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1
Neunaber, Ingrid, Michael Hölling, Richard J. A. M. Stevens, Gerard Schepers, and Joachim Peinke. "Distinct Turbulent Regions in the Wake of a Wind Turbine and Their Inflow-Dependent Locations: The Creation of a Wake Map." Energies 13, no. 20 (2020): 5392. http://dx.doi.org/10.3390/en13205392.
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Wind turbines are usually clustered in wind farms which causes the downstream turbines to operate in the turbulent wakes of upstream turbines. As turbulence is directly related to increased fatigue loads, knowledge of the turbulence in the wake and its evolution are important. Therefore, the main objective of this study is a comprehensive exploration of the turbulence evolution in the wind turbine’s wake to identify characteristic turbulence regions. For this, we present an experimental study of three model wind turbine wake scenarios that were scanned with hot-wire anemometry with a very high downstream resolution. The model wind turbine was exposed to three inflows: laminar inflow as a reference case, a central wind turbine wake, and half of the wake of an upstream turbine. A detailed turbulence analysis reveals four downstream turbulence regions by means of the mean velocity, variance, turbulence intensity, energy spectra, integral and Taylor length scales, and the Castaing parameter that indicates the intermittency, or gustiness, of turbulence. In addition, a wake core with features of homogeneous isotropic turbulence and a ring of high intermittency surrounding the wake can be identified. The results are important for turbulence modeling in wakes and optimization of wind farm wake control.
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Foti, Daniel, Xiaolei Yang, Lian Shen, and Fotis Sotiropoulos. "Effect of wind turbine nacelle on turbine wake dynamics in large wind farms." Journal of Fluid Mechanics 869 (April 18, 2019): 1–26. http://dx.doi.org/10.1017/jfm.2019.206.
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Wake meandering, a phenomenon of large-scale lateral oscillation of the wake, has significant effects on the velocity deficit and turbulence intensities in wind turbine wakes. Previous studies of a single turbine (Kang et al., J. Fluid. Mech., vol. 774, 2014, pp. 374–403; Foti et al., Phys. Rev. Fluids, vol. 1 (4), 2016, 044407) have shown that the turbine nacelle induces large-scale coherent structures in the near field that can have a significant effect on wake meandering. However, whether nacelle-induced coherent structures at the turbine scale impact the emergent turbine wake dynamics at the wind farm scale is still an open question of both fundamental and practical significance. We take on this question by carrying out large-eddy simulation of atmospheric turbulent flow over the Horns Rev wind farm using actuator surface parameterisations of the turbines without and with the turbine nacelle taken into account. While the computed mean turbine power output and the mean velocity field away from the nacelle wake are similar for both cases, considerable differences are found in the turbine power fluctuations and turbulence intensities. Furthermore, wake meandering amplitude and area defined by wake meanders, which indicates the turbine wake unsteadiness, are larger for the simulations with the turbine nacelle. The wake influenced area computed from the velocity deficit profiles, which describes the spanwise extent of the turbine wakes, and the spanwise growth rate, on the other hand, are smaller for some rows in the simulation with the nacelle model. Our work shows that incorporating the nacelle model in wind farm scale simulations is critical for accurate predictions of quantities that affect the wind farm levelised cost of energy, such as the dynamics of wake meandering and the dynamic loads on downwind turbines.
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Ahmed, W. U., C. Moss, S. Roy, et al. "Wind Farm Wakes and Farm-to-Farm Interactions: Lidar and Wind Tunnel Tests." Journal of Physics: Conference Series 2767, no. 9 (2024): 092105. http://dx.doi.org/10.1088/1742-6596/2767/9/092105.
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Abstract Recent experimental and numerical evidence has shown that the cumulative wake generated from the overlapping of multiple wakes within a wind farm could reduce power performance and enhance fatigue loads of wind turbines installed in neighboring downstream wind farms and may also extend up to distances one order of magnitude larger than those typically considered for intra-farm wake interactions. Similar to individual wind turbine wakes, wind farm wakes have a velocity deficit and added turbulence intensity, both affected by the turbine rotor thrust forces and the incoming turbulence intensity. Therefore, the evolution of wind farm wakes will vary for different operational and atmospheric conditions. In this paper, lidar measurements collected during the American WAKE experimeNt (AWAKEN) and wind tunnel tests of wind farms reproduced by porous disks are leveraged to investigate wind farm wakes.
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Ghaisas, Niranjan S., Aditya S. Ghate, and Sanjiva K. Lele. "Effect of tip spacing, thrust coefficient and turbine spacing in multi-rotor wind turbines and farms." Wind Energy Science 5, no. 1 (2020): 51–72. http://dx.doi.org/10.5194/wes-5-51-2020.
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Abstract. Large eddy simulations (LESs) are performed to study the wakes of a multi-rotor wind turbine configuration comprising four identical rotors mounted on a single tower. The multi-rotor turbine wakes are compared to the wake of a conventional turbine comprising a single rotor per tower with the same frontal area, hub height and thrust coefficient. The multi-rotor turbine wakes are found to recover faster, while the turbulence intensity in the wake is smaller, compared to the wake of the conventional turbine. The differences with the wake of a conventional turbine increase as the spacing between the tips of the rotors in the multi-rotor configuration increases. The differences are also sensitive to the thrust coefficients used for all rotors, with more pronounced differences for larger thrust coefficients. The interaction between multiple multi-rotor turbines is contrasted with that between multiple single-rotor turbines by considering wind farms with five turbine units aligned perfectly with each other and with the wind direction. Similar to the isolated turbine results, multi-rotor wind farms show smaller wake losses and smaller turbulence intensity compared to wind farms comprised of conventional single-rotor turbines. The benefits of multi-rotor wind farms over single-rotor wind farms increase with increasing tip spacing, irrespective of the axial spacing and thrust coefficient. The mean velocity profiles and relative powers of turbines obtained from the LES results are predicted reasonably accurately by an analytical model assuming Gaussian radial profiles of the velocity deficits and a hybrid linear-quadratic model for the merging of wakes. These results show that a larger power density can be achieved without significantly increased fatigue loads by using multi-rotor turbines instead of conventional, single-rotor turbines.
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Shaler, Kelsey, Amy N. Robertson, and Jason Jonkman. "Sensitivity analysis of the effect of wind and wake characteristics on wind turbine loads in a small wind farm." Wind Energy Science 8, no. 1 (2023): 25–40. http://dx.doi.org/10.5194/wes-8-25-2023.
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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.
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Tian, Wenxin, Qiang Shi, Lidong Zhang, et al. "Effect of Turbulence Intensity on Aerodynamic Loads of Floating Wind Turbine under Wind–Wave Coupling Effect." Sustainability 16, no. 7 (2024): 2967. http://dx.doi.org/10.3390/su16072967.
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This study first employs TurbSim and OpenFAST (Fatigue, Aerodynamics, Structures, Turbulence) programs for secondary development to comprehensively model the NREL-5MW semi-submersible wind turbine and OC4-DeepC wind floating platform with wind–wave interaction. Next, we investigate the dynamic response of floating wind turbines under the complex coupling of turbulent winds and irregular waves. Turbulent wind fields were simulated using the IEC Kaimal model with turbulence intensities of 5% and 20%. Additionally, two irregular waves were simulated with the Pierson–Moskowitz (P–M) spectrum. The results indicate that in turbulent wind conditions, the aerodynamic power of the wind turbine and the root bending moments of the blades are significantly influenced by turbulence, while the impact of waves is minimal. The coupled motion response of the floating platform demonstrates that turbulence intensity has the greatest impact on the platform’s heave and pitch motions, underscoring the importance of turbulence in platform stability. This study provides essential insights for designing and optimizing floating wind turbines in complex wind–wave coupling offshore environments.
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Parinam, Anand, Pierre Benard, Dominic Von Terzi, and Axelle Viré. "Exploring the impact of different inflow conditions on wind turbine wakes using Large-Eddy Simulations." Journal of Physics: Conference Series 2767, no. 9 (2024): 092098. http://dx.doi.org/10.1088/1742-6596/2767/9/092098.
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Abstract The ever-growing demand for renewable energy, driven by cost-effectiveness and minimal ecological impacts, has resulted in the deployment of larger wind turbines with rotor diameters surpassing 200 m. This underscores the importance of a thorough understanding of flow dynamics to optimize operational efficiency in diverse atmospheric inflow scenarios. Understanding the intricate impact of atmospheric conditions, including wind shear and turbulence, on wind turbine wakes is crucial for optimizing wind farm layouts and performance, influencing wake evolution, turbine loads, and power output. This research focuses on bridging the gap between idealized inflow scenarios and real-world atmospheric inflow conditions by systematically integrating linear shear, turbulence and the logarithmic wind shear profile into the uniform inflow conditions and analyzing the wake behind the IEA-15 MW wind turbine. To specifically examine inflow effects, a constant hub height wind speed was maintained through a velocity controller. The study focuses on analyzing the wake’s flow field and providing insights into its recovery process. It was found that turbulence plays a critical role in a faster wake recovery as well as increasing the power production of the turbine for sheared inflows and the wind speed selected.
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Bodini, Nicola, Dino Zardi, and Julie K. Lundquist. "Three-dimensional structure of wind turbine wakes as measured by scanning lidar." Atmospheric Measurement Techniques 10, no. 8 (2017): 2881–96. http://dx.doi.org/10.5194/amt-10-2881-2017.
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Abstract. The lower wind speeds and increased turbulence that are characteristic of turbine wakes have considerable consequences on large wind farms: turbines located downwind generate less power and experience increased turbulent loads. The structures of wakes and their downwind impacts are sensitive to wind speed and atmospheric variability. Wake characterization can provide important insights for turbine layout optimization in view of decreasing the cost of wind energy. The CWEX-13 field campaign, which took place between June and September 2013 in a wind farm in Iowa, was designed to explore the interaction of multiple wakes in a range of atmospheric stability conditions. Based on lidar wind measurements, we extend, present, and apply a quantitative algorithm to assess wake parameters such as the velocity deficits, the size of the wake boundaries, and the location of the wake centerlines. We focus on wakes from a row of four turbines at the leading edge of the wind farm to explore variations between wakes from the edge of the row (outer wakes) and those from turbines in the center of the row (inner wakes). Using multiple horizontal scans at different elevations, a three-dimensional structure of wakes from the row of turbines can be created. Wakes erode very quickly during unstable conditions and can in fact be detected primarily in stable conditions in the conditions measured here. During stable conditions, important differences emerge between the wakes of inner turbines and the wakes of outer turbines. Further, the strong wind veer associated with stable conditions results in a stretching of the wake structures, and this stretching manifests differently for inner and outer wakes. These insights can be incorporated into low-order wake models for wind farm layout optimization or for wind power forecasting.
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Castorrini, A., L. Tieghi, V. F. Barnabei, et al. "Wake interaction in offshore wind farms with mesoscale derived inflow condition and sea waves." IOP Conference Series: Earth and Environmental Science 1073, no. 1 (2022): 012009. http://dx.doi.org/10.1088/1755-1315/1073/1/012009.
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Abstract Numerical simulation is an indispensable tool for the design and optimization of wind farms layout and control strategies for energy loss reduction. Achieving consistent simulation results is strongly related to the definition of reliable weather and sea conditions, as well as the use of accurate computational fluid dynamics (CFD) models for the simulation of the wind turbines and wakes. Thus, we present a case study aiming to evaluate the wake-rotor interaction between offshore multi-MW wind turbines modelled using the Actuator Line Model (ALM) and realistic wind inflow conditions. In particular, the interaction between two DTU10 wind turbines is studied for two orientations of the upstream turbine rotor, simulating the use of a yaw-based wake control strategy. Realistic wind inflow conditions are obtained using a multi-scale approach, where the wind field is firstly computed using mesoscale numerical weather prediction (NWP). Then, the mesoscale vertical wind profile is used to define the wind velocity and turbulence boundary conditions for the high-fidelity CFD simulations. Sea waves motion is also imposed using a dynamic mesh approach to investigate the interaction between sea waves, surface boundary layer, and wind turbine wakes and loads.
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Iungo, G. V., and F. Porté-Agel. "Measurement procedures for characterization of wind turbine wakes with scanning Doppler wind LiDARs." Advances in Science and Research 10, no. 1 (2013): 71–75. http://dx.doi.org/10.5194/asr-10-71-2013.
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Abstract. The wake flow produced from an Enercon E-70 wind turbine is investigated through three scanning Doppler wind LiDARs. One LiDAR is deployed upwind to characterize the incoming wind, while the other two LiDARs are located downstream to carry out wake measurements. The main challenge in performing measurements of wind turbine wakes is represented by the varying wind conditions, and by the consequent adjustments of the turbine yaw angle needed to maximize power production. Consequently, taking into account possible variations of the relative position between the LiDAR measurement volume and wake location, different measuring techniques were carried out in order to perform 2-D and 3-D characterizations of the mean wake velocity field. However, larger measurement volumes and higher spatial resolution require longer sampling periods; thus, to investigate wake turbulence tests were also performed by staring the LiDAR laser beam over fixed directions and with the maximum sampling frequency. The characterization of the wake recovery along the downwind direction is performed. Moreover, wake turbulence peaks are detected at turbine top-tip height, which can represent increased fatigue loads for downstream wind turbines within a wind farm.
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Bangga, G., and E. Bossanyi. "BladedFarmWake: A framework for evaluating the influence of upstream wakes on turbine loads using Bladed." Journal of Physics: Conference Series 2767, no. 9 (2024): 092025. http://dx.doi.org/10.1088/1742-6596/2767/9/092025.
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Abstract A new framework “BladedFarmWake” to include the upstream wake effects into a wind turbine design tool Bladed was developed in the present work. The effects of neighboring turbines in a wind farm are extracted from a wind farm flow solver LongSim, which has been developed for designing wind farm controllers and evaluating wind farm performance, taking account of atmospheric conditions and wake effects including the importance of turbine layouts and individual turbine or wind farm control strategies. These wind farm effects are incorporated into Bladed simulations to obtain time accurate load analyses. BladedFarmWake is designed to work with less human interaction as much as possible, allowing the tool to be adopted in large scale load analyses within the wind turbine design load cases (DLCs). It is demonstrated that the timeseries of the wind flow field and the wake meandering effects are successfully modelled in the framework. The effects of velocity deficit and the wake added turbulence are well captured in the generated turbulent data. As a consequence of the velocity deficit from the upstream turbine, the hub load changes considerably due to the wake meandering effects. The newly developed integrated framework will be of value for wind turbine engineers to incorporate wind farm effects in the design process.
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Doubrawa, Paula, Kelsey Shaler, and Jason Jonkman. "Difference in load predictions obtained with effective turbulence vs. a dynamic wake meandering modeling approach." Wind Energy Science 8, no. 9 (2023): 1475–93. http://dx.doi.org/10.5194/wes-8-1475-2023.
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Abstract. According to the international standard for wind turbine design, the effects of wind turbine wakes on structural loads can be considered in two ways: (1) by augmenting the ambient turbulence levels with the effective turbulence model (EFF) and then calculating the resulting loads and (2) by performing dynamic wake meandering (DWM) simulations, which compute wake effects and loads for all turbines on a farm at once. There is no definitive answer in scientific literature as to the consequences of choosing one model over the other, but the two approaches are unarguably very different. The work presented here expounds on these differences and investigates to what extent they affect the simulated structural loads. We consider an idealized 4×4 rectangular array of National Renewable Energy Laboratory 5 MW wind turbines with a spacing of 5 by 8 rotor diameters and three wind speed scenarios at high ambient turbulence. Load simulations are performed in OpenFAST with EFF and in FAST.Farm with the DWM implementation. We compare ambient turbulence, wind farm turbulence, and loads between both approaches. When omnidirectional results are compared, EFF wind farm turbulence intensity is consistently higher by 0.2 % (above-rated wind speed) to 2.7 % (below-rated wind speed). However, for certain wind directions, the EFF turbulence can be lower than FAST.Farm by almost 9 %. Wind speeds within the farm were found to differ by up to 3 m s−1 due to the lack of wake deficits in the EFF approach, leading to longer tails toward low values in the FAST.Farm mean load distributions. Consistent with the turbulence results, the median EFF load standard deviations are also consistently higher, by a maximum of 20 % and 17 % for blade-root out-of-plane and tower-base fore-aft moments, respectively.
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Guo, Feng, and David Schlipf. "A Spectral Model of Grid Frequency for Assessing the Impact of Inertia Response on Wind Turbine Dynamics." energies 14, no. 9 (2021): 2492. https://doi.org/10.3390/en14092492.
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Journal Paper published to energies (MDPI) The recent development in renewable energy has led to a higher proportion of converter-connected power generation sources in the grid. Operating a high renewable energy penetrated power system and ensuring the frequency stability could be challenging due to the reduced system inertia that is usually provided by the conventional synchronous generator. Wind turbines, as one major role of renewable generation sources, have the advantage to provide synthetic inertia response to the grid. This is achieved by controlling the kinetic energy extraction from the rotating parts by its converters. Previous studies have shown the potential of wind turbines to provide inertia response based on the measured rate of change of grid frequency. In this paper, we derive a spectral-based model of the grid frequency by analyzing historical measurements. The spectral model is then used to generate realistic, generic, and stochastic signals of the grid frequency for typical aero-elastic simulations of wind turbines. The spectral model enables the direct assessment of the additional impact of the inertia response control on wind turbines: the spectra of wind turbine output signals such as generator speed, tower base bending moment, and shaft torsional moment are calculated directly from the developed spectral model of the grid frequency and a commonly used spectral model of the turbulent wind with high accuracy. The calculation of output spectra is verified with non-linear time-domain simulation and spectral estimation. Based on this analysis, a notch filter is designed to alleviate significantly the negative impact on wind turbine structural loads due to inertia response with only small impacts on the grid support.
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Astolfi, Davide, Fabrizio De Caro, and Alfredo Vaccaro. "Characterizing the Wake Effects on Wind Power Generator Operation by Data-Driven Techniques." Energies 16, no. 15 (2023): 5818. http://dx.doi.org/10.3390/en16155818.
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Wakes between neighboring wind turbines are a significant source of energy loss in wind farm operations. Extensive research has been conducted to analyze and understand wind turbine wakes, ranging from aerodynamic descriptions to advanced control strategies. However, there is a relatively overlooked research area focused on characterizing real-world wind farm operations under wake conditions using Supervisory Control And Data Acquisition (SCADA) parameters. This study aims to address this gap by presenting a detailed discussion based on SCADA data analysis from a real-world test case. The analysis focuses on two selected wind turbines within an onshore wind farm operating under wake conditions. Operation curves and data-driven methods are utilized to describe the turbines’ performance. Particularly, the analysis of the operation curves reveals that a wind turbine operating within a wake experiences reduced power production not only due to the velocity deficit but also due to increased turbulence intensity caused by the wake. This effect is particularly prominent during partial load operation when the rotational speed saturates. The turbulence intensity, manifested in the variability of rotational speed and blade pitch, emerges as the crucial factor determining the extent of wake-induced power loss. The findings indicate that turbulence intensity is strongly correlated with the proximity of the wind direction to the center of the wake sector. However, it is important to consider that these two factors may convey slightly different information, possibly influenced by terrain effects. Therefore, both turbulence intensity and wind direction should be taken into account to accurately describe the behavior of wind turbines operating within wakes.
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Schottler, Jannik, Jan Bartl, Franz Mühle, Lars Sætran, Joachim Peinke, and Michael Hölling. "Wind tunnel experiments on wind turbine wakes in yaw: redefining the wake width." Wind Energy Science 3, no. 1 (2018): 257–73. http://dx.doi.org/10.5194/wes-3-257-2018.
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Abstract. This paper presents an investigation of wakes behind model wind turbines, including cases of yaw misalignment. Two different turbines were used and their wakes are compared, isolating effects of boundary conditions and turbine specifications. Laser Doppler anemometry was used to scan full planes of wakes normal to the main flow direction, six rotor diameters downstream of the respective turbine. The wakes of both turbines are compared in terms of the time-averaged main flow component, the turbulent kinetic energy and the distribution of velocity increments. The shape of the velocity increments' distributions is quantified by the shape parameter λ2. The results show that areas of strongly heavy-tailed distributed velocity increments surround the velocity deficits in all cases examined. Thus, a wake is significantly wider when two-point statistics are included as opposed to a description limited to one-point quantities. As non-Gaussian distributions of velocity increments affect loads of downstream rotors, our findings impact the application of active wake steering through yaw misalignment as well as wind farm layout optimizations and should therefore be considered in future wake studies, wind farm layout and farm control approaches. Further, the velocity deficits behind both turbines are deformed to a kidney-like curled shape during yaw misalignment, for which parameterization methods are introduced. Moreover, the lateral wake deflection during yaw misalignment is investigated.
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Yang, Hua, Liguo Liu, Xiaofeng Wang, et al. "Analysis of the impact of different inflow conditions on the wake and aerodynamic noise of wind turbines." Journal of Physics: Conference Series 2932, no. 1 (2025): 012024. https://doi.org/10.1088/1742-6596/2932/1/012024.
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Abstract This paper studies the aerodynamic performance and noise characteristics of a 6 MW horizontal axis wind turbine based on CFD fluid simulation and acoustic analogy method. The influence of different flow velocities on wind turbine wake and aerodynamic noise are compared. The result shows that: The main load source of the wind turbine is the shaft flow; the airflow through the engine room and the tower, the blade, and the tower will make the airflow speed through the wind turbine change, and form a large range of low-speed area in the rear of the wind wheel; the maximum axial velocity loss of wind turbine wakes at different sections under different flow speeds is located at the hub; the wake behind the wind turbine under high turbulence intensity obtains significantly higher energy than the low turbulence intensity during development; under different inflow velocity, the higher inflow velocity increases the aerodynamic noise, which is mainly affected by the tip vortex; under low turbulent intensity, different turbulence intensity has less influence on the wind turbine aerodynamic performance and aerodynamic noise.
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Iungo, Giacomo Valerio, Yu-Ting Wu, and Fernando Porté-Agel. "Field Measurements of Wind Turbine Wakes with Lidars." Journal of Atmospheric and Oceanic Technology 30, no. 2 (2013): 274–87. http://dx.doi.org/10.1175/jtech-d-12-00051.1.
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AbstractField measurements of the wake flow produced from a 2-MW Enercon E-70 wind turbine were performed using three scanning Doppler wind lidars. A GPS-based technique was used to determine the position of the wind turbine and the wind lidar locations, as well as the direction of the laser beams. The lidars used in this study are characterized by a high spatial resolution of 18 m, which allows the detailed characterization of the wind turbine wake. Two-dimensional measurements of wind speed were carried out by scanning a single lidar over the vertical symmetry plane of the wake. The mean axial velocity field was then retrieved by averaging 2D scans performed consecutively. To investigate wake turbulence, single lidar measurements were performed by staring the laser beam at fixed directions and using the maximum sampling frequency. From these tests, peaks in the velocity variance are detected within the wake in correspondence of the turbine top tip height; this enhanced turbulence could represent a source of dangerous fatigue loads for downstream turbines. The spectral density of the measured velocity fluctuations shows a clear inertial-range scaling behavior. Then, simultaneous measurements with two lidars were performed in order to characterize both the axial and the vertical velocity components. For this setup, the two velocity components were retrieved only for measurement points for which the two laser beams crossed nearly at a right angle. Statistics were computed over the sample set for both velocity components, and they showed strong flow fluctuations in the near-wake region at turbine top tip height, with a turbulence intensity of about 30%.
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Bartl, Jan, Franz Mühle, and Lars Sætran. "Wind tunnel study on power output and yaw moments for two yaw-controlled model wind turbines." Wind Energy Science 3, no. 2 (2018): 489–502. http://dx.doi.org/10.5194/wes-3-489-2018.
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Abstract. In this experimental wind tunnel study the effects of intentional yaw misalignment on the power production and loads of a downstream turbine are investigated for full and partial wake overlap. Power, thrust force and yaw moment are measured on both the upstream and downstream turbine. The influence of inflow turbulence level and streamwise turbine separation distance are analyzed for full wake overlap. For partial wake overlap the concept of downstream turbine yawing for yaw moment mitigation is examined for different lateral offset positions. Results indicate that upstream turbine yaw misalignment is able to increase the combined power production of the two turbines for both partial and full wake overlap. For aligned turbine setups the combined power is increased between 3.5 % and 11 % depending on the inflow turbulence level and turbine separation distance. The increase in combined power is at the expense of increased yaw moments on both the upstream and downstream turbine. For partial wake overlap, yaw moments on the downstream turbine can be mitigated through upstream turbine yawing. Simultaneously, the combined power output of the turbine array is increased. A final test case demonstrates benefits for power and loads through downstream turbine yawing in partial wake overlap. Yaw moments can be decreased and the power increased by intentionally yawing the downstream turbine in the opposite direction.
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Chatterjee, Tanmoy, Jing Li, Shashank Yellapantula, Balaji Jayaraman, and Eliot Quon. "Wind farm response to mesoscale-driven coastal low level jets: a multiscale large eddy simulation study." Journal of Physics: Conference Series 2265, no. 2 (2022): 022004. http://dx.doi.org/10.1088/1742-6596/2265/2/022004.
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Abstract Realistic atmospheric turbulence–wind farm interactions during coastal low-level jet (LLJ) events are captured using high-fidelity, mesoscale-driven large eddy simulations (LES) to understand wind turbine loads, wakes and overall performance. The simulation has been carried out using the ExaWind aeroelastic solver, AMR-Wind. The simulations have been compared against a baseline unstable case matching the wind speed, wind direction and TI at hub-height location. Results indicate that the LLJ has negative impacts on the turbine hub and tower loads, and opens up potential avenues for design load mitigation strategies.
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Rogers, Jonathan D. "Experimental evaluation of wind turbine wake turbulence impacts on a general aviation aircraft." Wind Energy Science 9, no. 9 (2024): 1849–68. http://dx.doi.org/10.5194/wes-9-1849-2024.
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Abstract. Continued development of wind farms near populated areas has led to rising concerns about the potential risk posed to general aviation aircraft when flying through wind turbine wakes. There is an absence of experimental flight test data available with which to assess this potential risk. This paper presents the results of an instrumented flight experiment in which a general aviation aircraft was flown through the wake of a utility-scale wind turbine at an operating wind farm. Wake passes were flown at different downwind distances from the turbine, and data were collected on the orientation disturbances, altitude and speed deviations, and acceleration loads experienced by the aircraft. Videos and pilot statements were also collected, providing qualitative information about the disturbances encountered in the wake. Results show that flight disturbances were small in all cases, with no difference observed between flight data inside and outside the wake at distances greater than six rotor diameters from the turbine. At distances closer than six rotor diameters, small load factor and orientation disturbances were noted but were commensurate with those experienced in light or moderate atmospheric turbulence. Overall, the loads and disturbances experienced were far smaller than those that would risk causing loss of control or structural damage.
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Conti, Davide, Vasilis Pettas, Nikolay Dimitrov, and Alfredo Peña. "Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals." Wind Energy Science 6, no. 3 (2021): 841–66. http://dx.doi.org/10.5194/wes-6-841-2021.
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Abstract. This study proposes two methodologies for improving the accuracy of wind turbine load assessment under wake conditions by combining nacelle-mounted lidar measurements with wake wind field reconstruction techniques. The first approach consists of incorporating wind measurements of the wake flow field, obtained from nacelle lidars, into random, homogeneous Gaussian turbulence fields generated using the Mann spectral tensor model. The second approach imposes wake deficit time series, which are derived by fitting a bivariate Gaussian shape function to lidar observations of the wake field, on the Mann turbulence fields. The two approaches are numerically evaluated using a virtual lidar simulator, which scans the wake flow fields generated with the dynamic wake meandering (DWM) model, i.e., the target fields. The lidar-reconstructed wake fields are then input into aeroelastic simulations of the DTU 10 MW wind turbine for carrying out the load validation analysis. The power and load time series, predicted with lidar-reconstructed fields, exhibit a high correlation with the corresponding target simulations, thus reducing the statistical uncertainty (realization-to-realization) inherent to engineering wake models such as the DWM model. We quantify a reduction in power and loads' statistical uncertainty by a factor of between 1.2 and 5, depending on the wind turbine component, when using lidar-reconstructed fields compared to the DWM model results. Finally, we show that the number of lidar-scanned points in the inflow and the size of the lidar probe volume are critical aspects for the accuracy of the reconstructed wake fields, power, and load predictions.
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Cardaun, Martin, Björn Roscher, Ralf Schelenz, and Georg Jacobs. "Analysis of Wind-Turbine Main Bearing Loads Due to Constant Yaw Misalignments over a 20 Years Timespan." Energies 12, no. 9 (2019): 1768. http://dx.doi.org/10.3390/en12091768.
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The compact design of modern wind farms means that turbines are located in the wake over a certain amount of time. This leads to reduced power and increased loads on the turbine in the wake. Currently, research has been dedicated to reduce or avoid these effects. One approach is wake-steering, where a yaw misalignment is introduced in the upstream wind turbine. Due to the intentional misalignment of upstream turbines, their wake flow can be forced around the downstream turbines, thus increasing park energy output. Such a control scheme reduces the turbulence seen by the downstream turbine but introduces additional load variation to the turbine that is misaligned. Within the scope of this investigation, a generic multi body simulation model is simulated for various yaw misalignments. The time series of the calculated loads are combined with the wind speed distribution of a reference site over 20 years to investigate the effects of yaw misalignments on the turbines main bearing loads. It is shown that damage equivalent loads increase with yaw misalignment within the range considered. Especially the vertical in-plane force, bending and tilt moment acting on the main bearing are sensitive to yaw misalignments. Furthermore, it is found that the change of load due to yaw misalignments is not symmetrical. The results of this investigation are a primary step and can be further combined with distributions of yaw misalignments for a study regarding specific load distributions and load cycles.
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Guilloré, A., F. Campagnolo, and C. L. Bottasso. "A control-oriented load surrogate model based on sector-averaged inflow quantities: capturing damage for unwaked, waked, wake-steering and curtailed wind turbines." Journal of Physics: Conference Series 2767, no. 3 (2024): 032019. http://dx.doi.org/10.1088/1742-6596/2767/3/032019.
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Abstract This paper presents a novel approach to constructing a load surrogate model. The surrogate estimates the damage equivalent loads (DELs) of a wind turbine of a given type regardless of its position within a wind farm, and under various farm control actions. The model relies solely on local inflow quantities (sector-averaged wind speeds and turbulence intensities) and local control parameters (rotor speed, pitch angle, and yaw misalignment). Despite its highly simplified representation of the complex behavior of the turbulent wind field, wake effects, and controller dynamics, these quantities prove sufficient to characterize DELs. The paper demonstrates the training of this load model within a simulation environment. Validation results using a different wind farm configuration indicate that the surrogate can accurately predict fatigue loads for both unwaked and waked turbines, encompassing scenarios of wake steering and induction control.
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Porté-Agel, Fernando, Majid Bastankhah, and Sina Shamsoddin. "Wind-Turbine and Wind-Farm Flows: A Review." Boundary-Layer Meteorology 174, no. 1 (2019): 1–59. http://dx.doi.org/10.1007/s10546-019-00473-0.
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Abstract Wind energy, together with other renewable energy sources, are expected to grow substantially in the coming decades and play a key role in mitigating climate change and achieving energy sustainability. One of the main challenges in optimizing the design, operation, control, and grid integration of wind farms is the prediction of their performance, owing to the complex multiscale two-way interactions between wind farms and the turbulent atmospheric boundary layer (ABL). From a fluid mechanical perspective, these interactions are complicated by the high Reynolds number of the ABL flow, its inherent unsteadiness due to the diurnal cycle and synoptic-forcing variability, the ubiquitous nature of thermal effects, and the heterogeneity of the terrain. Particularly important is the effect of ABL turbulence on wind-turbine wake flows and their superposition, as they are responsible for considerable turbine power losses and fatigue loads in wind farms. These flow interactions affect, in turn, the structure of the ABL and the turbulent fluxes of momentum and scalars. This review summarizes recent experimental, computational, and theoretical research efforts that have contributed to improving our understanding and ability to predict the interactions of ABL flow with wind turbines and wind farms.
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Simley, Eric, Paul Fleming, Nicolas Girard, Lucas Alloin, Emma Godefroy, and Thomas Duc. "Results from a wake-steering experiment at a commercial wind plant: investigating the wind speed dependence of wake-steering performance." Wind Energy Science 6, no. 6 (2021): 1427–53. http://dx.doi.org/10.5194/wes-6-1427-2021.
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Abstract. Wake steering is a wind farm control strategy in which upstream wind turbines are misaligned with the wind to redirect their wakes away from downstream turbines, thereby increasing the net wind plant power production and reducing fatigue loads generated by wake turbulence. In this paper, we present results from a wake-steering experiment at a commercial wind plant involving two wind turbines spaced 3.7 rotor diameters apart. During the 3-month experiment period, we estimate that wake steering reduced wake losses by 5.6 % for the wind direction sector investigated. After applying a long-term correction based on the site wind rose, the reduction in wake losses increases to 9.3 %. As a function of wind speed, we find large energy improvements near cut-in wind speed, where wake steering can prevent the downstream wind turbine from shutting down. Yet for wind speeds between 6–8 m/s, we observe little change in performance with wake steering. However, wake steering was found to improve energy production significantly for below-rated wind speeds from 8–12 m/s. By measuring the relationship between yaw misalignment and power production using a nacelle lidar, we attribute much of the improvement in wake-steering performance at higher wind speeds to a significant reduction in the power loss of the upstream turbine as wind speed increases. Additionally, we find higher wind direction variability at lower wind speeds, which contributes to poor performance in the 6–8 m/s wind speed bin because of slow yaw controller dynamics. Further, we compare the measured performance of wake steering to predictions using the FLORIS (FLOw Redirection and Induction in Steady State) wind farm control tool coupled with a wind direction variability model. Although the achieved yaw offsets at the upstream wind turbine fall short of the intended yaw offsets, we find that they are predicted well by the wind direction variability model. When incorporating the expected yaw offsets, estimates of the energy improvement from wake steering using FLORIS closely match the experimental results.
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Wang, Shifeng, and Sicong Wang. "Impacts of wind turbine characteristics on wake turbulence." Energy Storage and Conversion 3, no. 1 (2025): 1956. https://doi.org/10.59400/esc1956.
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The enhanced wake turbulence generated by wind turbine has remarkable effects on the power generation and fatigue loads of wind farm and the environment. The paper investigates the mechanism of the impacts of the wind turbine characteristics on the wake turbulence, to provide new knowledge on the design of wind turbine to wind turbine manufacturing factories. A novel wake turbulence coefficient is developed to quantify the ratio of the generated turbulence kinetic energy to the captured wind energy, and is derived as the function of wind turbine characteristics. This wake turbulence coefficient model is explored under optimal conditions. Results show that the wake turbulence coefficient decreases sharply with the increasing power coefficient of wind turbine. The larger the power coefficient is, the smaller the decrease of wake turbulence coefficient. Therefore, it is an effective way to reduce the enhanced wake turbulence through increasing the power coefficient, especially when the power coefficient is small. The wake turbulence intensity is the strongest around the hub of rotor and the weakest around the tip of rotor. It is therefore important to design the structure of the hub of rotor to reduce the enhanced wake turbulence.
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Khatamiaghda, Mohsen, Saeed Bahraminejad, and Roohollah Fadaeinedjad. "Power quality assessment in different wind power plant models considering wind turbine wake effects." Clean Energy 7, no. 4 (2023): 843–58. http://dx.doi.org/10.1093/ce/zkad033.
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Abstract The intense increase in the installed capacity of wind farms has required a computationally efficient dynamic equivalent model of wind farms. Various types of wind-farm modelling aim to identify the accuracy and simulation time in the presence of the power system. In this study, dynamic simulation of equivalent models of a sample wind farm, including single-turbine representation, multiple-turbine representation, quasi-multiple-turbine representation and full-turbine representation models, are performed using a doubly-fed induction generator wind turbine model developed in DIgSILENT software. The developed doubly-fed induction generator model in DIgSILENT is intended to simulate inflow wind turbulence for more accurate performance. The wake effects between wind turbines for the full-turbine representation and multiple-turbine representation models have been considered using the Jensen method. The developed model improves the extraction power of the turbine according to the layout of the wind farm. The accuracy of the mentioned methods is evaluated by calculating the output parameters of the wind farm, including active and reactive powers, voltage and instantaneous flicker intensity. The study was carried out on a sample wind farm, which included 39 wind turbines. The simulation results confirm that the computational loads of the single-turbine representation (STR), the multiple-turbine representation and the quasi-multiple-turbine representation are 1/39, 1/8 and 1/8 times the full-turbine representation model, respectively. On the other hand, the error of active power (voltage) with respect to the full-turbine representation model is 74.59% (1.31%), 43.29% (0.31%) and 7.19% (0.11%) for the STR, the multiple-turbine representation and the quasi-multiple representation, respectively.
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Ahmed, Fahim Masud, and Mostafa Bakhoday Paskyabi. "Effects of negative shear on loads for a 15 MW offshore wind turbine during low-level jet events." Journal of Physics: Conference Series 2626, no. 1 (2023): 012046. http://dx.doi.org/10.1088/1742-6596/2626/1/012046.
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Abstract Wind turbines are more often interacting with the negative shear region of a low-level jet due to increasing turbine sizes. However, the effects of negative shear on wind turbines are not sufficiently studied, particularly for offshore wind applications. In this paper, we studied the effects of negative shear on wind turbine loading. This was done using user-defined wind profiles and a model chain. The model chain consisted of a turbulence generator and a wake modelling tool coupled to an aero-hydro-servo-elastic engineering tool. We observed significant variations in the structural loading in the case of low-level jets. We also observed changes in the power spectral density estimates. Additionally, we briefly examined the wake recovery distance.
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Ranka, Preeti, Laura Valldecabres, Sebastian Schafhirt, and Wim Bierbooms. "Extreme wind speed ramp events: A measurement-based approach for improving the modelling of ultimate loads for wind turbine design." Journal of Physics: Conference Series 2265, no. 3 (2022): 032042. http://dx.doi.org/10.1088/1742-6596/2265/3/032042.
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Abstract Ramp events, i.e., significant changes in wind speed in a short time period, have become critically important to end-users. However, only a few studies address their impact on wind turbine loads. To the best of the authors’ knowledge, these results have not yet been validated with measurements. Therefore, this paper aims to investigate the impact of extreme wind speed ramps on ultimate wind turbine loads using eight months of offshore measurements. We also compare the measured loads with simulations following the International Electrotechnical Commission (IEC) extreme turbulence model, in order to improve the modelling of ultimate loads. This is because events with a 10-min horizontal wind speed standard deviation higher than the prescribed IEC turbulence class, in line with other research, are primarily associated with ramp events. They are found to be design driving for the blade root flap-wise moments below and beyond rated wind speed, but not in the transition region. The high-frequency analysis of these moments showed a sudden pitch transition from the inactive to the active region. In general, the loads associated with ramp events did not exceed the simulations. In addition, non-ramp related extreme loads around rated wind speed, which exceeded the simulations, were associated with standard deviations slightly above the normal turbulence model (NTM) of IEC for a waked turbine, indicating the impact of wake added turbulence. In conclusion, for the ultimate load analysis, the wind speed time series should include a sudden pitch transition from the inactive to the active region in addition to wake added turbulence.
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Zhao, Rongyong, Daheng Dong, Cuiling Li, et al. "An Improved Power Control Approach for Wind Turbine Fatigue Balancing in an Offshore Wind Farm." Energies 13, no. 7 (2020): 1549. http://dx.doi.org/10.3390/en13071549.
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Increasing maintenance costs will hinder the expansion of the wind power industry in the coming decades. Training personnel, field maintenance, and frequent boat or helicopter visits to wind turbines (WTs) is becoming a large cost. One reason for this cost is the routine turbine inspection repair and other stochastic maintenance necessitated by increasingly unbalanced figure loads and unequal turbine fatigue distribution in large-scale offshore wind farms (OWFs). In order to solve the problems of unbalanced fatigue loads and unequal turbine fatigue distribution, thereby cutting the maintenance cost, this study analyzes the disadvantages of conventional turbine fatigue definitions. We propose an improved fatigue definition that simultaneously considers the mean wind speed, wind wake turbulence, and electric power generation. Further, based on timed automata theory, a power dispatch approach is proposed to balance the fatigue loads on turbines in a wind farm. A control topology is constructed to describe the logical states of the wind farm main controller (WFMC) in an offshore wind farm. With this novel power control approach, the WFMC can re-dispatch the reference power to the wind turbines according to their cumulative fatigue value and the real wind conditions around the individual turbines in every power dispatch time interval. A workflow is also designed for the control approach implementation. Finally, to validate this proposed approach, wind data from the Horns Rev offshore wind farm in Denmark are used for a numerical simulation. All the simulation results with 3D and 2D figures illustrate that this approach is feasible to balance the loads on an offshore wind farm. Some significant implications are that this novel approach can cut the maintenance cost and also prolong the service life of OWFs.
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Baungaard, M., M. Abkar, M. P. van der Laan, and M. Kelly. "A numerical investigation of a wind turbine wake in non-neutral atmospheric conditions." Journal of Physics: Conference Series 2265, no. 2 (2022): 022015. http://dx.doi.org/10.1088/1742-6596/2265/2/022015.
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Abstract Wind turbine wakes cause energy losses and increased blade fatigue loads in wind farms. The magnitude of these effects depend strongly on the atmospheric conditions. In nonneutral atmospheric conditions, there is a turbulence kinetic energy (TKE) contribution from buoyancy, either positive (convective boundary layer, CBL) or negative (stable boundary layer, SBL). In this work, both conditions are analyzed with new large-eddy simulation (LES) data of a single wind turbine wake in flat, homogeneous terrain to quantify the effects of buoyancy. It is found that the buoyancy contribution is negligible compared to the shear production in the wake region and the role of buoyancy is therefore mainly to alter the inflow profiles. This fact is used in a simple Reynolds-averaged Navier-Stokes (RANS) turbulence model, which shows reasonable results for wake velocity deficit compared to LES data.
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Alletto, Michael, Jan Woesmann, Marcus O. Letzel, and Malte Heyen. "Wind Turbine Loads in the Near Wake." Journal of Physics: Conference Series 2767, no. 9 (2024): 092047. http://dx.doi.org/10.1088/1742-6596/2767/9/092047.
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Abstract This work is analyzing the the engineering wake models Frandsen and TNO for small inter-turbine distances. Therefore, loads generated by actuator line LES (AL-LES) wind fields will be compared with the loads generated by the mentioned engineering models. The results are checked for plausibility by comparing the current results with the available literature. Load comparisons for non-dimensional distances x/D ranging from 1.75 to 4 and for seven different wind speeds in order to consider the influence of the thrust coefficient were made. For each speed a low and a high turbulence intensity case is considered. Two latest generation turbines are investigated (one with a diameter of 138 m and one with a diameter of 175 m).Our studies reveal that the fatigue loads computed with the Frandsen and TNO model are conservative compared to the loads generated by AL-LES wind fields. The Wöhler averaged (m=10 and a sector of 120°) flap wise blade root bending moments are at least 150% higher for the TNO and Frandsen model compared to the loads generated by AL-LES wind fields for distances lower than 2.3D and C T values higher than 0.7. This indicates that current sector management rules applied by means of the results of the Frandsen and TNO model are too restrictive. A possible way to decrease the conservatism without posing at risk the structural integrity of the turbines is the following: The wake added turbulence intensity can be kept constant for regions in the parameter space with very high conservatism (e.g. for distances smaller than 2.3D and C T values higher than 0.7).
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Mann, Jakob, and Abdul Haseeb Syed. "Simulating low-frequency wind fluctuations." Wind Energy Science 9, no. 6 (2024): 1381–91. https://doi.org/10.5194/wes-9-1381-2024.
Full textAbstract:
Large-scale flow structures are vital in influencing the dynamic response of floating wind turbines and wake meandering behind large offshore wind turbines. It is imperative that we develop an inflow wind turbulence model capable of replicating the large-scale and low-frequency wind fluctuations occurring in the marine atmosphere since the current turbulence models do not account well for this phenomenon. Here, we present a method to simulate low-frequency wind fluctuations. This method employs the two-dimensional (2D) spectral tensor for low-frequency, anisotropic wind fluctuations presented by Syed and Mann (2024) to generate stochastic wind fields. The simulation method generates large-scale 2D spatial wind fields for the longitudinal u and lateral v wind components, which can be converted into a frequency domain using Taylor’s frozen turbulence hypothesis. The low-frequency wind turbulence is assumed to be independent of the high-frequency turbulence; thus, a broad spectral representation can be obtained just by superposing the two turbulent wind fields. The method is tested by comparing the simulated and theoretical spectra and co-coherences of the combined lowand high-frequency fluctuations. Furthermore, the low-frequency wind fluctuations can also be subjected to anisotropy. The resulting wind fields from this method can be used to analyze the impact of low-frequency wind fluctuations on wind turbine loads and dynamic response and to study the wake meandering behind large offshore wind farms.
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Sood, Ishaan, Elliot Simon, Athanasios Vitsas, Bart Blockmans, Gunner C. Larsen, and Johan Meyers. "Comparison of large eddy simulations against measurements from the Lillgrund offshore wind farm." Wind Energy Science 7, no. 6 (2022): 2469–89. http://dx.doi.org/10.5194/wes-7-2469-2022.
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Abstract. Numerical simulation tools such as large eddy simulations (LESs) have been extensively used in recent years to simulate and analyze turbine–wake interactions within large wind farms. However, to ensure the reliability of the performance and accuracy of such numerical solvers, validation against field measurements is essential. To this end, a measurement campaign is carried out at the Lillgrund offshore wind farm to gather data for the validation of an in-house LES solver. Flow field data are collected from the farm using three long-range WindScanners, along with turbine performance and load measurements from individual turbines. Turbulent inflow conditions are reconstructed from an existing precursor database using a scaling-and-shifting approach in an optimization framework, proposed so that the generated inflow statistics match the measurements. Thus, five different simulation cases are setup, corresponding to five different inflow conditions at the Lillgrund wind farm. Operation of the 48 Siemens 2.3 MW turbines from the Lillgrund wind farm is parameterized in the flow domain using an aeroelastic actuator sector model (AASM). Time-series turbine performance metrics from the simulated cases are compared against field measurements to evaluate the accuracy of the optimization framework, turbine model, and flow solver. In general, results from the numerical solver exhibited a good comparison in terms of the trends in power production, turbine loading, and wake recovery. For four out of the five simulated cases, the total wind farm power error was found to be below 5 %. However, when comparing individual turbine power production, statistical significant errors were observed for 16 % to 84 % of the turbines across the simulated cases, with larger errors being associated with wind directions resulting in configurations with aligned turbines. While the compared flapwise loads in general show a reasonable agreement, errors greater than 100 % were also present in some cases. Larger errors in the wake recovery in the far wake region behind the lidar installed turbines were also observed. An analysis of the observed errors reveals the need for an improved controller implementation, improvement in representing meso-scale effects, and possibly a finer simulation grid for capturing the smaller scales of wake turbulence.
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Kim, Jaewook, Sanghwan Heo, and WeonCheol Koo. "Analysis of Dynamic Response Characteristics for 5 MW Jacket-type Fixed Offshore Wind Turbine." Journal of Ocean Engineering and Technology 35, no. 5 (2021): 347–59. http://dx.doi.org/10.26748/ksoe.2021.058.
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This study aims to evaluate the dynamic responses of the jacket-type offshore wind turbine using FAST software (Fatigue, Aerodynamics, Structures, and Turbulence). A systematic series of simulation cases of a 5 MW jacket-type offshore wind turbine, including wind-only, wave-only, wind & wave load cases are conducted. The dynamic responses of the wind turbine structure are obtained, including the structure displacement, rotor speed, thrust force, nacelle acceleration, bending moment at the tower bottom, and shear force on the jacket leg. The calculated time-domain results are transformed to frequency domain results using FFT and the environmental load with more impact on each dynamic response is identified. It is confirmed that the dynamic displacements of the wind turbine are dominant in the wave frequency under the incident wave alone condition, and the rotor thrust, nacelle acceleration, and bending moment at the bottom of the tower exhibit high responses in the natural frequency band of the wind turbine. In the wind only condition, all responses except the vertical displacement of the wind turbine are dominant at three times the rotor rotation frequency (considering the number of blades) generated by the wind. In a combined external force with wind and waves, it was observed that the horizontal displacement is dominant by the wind load. Additionally, the bending moment on the tower base is highly affected by the wind. The shear force of the jacket leg is basically influenced by the wave loads, but it can be affected by both the wind and wave loads especially under the turbulent wind and irregular wave conditions.
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Shaw, William J., Larry K. Berg, Mithu Debnath, et al. "Scientific challenges to characterizing the wind resource in the marine atmospheric boundary layer." Wind Energy Science 7, no. 6 (2022): 2307–34. http://dx.doi.org/10.5194/wes-7-2307-2022.
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Abstract. With the increasing level of offshore wind energy investment, it is correspondingly important to be able to accurately characterize the wind resource in terms of energy potential as well as operating conditions affecting wind plant performance, maintenance, and lifespan. Accurate resource assessment at a particular site supports investment decisions. Following construction, accurate wind forecasts are needed to support efficient power markets and integration of wind power with the electrical grid. To optimize the design of wind turbines, it is necessary to accurately describe the environmental characteristics, such as precipitation and waves, that erode turbine surfaces and generate structural loads as a complicated response to the combined impact of shear, atmospheric turbulence, and wave stresses. Despite recent considerable progress both in improvements to numerical weather prediction models and in coupling these models to turbulent flows within wind plants, major challenges remain, especially in the offshore environment. Accurately simulating the interactions among winds, waves, wakes, and their structural interactions with offshore wind turbines requires accounting for spatial (and associated temporal) scales from O(1 m) to O(100 km). Computing capabilities for the foreseeable future will not be able to resolve all of these scales simultaneously, necessitating continuing improvement in subgrid-scale parameterizations within highly nonlinear models. In addition, observations to constrain and validate these models, especially in the rotor-swept area of turbines over the ocean, remains largely absent. Thus, gaining sufficient understanding of the physics of atmospheric flow within and around wind plants remains one of the grand challenges of wind energy, particularly in the offshore environment. This paper provides a review of prominent scientific challenges to characterizing the offshore wind resource using as examples phenomena that occur in the rapidly developing wind energy areas off the United States. Such phenomena include horizontal temperature gradients that lead to strong vertical stratification; consequent features such as low-level jets and internal boundary layers; highly nonstationary conditions, which occur with both extratropical storms (e.g., nor'easters) and tropical storms; air–sea interaction, including deformation of conventional wind profiles by the wave boundary layer; and precipitation with its contributions to leading-edge erosion of wind turbine blades. The paper also describes the current state of modeling and observations in the marine atmospheric boundary layer and provides specific recommendations for filling key current knowledge gaps.
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Battaglia, Laura, Marco Schauer, and Gustavo Ríos Rodríguez. "Gravity-Based Offshore Wind Turbine Dynamic Response Analysis under Combined Wind and Water Waves Actions." Resúmenes de Mecánica Computacional 1, no. 13 (2024): 129. https://doi.org/10.70567/rmc.v1i13.189.
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Gravity based foundations are usually used for small and medium size offshore wind turbines installed in shallow and intermediate water depths. In this work, the dynamic response of a reference wind turbine of 5MW rated power with this kind of foundation is studied, taking into account the soil-structure interaction. To this end, a strategy based on a coupled finite element and scaled-boundary finite element methods is adopted. It is considered that the wind turbine is subjected both to wind and water waves loads. The action of turbulent aerodynamic loads is computed with OpenFAST while that of the water waves is computed with OpenFOAM following a highly non-linear streamFunction model with a k-epsilon turbulence model, using a volume of fluid strategy. Different mesh discretizations are convenient for each model, so non-matching grids are unavoidable, particularly between the water and the structure, and between the foundation and the soil. Therefore, a convenient algorithm was developed and used to transfer the data between the sub-problems. Information like displacements, velocity, and stresses at specific locations of the tower, its foundation and the soil are analyzed and compared with reference data in order to assess the capabilities of the proposed strategies and their implementation.
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Aju, Emmanuvel Joseph, Dhanush Bhamitipadi Suresh, and Yaqing Jin. "The Influence of Winglet Pitching on the Performance of a Model Wind Turbine: Aerodynamic Loads, Rotating Speed, and Wake Statistics." Energies 13, no. 19 (2020): 5199. http://dx.doi.org/10.3390/en13195199.
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The objective of this study is to investigate the influence of winglet pitching as an aero-brake on the performance of a model wind turbine by wind tunnel experiments. Time-resolved particle image velocimetry, force sensor, and datalogger were used to characterize the coupling between wake statistics, aerodynamic loads, and rotation speed. Results highlighted that, for a winglet with 4% of the rotor diameter length, the increase of its pitching angle can significantly reduce the turbine rotation speed up to ∼28% and thrust coefficient of ∼20%. The winglet pitching induced minor influence on the velocity deficit in the very near wake regions, while its influence on accelerating the wake recovery become clear around three diameters downstream the turbine rotor. The turbulence kinetic energy exhibited a distinctive increase under large pitching angles in the near wake region at the turbine hub height due to the strong vertical flow fluctuations. Further investigation on the spectra of wake velocities revealed that the pitching of winglet can suppress the high-pass filtering effects of turbines on wake fluctuations; such large-scale turbulence facilitated the flow mixing and accelerated the wake transport.
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Mühle, Franz V., Florian M. Heckmeier, Filippo Campagnolo, and Christian Breitsamter. "Wind tunnel investigations of an individual pitch control strategy for wind farm power optimization." Wind Energy Science 9, no. 5 (2024): 1251–71. http://dx.doi.org/10.5194/wes-9-1251-2024.
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Abstract. This article presents the results of an experimental wind tunnel study which investigates a new control strategy named Helix. The Helix control employs individual pitch control for sinusoidally varying yaw and tilt moments to induce an additional rotational component in the wake, aiming to enhance wake mixing. The experiments are conducted in a closed-loop wind tunnel under low-turbulence conditions to emphasize wake effects. Highly sensorized model wind turbines with control capabilities similar to full-scale machines are employed in a two-turbine setup to assess wake recovery potential and explore loads on both upstream and downstream turbines. In a single-turbine study, detailed wake measurements are carried out using a fast-response five-hole pressure probe. The results demonstrate a significant improvement in energy content within the wake, with distinct peaks for clockwise and counterclockwise movements at Strouhal numbers of approximately 0.47. Both upstream and downstream turbine dynamic equivalent loads increase when applying the Helix control. The time-averaged wake flow streamwise velocity and rms value reveal a faster wake recovery for actuated cases in comparison to the baseline. Phase-locked results with azimuthal position display a leapfrogging behavior in the baseline case in contrast to the actuated cases, where distorted shedding structures in the longitudinal direction are observed due to a changed thrust coefficient and an accompanying lateral vortex shedding location. Additionally, phase-locked results with the additional frequency reveal a tip vortex meandering, which enhances faster wake recovery. Comparing the Helix cases with clockwise and counterclockwise rotations, the latter exhibits slightly higher gains and faster wake recovery. This difference is attributed to Helix' additional rotational component acting in either the same or the opposite direction as the wake rotation. Overall, both Helix cases exhibit significantly faster wake recovery compared to the baseline, indicating the potential of this technique for improved wind farm control.
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Syed, Abdul Haseeb, and Jakob Mann. "Simulating low-frequency wind fluctuations." Wind Energy Science 9, no. 6 (2024): 1381–91. http://dx.doi.org/10.5194/wes-9-1381-2024.
Full textAbstract:
Abstract. Large-scale flow structures are vital in influencing the dynamic response of floating wind turbines and wake meandering behind large offshore wind turbines. It is imperative that we develop an inflow wind turbulence model capable of replicating the large-scale and low-frequency wind fluctuations occurring in the marine atmosphere since the current turbulence models do not account well for this phenomenon. Here, we present a method to simulate low-frequency wind fluctuations. This method employs the two-dimensional (2D) spectral tensor for low-frequency, anisotropic wind fluctuations presented by Syed and Mann (2024) to generate stochastic wind fields. The simulation method generates large-scale 2D spatial wind fields for the longitudinal u and lateral v wind components, which can be converted into a frequency domain using Taylor's frozen turbulence hypothesis. The low-frequency wind turbulence is assumed to be independent of the high-frequency turbulence; thus, a broad spectral representation can be obtained just by superposing the two turbulent wind fields. The method is tested by comparing the simulated and theoretical spectra and co-coherences of the combined low- and high-frequency fluctuations. Furthermore, the low-frequency wind fluctuations can also be subjected to anisotropy. The resulting wind fields from this method can be used to analyze the impact of low-frequency wind fluctuations on wind turbine loads and dynamic response and to study the wake meandering behind large offshore wind farms.
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Pedersen, Mads Mølgaard, Torben Juul Larsen, Helge Aagaard Madsen, and Gunner Christian Larsen. "More accurate aeroelastic wind-turbine load simulations using detailed inflow information." Wind Energy Science 4, no. 2 (2019): 303–23. http://dx.doi.org/10.5194/wes-4-303-2019.
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Abstract. In this paper, inflow information is extracted from a measurement database and used for aeroelastic simulations to investigate if using more accurate inflow descriptions improves the accuracy of the simulated wind-turbine fatigue loads. The inflow information is extracted from nearby meteorological masts (met masts) and a blade-mounted five-hole pitot tube. The met masts provide measurements of the inflow at fixed positions some distance away from the turbine, whereas the pitot tube measures the inflow while rotating with the rotor. The met mast measures the free-inflow velocity; however the measured turbulence may evolve on its way to the turbine, pass beside the turbine or the mast may be in the wake of the turbine. The inflow measured by the pitot tube, in comparison, is very representative of the wind that acts on the turbine, as it is measured close to the blades and also includes variations within the rotor plane. Nevertheless, this inflow is affected by the presence of the turbine; therefore, an aerodynamic model is used to estimate the free-inflow velocities that would have occurred at the same time and position without the presence of the turbine. The inflow information used for the simulations includes the mean wind speed field and trend, the turbulence intensity, the wind-speed shear profile, atmospheric stability-dependent turbulence parameters, and the azimuthal variations within the rotor plane. In addition, instantaneously measured wind speeds are used to constrain the turbulence. It is concluded that the period-specific turbulence intensity must be used in the aeroelastic simulations to make the range of the simulated fatigue loads representative for the range of the measured fatigue loads. Furthermore, it is found that the one-to-one correspondence between the measured and simulated fatigue loads is improved considerably by using inflow characteristics extracted from the pitot tube instead of using the met-mast-based sensors as input for the simulations. Finally, the use of pitot-tube-recorded wind speeds to constrain the inflow turbulence is found to significantly decrease the variation of the simulated loads due to different turbulence realizations (seeds), whereby the need for multiple simulations is reduced.
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Weislein, Tobias, Ferdinand Seel, Thorsten Lutz, and Ewald Krämer. "Numerical investigation of the vortical structures in the near wake of a model wind turbine." Journal of Physics: Conference Series 2767, no. 2 (2024): 022008. http://dx.doi.org/10.1088/1742-6596/2767/2/022008.
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Abstract It is well known that the vortex system in a horizontal axis wind turbine wake is highly relevant in terms of fatigue loads and performance of wind turbines located in the wake of other wind turbines. The breakdown process of tip vortices particularly influences the mixing process of the low-speed wake region with the undisturbed flow outside the wake. As a collaboration with the Technische Universität Berlin (TUB), a major goal in a joint research is to study the effects involved in tip vortex breakdown. TUB designed a model turbine that will be towed through a large water tank to analyse and to control the tip vortex decay. To accommodate the measurement equipment, the ratio of blade length to nacelle length is unconventionally small, leading to uncertainty regarding the effect on the breakdown of the tip vortex. Due to the dimensions of the model wind turbine the root vortex system and the nacelle wake are not comparable to former studies and should therefore be investigated in detail. To do so computational fluid dynamics, in particular delayed detached eddy simulations, are conducted for the model turbine with the compressible flow solver FLOWer and the two-equation Menter-SST turbulence model. Two simulations are conducted with and without the nacelle. The results indicate that the root vortices propagate downstream and interact with each other. Additionally, these vortical structures are also influenced by the geometry of the turbine nacelle which causes faster decay of the root vortices compared to a configuration without the nacelle. However, the root vortex breakdown does not influence the tip vortices as the turbulent intensity matches for the area where tip vortices are present. In short, this investigation shows that the influence of the nacelle geometry and root vortex system on the tip vortices is negligible. Thus, the model wind turbine designed by TUB is suitable for the investigation of tip vortices.
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Wiley, Will, Jason Jonkman, Amy Robertson, and Kelsey Shaler. "Sensitivity analysis of numerical modeling input parameters on floating offshore wind turbine loads." Wind Energy Science 8, no. 10 (2023): 1575–95. http://dx.doi.org/10.5194/wes-8-1575-2023.
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Abstract. Floating wind turbines must withstand a unique and challenging set of loads from the wind and ocean environment. To de-risk development, accurate predictions of these loads are necessary. Uncertainty in modeling predictions leads to larger required safety factors, increasing project costs and the levelized cost of energy. Complex aero-hydro-elastic modeling tools use many input parameters to represent the wind, waves, current, aerodynamic loads, hydrodynamic loads, and structural properties. It is helpful to understand which of these parameters ultimately drives a design. In this work, an ultimate and fatigue-proxy load sensitivity analysis was performed with 35 different input parameters, using an elementary effects approach to identify the most influential parameters for a case study involving the National Renewable Energy Laboratory (NREL) 5 MW baseline wind turbine atop the OC4-DeepCwind semisubmersible during normal operation. The importance of each parameter was evaluated using 14 response quantities of interest across three operational wind speed conditions. The study concludes that turbulent wind velocity standard deviation is the parameter with the strongest sensitivity; this value is important not just for turbine loads, but also for the global system response. The system center of mass in the wind direction is found to have the highest impact on the system rotation and tower loads. The current velocity is found to be the most dominating parameter for the system global motion and consequently the mooring loads. All tested wind turbulence parameters in addition to the standard deviation are also found to be influential. Wave characteristics are influential for some fatigue-proxy loading but do not significantly impact the extreme ultimate loads in these operational load cases. The required number of random seeds for stochastic environmental conditions is considered to ensure that the sensitivities are due to the input parameters and not due to the seed. The required number of analysis points in the parameter space is identified so that the conclusions represent a global sensitivity. The results are specific to the platform, turbine, and choice of parameter ranges, but the demonstrated approach can be applied widely to guide focus in parameter uncertainty.
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Liew, Jaime, Tuhfe Göçmen, Alan W. H. Lio, and Gunner Chr Larsen. "Extending the dynamic wake meandering model in HAWC2Farm: a comparison with field measurements at the Lillgrund wind farm." Wind Energy Science 8, no. 9 (2023): 1387–402. http://dx.doi.org/10.5194/wes-8-1387-2023.
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Abstract. With the increasing growth of wind farm installations, the impact of wake effects caused by wind turbines on power output, structural loads, and revenue has become more relevant than ever. Consequently, there is a need for precise simulation tools to facilitate efficient and cost-effective design and operation of wind farms. To address this need, we present HAWC2Farm, a dynamic and versatile aeroelastic wind farm simulation methodology that combines state-of-the-art engineering models to accurately capture the complex physical phenomena in wind farms. HAWC2Farm employs the aeroelastic wind turbine simulator, HAWC2, to model each individual turbine within the wind farm. It utilises a shared, large-scale turbulence box to represent atmospheric flow field effects at the farm level. The methodology incorporates a modified version of the dynamic wake meandering model to accurately capture wake interactions. This approach not only ensures computational efficiency but also provides valuable insights for wind farm design and operation. To assess its performance, HAWC2Farm is compared using time series extracted from field measurements at the Lillgrund wind farm, encompassing various scenarios involving wake steering via yaw control and a turbine shutdown. The results indicate that HAWC2Farm effectively addresses the challenges associated with modelling the complex dynamics within wind farms, thereby enabling more precise, informed, and cost-effective design and operation strategies.
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Bakhoday-Paskyabi, Mostafa, Maria Krutova, Hai Bui, and Xu Ning. "Multiscale Simulation of Offshore Wind Variability During Frontal Passage: Brief Implication on Turbines’ Wakes and Load." Journal of Physics: Conference Series 2362, no. 1 (2022): 012003. http://dx.doi.org/10.1088/1742-6596/2362/1/012003.
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Enhancing the performance of offshore wind park power production requires, to a large extent, a better understanding of the interactions of wind farms and individual wind turbines with the atmospheric boundary layer over a wide range of spatiotemporal scales. In this study, we use a multiscale atmospheric model chain coupled offline with the aeroelastic Fatigue, Aerodynamics, Structures, and Turbulence (FAST) code. The multiscale model contains two different components in which the nested mesoscale Weather and Research Forecast (WRF) model is coupled offline with the Parallelized Large-eddy Simulation Model (PALM). Such a multiscale framework enables to study in detail the turbine behaviour under various atmospheric forcing conditions, particularly during transient atmospheric events.
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Alkumet, Adel A., Mohammed A. Mohammed, and Abdullateef A. Jadallah. "A Review of Multi-Wind Turbine Systems, Design, Cost and Productivity." Journal of Advanced Research in Fluid Mechanics and Thermal Sciences 129, no. 2 (2025): 38–55. https://doi.org/10.37934/arfmts.129.2.3855.
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One of the most important methods used to reduce manufacturing and maintenance costs for single-rotor wind turbines is to replace them with a multi-rotor turbine system, which captures the same amount of energy expended by the single turbine. The multi-rotor turbine system consists of several small turbines that reduce system loads and improve reliability. However, the use of this type of system faces many challenges, which many researchers and designers are working to overcome to reach an ideal design at the lowest cost in manufacturing, operation and maintenance with the best performance. This study presents the main reasons for using and developing multi-rotor wind turbines in terms of efficiency and cost, and the methods used by researchers and manufacturers to enhance the efficiency of this type of wind turbines. This review article will present an in-depth investigation of the power generating capabilities, cost concerns, and design characteristics of multi rotor wind turbines. By integrating current research and data on this revolutionary technology, this article hopes to add to the continuing conversation around sustainable energy alternatives and guide future developments in the field. Furthermore, multi-rotor turbines have faster wake recovery times, resulting in lower turbulence intensity in the wake than typical single-rotor turbines. Control of multi-rotor turbines is critical for reducing structural stress while increasing power output, necessitating advanced control algorithms and simulations. Noise prediction and control in multi-rotor systems provide additional issues, with rotor proximity influencing performance and noise production, demanding high-fidelity approaches for reliable predictions. Overall, while multi-rotor wind turbines improve performance, they also introduce complexity in design, control, and noise management that need careful analysis and innovative solutions.
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Zúñiga Inestroza, M. A., J. M. Mattuella, A. R. Wittwer, and A. M. Loredo-Souza. "Wind tunnel experiments for investigating wake effects in atmospheric boundary layers using a simplified miniature model wind turbine." Journal of Physics: Conference Series 2265, no. 2 (2022): 022083. http://dx.doi.org/10.1088/1742-6596/2265/2/022083.
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Abstract The clustering of wind turbines within a prospective site is prone to significant wake interactions, which have a negative impact in terms of loads and plant performance. Further improvements in the design and control of wind farms can be achieved through a detailed assessment of wake effects under site-specific conditions. The aim of this paper was to investigate wake effects in atmospheric boundary layer (ABL) flows using a simplified model wind turbine. First, we performed experiments under smooth- and turbulent-uniform inflows to highlight the wake features of the model. Second, we evaluated the interactions with two different neutrally stratified ABL: i) ABL Type-I (α = 0.11, TI = 6 %), ii) ABL Type-II (α = 0.23, TI = 13 %), where α is the incident wind shear and TI is the turbulence intensity. For each case, hot-wire anemometry was used to obtain wake mean velocity, turbulence intensity and power spectrum profiles at four different downstream positions. We also included a comparison with three analytical wake models to get further indications on the experimental measurements. First results showed that the simplified model is well-suited for its intended purpose. The largest discrepancies between experiments and model predictions were in the near-wake region and in cases with lower background turbulence. We also corroborated a strong influence of the incoming wind profile on how fast the wake recovers to the undisturbed conditions. Furthermore, this study provided an initial framework to explore the ABL wind tunnel at Universidade Federal do Rio Grande do Sul (UFRGS) as a viable tool for research in wind energy.
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Reinwardt, Inga, Levin Schilling, Dirk Steudel, Nikolay Dimitrov, Peter Dalhoff, and Michael Breuer. "Validation of the dynamic wake meandering model with respect to loads and power production." Wind Energy Science 6, no. 2 (2021): 441–60. http://dx.doi.org/10.5194/wes-6-441-2021.
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Abstract. The outlined analysis validates the dynamic wake meandering (DWM) model based on loads and power production measured at an onshore wind farm with small turbine distances. Special focus is given to the performance of a version of the DWM model that was previously recalibrated at the site. The recalibration is based on measurements from a turbine nacelle-mounted lidar system. The different versions of the DWM model are compared to the commonly used Frandsen wake-added turbulence model. The results of the recalibrated wake model agree very well with the measurements, whereas the Frandsen model overestimates the loads drastically for short turbine distances. Furthermore, lidar measurements of the wind speed deficit as well as the wake meandering are incorporated in the DWM model definition in order to decrease the uncertainties.
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Damiani, Rick, Scott Dana, Jennifer Annoni, et al. "Assessment of wind turbine component loads under yaw-offset conditions." Wind Energy Science 3, no. 1 (2018): 173–89. http://dx.doi.org/10.5194/wes-3-173-2018.
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Abstract. Renewed interest in yaw control for wind turbine and power plants for wake redirection and load mitigation demands a clear understanding of the effects of running with skewed inflow. In this paper, we investigate the physics of yawed operations, building up the complexity from a simplified analytical treatment to more complex aeroelastic simulations. Results in terms of damage equivalent loads (DELs) and extreme loads under misaligned conditions of operation are compared to data collected from an instrumented, utility-scale wind turbine. The analysis shows that multiple factors are responsible for the DELs of the various components and that airfoil aerodynamics, elastic characteristics of the rotor, and turbulence intensities are the primary drivers. Both fatigue and extreme loads are observed to have relatively complex trends with yaw offsets, which can change depending on the wind-speed regime. Good agreement is found between predicted and measured trends for both fatigue and ultimate loads.
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Céspedes Moreno, Juan Felipe, Juan Pablo Murcia León, and Søren Juhl Andersen. "Convergence and efficiency of global bases using proper orthogonal decomposition for capturing wind turbine wake aerodynamics." Wind Energy Science 10, no. 3 (2025): 597–611. https://doi.org/10.5194/wes-10-597-2025.
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Abstract. Wind turbine wakes affect power production and loads but are highly turbulent and therefore complex to model. Proper orthogonal decomposition (POD) has often been applied for reduced-order models (ROMs), as POD yields an orthogonal basis optimal in terms of capturing the turbulent kinetic energy content. POD is typically used to understand flow physics and reconstruct a specific flow case. However, reduced-order models have been proposed for predicting wind turbine wake aerodynamics by applying POD on multiple flow cases with different governing parameters to derive a global basis intended to represent all flows within the parameter space. This article evaluates the convergence and efficiency of global POD bases covering multiple cases of wind turbine wake aerodynamics in large wind farms. The analysis shows that the global POD bases have better performance across the parameter space than the optimal POD basis computed from a single dataset. The error associated with using a global basis across the parameter space of reconstructions decreases and converges as the dataset is expanded with more flow cases, and there is a low sensitivity as to which datasets to include. It is also shown how this error is an order of magnitude smaller than the truncation error for 100 modes. Finally, the global basis has the advantage of providing consistent physical interpretability of the highly turbulent flow within wind farms.