examined. In the first method, the curled shape of the wake due to the yaw offset is initially modelled. The wake shape is then laterally skewed at each height due to the wind veer based on the assumption that the turbine wake is transported downstream by the incoming flow. The second method is a more realistic approach that accounts for the effect of wind veer on the wind velocity direction and the yaw angle seen by the wind turbine. This models the wake region in a local coordinate system defined based on the wind direction at each height. A coordinate transformation is then performed to represent the wake flow distribution in the global coordinate system attached to the ground. The results show that while the two methods provide similar outputs for small variations in the wind direction across the rotor, the difference becomes more evident with an increase in wind veer. High-fidelity simulations for a turbine subject to a neutral atmospheric boundary layer were employed to validate model predictions for different operating conditions.

17 WIND ENERGY↗

A baseline for ensemble-based, time-resolved inflow reconstruction for a single turbine using large-eddy simulations and latent diffusion models

We are interested in reconstructing winds flowing through a turbine on a second-by-second basis over a 10 min window. Previously, we developed a machine learning algorithm that takes in a snapshot of wind speed measurements and generates ensembles of three-dimensional wind field estimates. Here, we use these estimates as initial conditions in large-eddy simulations and reconstruct atmospheric and turbine response dynamic quantities in a synthetic field campaign. In doing so, we establish a baseline for model validation that future time-aware data assimilation techniques will be compared to. In turbine-free case studies, ground truth wind speeds consistently fall within our estimated wind speed distribution for the first 100 s after the simulation start. In simulations with turbines, the wind estimates show a small bias of 0.10 m s 1 and good correlation of 0.80 during the first 100 s. During this window, our estimates of the Blade 1 bending moment and generator power typically span the ground truth, with the estimate of the former performing better overall. In summary, this approach shows promise as a stand-alone technique for reconstructing real-world inflow and turbine dynamics in 1-2 min windows and as a foundation for future time-aware data assimilation techniques.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Sensitivity analysis of the effect of wind and wake characteristics on wind turbine loads in a small wind farm

Abstract. Wind turbines are designed using a set of simulations to determine the fatigue and ultimate loads, which are typically focused solely on unwaked wind turbine operation. These structural loads can be significantly influenced by the wind inflow conditions. Turbines experience altered inflow conditions when placed in the wake of upstream turbines, which can additionally influence the fatigue and ultimate loads. It is important to understand the impact of uncertainty on the resulting loads of both unwaked and waked turbines. The goal of this work is to assess which wind-inflow-related and wake-related parameters have the greatest influence on fatigue and ultimate loads during normal operation for turbines in a three-turbine wind farm. Twenty-eight wind inflow and wake parameters are screened using an elementary effects sensitivity analysis approach to identify the parameters that lead to the largest variation in the fatigue and ultimate loads of each turbine. This study uses the National Renewable Energy Laboratory (NREL) 5 MW baseline wind turbine, simulated with OpenFAST and synthetically generated inflow based on the International Electrotechnical Commission (IEC) Kaimal turbulence spectrum with the IEC exponential coherence model using the NREL tool TurbSim. The focus is on sensitivity to individual parameters, though interactions between parameters are considered, and how sensitivity differs between waked and unwaked turbines. The results of this work show that for both waked and unwaked turbines, ambient turbulence in the primary wind direction and shear are the most sensitive parameters for turbine fatigue and ultimate loads. Secondary parameters of importance for all turbines are identified as yaw misalignment, streamwise integral length, and the exponent and streamwise components of the IEC coherence model. The tertiary parameters of importance differ between waked and unwaked turbines. Tertiary effects account for up to 9.0 % of the significant events for waked turbine ultimate loads and include veer, non-streamwise components of the IEC coherence model, Reynolds stresses, wind direction, air density, and several wake calibration parameters. For fatigue loads, tertiary effects account for up to 5.4 % of the significant events and include vertical turbulence standard deviation, lateral and vertical wind integral lengths, non-streamwise components of the IEC coherence model, Reynolds stresses, wind direction, and all wake calibration parameters. This information shows the increased importance of non-streamwise wind components and wake parameters in the fatigue and ultimate load sensitivity of downstream turbines.

17 WIND ENERGY↗

Statorless mixed flow turbine for transonic pulsating inflow

Effective harvesting of power from high speed highly transient inflows such as the outflow of rotating detonation combustors (RDCs) is key to achieving their promised cycle efficiency step jump. To increase power density and efficiency simultaneously, a concept that can directly ingest transonic outflow, addressing the choking is needed, i.e. without additional transition elements. A new statorless design was assessed using a comprehensive approach to quantify all contributions to loss generation in transient flows, locally and globally. The turbine rotor was designed under steady flow conditions with a genetic algorithm. The comparison of power and loss generation between steady and unsteady flow results shows that a design methodology under steady-state conditions is suitable to characterize the performance of different designs. Three design families were further assessed under highly transient transonic conditions including traveling shock waves with a relative total pressure amplitude of 149.6% around the mean value and inflow angle variations from -26.5 deg to +51.8 deg. The oblique shock impinging on the pressure side (PS) of the turbine augments the shaft power extraction. When the oblique shock reflects between the pressure side and suction side (SS), its strength diminishes. This paper provides design guidelines on efficient turbine work extraction from the shocks emanating from detonation combustors.

rotating detonation engines↗

Near wake evolution of a tidal stream turbine due to asymmetric sheared turbulent inflow with different integral length scales

Tidal stream turbines deployed at highly energetic open water sites are subjected to sheared inflow in the rotor plane. The inflow shear is expected to cause asymmetric loading on the rotor blades and affect the downstream wake. In the current study, two different turbulent inflow conditions, static-high shear and dynamic shear, were generated via an active-grid turbulence generator. A 1:20 scaled three-bladed horizontal axis tidal turbine model was tested in those conditions. The results were compared to a quasi-laminar case with no imposed turbulence or shear. The results show that the high shear reduces the average performance, with a drop of up to 16% in the optimal power coefficient. Besides, the shear profiles increase torque fluctuations and induce significant differences in wake hydrodynamics between the high-speed (upper) and low-speed (lower) regions. The large integral length scales further enhance the load fluctuations perceived by the rotor but have a negligible effect on the mean wake field quantities and the wake recovery. The lower half region featured a faster breakdown of tip vortex structure and a rapid drop of swirl number, a phenomenon conjectured to be a consequence of the strong turbulence intensities and Reynolds stresses in the lower half region. Furthermore, the sheared turbulent inflow also results in a very intensive energy redistribution process towards large-scale, low-frequency motions, which is important to the downstream turbines.

16 TIDAL AND WAVE POWER↗

Going beyond BEM with BEM: an insight into dynamic inflow effects on floating wind turbines

Blade element momentum (BEM) theory is the backbone of many industry-standard wind turbine aerodynamic models. To be applied to a broader set of engineering problems, BEM models have been extended since their inception and now include several empirical corrections. These models have benefitted from decades of development and refinement and have been extensively used and validated, proving their adequacy in predicting aerodynamic forces of horizontal-axis wind turbine rotors in most scenarios. However, the analysis of floating offshore wind turbines (FOWTs) introduces new sets of challenges, especially if new-generation large and flexible machines are considered. In fact, due to the combined action of wind and waves and their interaction with the turbine structure and control system, these machines are subject to unsteady motion and thus unsteady inflow on the wind turbine's blades, which could put BEM models to the test. Consensus has not been reached on the accuracy limits of BEM in these conditions. This study contributes to the ongoing research on the topic by systematically comparing four different aerodynamic models, ranging from BEM to computational fluid dynamics, in an attempt to shed light on the unsteady aerodynamic phenomena that are at stake in FOWTs and whether BEM is able to model them appropriately. Simulations are performed on the UNAFLOW 1:75 scale rotor during imposed harmonic surge and pitch motion. Experimental results are available for these conditions and are used for baseline validation. The rotor is analyzed in both rated operating conditions and low wind speeds, where unsteady aerodynamic effects are expected to be more pronounced. Results show that BEM, despite its simplicity, can adequately model the aerodynamics of FOWTs in most conditions if augmented with a dynamic inflow model.

17 WIND ENERGY↗

A Green's Function Wind Turbine Induction Model That Incorporates Complex Inflow Conditions

ABSTRACT In this work, we develop a new analytical turbine induction model that can incorporate complex inflow conditions including cases where the wind velocity and temperature profiles can vary as functions of height. This induction model is derived from the linearized Navier–Stokes and leads to a second‐order ODE that can be solved using a Green's function formulation. The corresponding Green's function for several configurations are found including the infinite domain, semi‐infinite domain with ground plane, and a power law velocity inflow profile. The results of this approach are then compared with simulations of the turbine induction field using the AMR‐Wind CFD solver with a uniformly loaded actuator disk model. These comparisons show that the Green's function approach captures the centerline blockage, three‐dimensional blockage flow field, and streamwise velocity slow down, with very good agreement for lower thrust conditions and at larger distances away from rotor disk. The effects of shear on the turbine blockage were also compared using a power law inflow profile, and we show that this approach matches the CFD predictions for the cases considered.

17 WIND ENERGY↗

In-Situ Blade Strain Measurements of a Crossflow Turbine Operating in a Tidal Flow

This data was collected between October 25 and December 12 of 2022 at the University of New Hampshire (UNH) and Atlantic Marine Energy Center (AMEC) turbine deployment platform (TDP). The goal was to collect blade strain data from a crossflow turbine operating in a tidal flow. A table in ('Deployment Schedule.PNG') outlines the various dates when each instrument was operational, and more details can be found via literature listed in 'Related Publications'.txt. This dataset includes zipped folders for each instrument containing data in .csv files for the relevant duration specific to each instrument, along with separate README file for each measurement. Some instrument files are quite large and can pose a challenge for a visual spreadsheet editor to open. A processing software like MATLAB or Python is recommended. All data contained in this submission is unfiltered/unprocessed data unless otherwise noted in the README file. Blade strain was measured using 8 foil-based strain gauges along the span of a single turbine blade. Water currents were measured using Acoustic Doppler Current Profilers (ADCP's) and Acoustic Doppler Velocimeters (ADV's) both upstream and downstream of the turbine for inflow, wake and turbulence measurements. Electrical power output was measured using the Voltsys rectifier. Shaft speed was calculated based on the Voltsys measurements of the permanent magnet three phase generator AC generation frequency, coupled directly to the cross flow turbine under test (i.e., no gear box). Platform motions were captured using a Yost IMU (inertial measurement unit). Turbine thrust loading was measured using a reaction arm about the turbine deployment platform spanning beam, where two bi-directional load cells were connected to the system via a pinned connection. The TDP is a floating structure moored on the Portsmouth facing side of Memorial Bridge pier #2, which spans the Piscataqua River between Portsmouth, NH and Kittery, ME. The Piscataqua River connects the Great Bay Estuary to the Gulf of Maine and the river currents are dominated by tidal flow with water velocities exceeding 2.5 m/s during spring ebb tides at this site which were previously characterized by Chancey 2019. The turbine under test was a modified New Energy Corporation (Calgary, CA) model EVG-025 4-blade H-Darrius type vertical axis cross flow turbine that rotates in the clockwise direction with a rotor diameter of 3.2m and blade length of 1.7m. The hydro-foil profile was a NACA 0021 with a 10 inch chord length and a blade preset pitch angle of +4deg with a positive angle corresponding with the toe in direction. The standard EVG-025 has a rotor diameter of 3.4m and its rated power output is 25kW at 3 m/s. The rotor diameter was reduced to accommodate the size of the existing TDP moon-pool. A single blade of this turbine was further modified to accommodate 8 full-bridge strain gauges (Bharath et al 2023, Bichanich et al 2024). For power performance and other relevant details on the turbine and its characteristics, see O'Byrne 2022.

16 TIDAL AND WAVE POWER↗

RAAW

High-fidelity wind turbine modeling advances necessitate model validation datasets of equally high fidelity. The Rotor Aerodynamics, Aeroelastics & Wake (RAAW) project was designed to address this need. This three-year project runs from October 2021 through October 2024 starting with a field data collection period followed by model validation activities. RAAW is a partnership between GE Renewable Energy and the United States Department of Energy (DOE) through the National Renewable Energy Laboratory (NREL) and Sandia National Laboratories. The field experiment is designed to make detailed measurements of the inflow, wind turbine response, and the resulting wake. The experimental dataset will be suitable for validating wind turbine models across the fidelity spectrum from actuator disk methods to blade-resolved codes.

17 WIND ENERGY↗

Challenges in Rotor Aerodynamic Modeling for Non-Uniform Inflow Conditions

Within an international collaboration framework, the accuracy of rotor aerodynamic models used for design load calculations of wind turbines is being assessed. Where the use of high-fidelity computation fluid dynamics (CFD) and mid-fidelity free-vortex wake (FVW) models has become commonplace within the wind energy community, these still fail to meet the requirements in terms of execution time and computational cost needed for design load calculations. The fast but engineering fidelity blade-element/momentum (BEM) method can therefore still be considered the industry workhorse for design load simulations. At the same time, upscaling of wind turbine rotors makes inflow non-uniformities (e.g. shear, veer, turbulence) more important. The objective of this work is to assess model accuracy in non-uniform inflow conditions, which violate several BEM assumptions. Thereto a comparison in turbulent inflow has been executed including a wide variety of codes, focusing on the DanAero field measurements, where a 2.3-MW turbine was equipped with, among other sensors, a pressure measurement apparatus. The results indicate that, although average load patterns are in good agreement, this does not hold for the unsteady loads that drive fatigue damage and aero-elastic stability. A simplified comparison round in vertical shear was initiated to investigate the observed differences in a more controlled manner. A consistent offset in load amplitude was observed between CFD and free-vortex codes on the one hand and BEM-type codes on the other hand. To shed more light on the observations, dedicated efforts are ongoing to pinpoint the cause for these differences, in the end leading to guidelines for an improved BEM implementation.

17 WIND ENERGY↗

A Three-Dimensional, Analytical Wind Turbine Wake Model: Flow Acceleration, Empirical Correlations, and Continuity

A new, three-dimensional, analytical, steady-state wake model is presented that includes local flow acceleration near the rotor, improving the wake description compared to existing models. Wake structures such as the momentum deficit and regions of accelerated flow are concisely described with compound and normal Gaussian functions. Large-eddy simulations (LES) are used as training data to develop the model using two in-line turbines under various inflow conditions parameterized by hub-height wind speed and turbulence intensity. Mass conservation is considered by fixing two components of the wake velocity model and optimizing the third to best satisfy continuity; after which, the model performs comparably if not better than existing work with regards to both relative error and mass consistency. The final model demonstrates a high degree of flexibility, making use of empirical correlations to scale across different inflow conditions. The inclusion of these effects is capable of revealing unused opportunities for enhanced power generation by aligning wake trajectories with these regions of accelerated flow.

modeling↗

A time‐varying formulation of the curled wake model within the FAST.Farm framework

Abstract In this article, we present a time‐varying formulation of the curled wake model that we implemented in FAST.Farm. The curled wake model, originally developed for steady‐state conditions, is used to produce realistic wake profiles behind a wind turbine in yawed (or skewed) conditions. We begin by introducing the key elements of the FAST.Farm framework. Then, after briefly summarizing the original wake dynamics formulation of FAST.Farm based on a polar wake profile, we present the new time‐varying formulation of the curled wake model, compare the two, and highlight the differences with the original curled wake model. After discussing some implementation details, we present different applications with increasing levels of complexity: single turbine with uniform and turbulent inflow, fixed and transient yaw, and multiple turbines. We verify our results using the original FAST.Farm implementation and large‐eddy simulations. The results with the new curled wake model are improved compared to the original implementation, as they include cross‐flow velocities and wake asymmetry. Yet, large‐eddy simulation results show a more pronounced lateral convection of the wake and a stronger concentration of vorticity at the top vortex. The new curled wake implementation in FAST.Farm should enable the calculation of not only generator power but also wind turbine structural loads for applications involving intentional or unintentional skewed flow and wind‐farm control involving wake steering.

17 WIND ENERGY↗

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)↗

A simple vortex model applied to an idealized rotor in sheared inflow

A simple analytical vortex model is presented and used to study an idealized wind turbine rotor in uniform and sheared inflow, respectively. Our model predicts that 1D momentum theory should be applied locally when modelling a non-uniformly loaded rotor in a sheared inflow. Hence the maximum local power coefficient (expressed with respect to the local, upstream velocity) of an ideal rotor is not affected by the presence of shear. We study the interaction between the wake vorticity generated by the rotor and the wind shear vorticity and find that their mutual interaction results in no net generation of axial vorticity: the wake effects and the shear effects exactly cancel each other out. This means that there are no resulting cross-shear-induced velocities and therefore also no cross-shear deflection of the wake in this model.

17 WIND ENERGY↗

A Study of Wake Characteristics of Marine Turbine Arrays: Preprint

As the marine energy industry continues to develop and installations grow from single turbines to small arrays and larger farms, understanding and predicting wake behavior using modeling tools is necessary for array design and optimization. The wake characteristics of upstream turbines, including velocity deficit, wake swirling, tip vortices, wake shape and direction, and flow recovery, influence the inflow conditions experienced by downstream turbines in an array and, subsequently, affect the individual turbine loading and power generated by the array. These wake characteristics are influenced by many factors, including site geography, inflow shear profile, turbulence, waves, the strength of the current resource, gravitational forces, storm surges, and seasonal effects like temperature and wind conditions. Efficient array modeling tools that capture these wake effects and resulting turbine-to-turbine interactions need to be developed to optimize farm layouts and design individual turbines for operation within arrays. Unlike the wind industry, the marine energy research community is largely limited to the use of either numerical tools or tank/flume testing to understand marine turbine wake interactions. This paper will investigate recent advances in numerical and experimental marine turbine wake modeling, with a focus on recent publications and on both axial-flow and cross-flow marine turbines. A summary of recent research on these topics is provided. Additionally, a demonstration of turbine wake interactions using computational fluid dynamics is presented.

marine hydrokinetic turbine↗