bluuebunny/crossref_metadata_2025 huggingface dataset:
Spinner anemometer: wind speed and Spinner Transfer Function seasonal robustness in an offshore wind farm
Authors: Ritter K , Gómez Arranz P
Published: September 2020

This work presents the first, long-term, demonstration case of the use of spinner anemometers for power curve measurements in an offshore wind farm. The stability of the spinner anemometer wind speed and its STF during a 22-month measurement period was quantified, using a nacelle lidar as reference. Power curves and annual energy productions (AEPs) were obtained using this long-term data set, to assess the spinner anemometer wind speed stability. Next, several STFs were obtained at a reference turbine in different periods (four two-months periods) to assess the STF seasonality. Finally, the AEPs of three neighbouring turbines were analysed using the STFs generated at the reference turbine.
Lidar-based Estimation of Turbulence Intensity for Controller Scheduling
Authors: Schlipf David , Guo Feng , Raach Steffen
Published: September 2020

Lidar-assisted wind turbine control is a promising technology and various concepts have been developed. This paper aims to add another concept to the list by describing how turbulence intensity can be estimated and used for controller scheduling to reduce structural loads. The turbulence intensity estimation is applied to lidar data from aero-elastic simulations and good agreement with the turbulence intensity calculation from wind fields is obtained. Further, a controller scheduling scheme is proposed to adjust the power level based on the estimated turbulence intensity. In a first simulation study, the scheduling scheme is able to reduce the power and extreme loads on the tower during severe turbulence conditions while keeping a similar level of power production and fatigue loads for normal turbulent conditions.
On the Use of Cambered Plate Airfoils for Small Wind Turbines
Authors: Kummer Aaron , Dimeo Jack , Hebel Mark , Visser Kenneth
Published: September 2020

The use of constant thickness, cambered plates is being explored as a means to reduce the cost of rotors for small wind turbines. Literature suggests that at low Reynolds numbers there is an advantage over conventional airfoils, and tests conducted on a 2.5 m ducted rotor indicate a constant thickness airfoil to be a viable solution. An operational turbine with a 3 m rotor was developed and is currently being tested. Data supports predictions and shows encouraging results.
Holistic Design of Small-scale Stand-alone Wind Energy Conversion Systems Using Locally Manufactured Small Wind Turbines
Authors: Latoufis Kostas , Serafeim Giannis , Chira Katerina , Riziotis Vasilis , Voutsinas Spyros , Hatziargyriou Nikos
Published: September 2020

A holistic and multi-disciplinary design approach is developed for small-scale stand-alone wind energy conversion systems (WECS) using locally manufactured small wind turbines (LMSWTs), with the aim of reducing capital and maintenance costs while increasing the annual energy production and energy utilization of such systems. Various subsystems are analysed and modelled, using both sequential and integrated design approaches, such as the rotor, including the airfoil and blade geometries, the axial flux permanent magnet generator including economic, thermal and structural aspects of the stator and rotor geometry, the furling system and the electrical system, including the power transmission cables and the battery bank. The holistic design approach is then applied to a 2.4m rotor diameter LMSWT and the complete WECS is dimensioned. Finally, the designed low cost system is compared to a high cost system using a maximum power point converter, with satisfactory results especially for low wind speeds around the mean wind speed of the site. It is thus concluded that a holistic and multi-disciplinary design approach to small-scale stand-alone WECS using LMSWTs, can lower the cost of energy for rural electrification applications by reducing capital costs, while sustaining the system’s efficiency and annual energy production in low wind speed regions.
Wind turbine rotor design under wind farm control laws
Authors: Sartori L , Fidelibus P De , Cacciola S , Croce A
Published: September 2020

In this work, we investigate the impact of different wind farm control techniques on the structural design of a 10MW reference wind turbine. Active wake mixing and wake redirection have been recently proposed as a way to reduce wake-turbine interference in a wind farm and both show potential for improving the overall power production. However, such controllers modify the dynamic behaviour of the individual turbine, so that a thorough assessment of the resulting loads and displacements becomes necessary. In fact, as most wind turbines are designed according to international standards, one or more structural constraints are active on the final design, meaning that an increase of the sizing loads, or deflections, would make necessary to modify the structural layout. To investigate these aspects, we compare three redesigns of the same rotor: the first is equipped with a standard controller, while the second and the third integrate different wind farm controllers. All the solutions are optimized with our in-house design tool so that the three configurations emerge from the same design process. Results are then compared in terms of ultimate and fatigue loads, displacements and blade mass.
Progressive structural scaling of a 20 MW two-bladed offshore wind turbine rotor blade examined by finite element analyses
Authors: Schütt Marcel , Anstock Fabian , Schorbach Vera
Published: September 2020

Two-bladed turbines offer a promising opportunity for rotor cost savings, especially considering the ongoing growth trend in rotor size. An increased chord and airfoil thickness of a two-bladed turbine’s blade results in potential structural improvements caused by a rapidly growing second moment of area. Compared to a three-bladed turbine’s blade, the blade structure would theoretically require less material, while withstanding 50% higher flapwise loads. An analytical method of progressive structural scaling for three-dimensional rotor blade structures, based on equal material stresses, is introduced to calculate the modified structural thickness properties of the two-bladed turbine’s blade. It simplifies the airfoil-shaped structure to a thin-walled rectangle, utilizes a fixed initial flapwise load factor, and scales the edgewise loads proportionally to the required blade mass. To evaluate the validity of this analytical approach, a progressively scaled and an iterated 20 MW two-bladed turbine’s blade are examined with finite element analyses for static loads. The outcomes are then compared to corresponding analyses of a three-bladed turbine’s reference blade. Overall, the static stress comparisons at different blade positions show good agreement with the analytical results. Nevertheless, the buckling analyses performed reveal stability issues, which subsequently will lead to a readjustment of the blade mass.
CFD Investigation of Separation Control on a Vertical Axis Wind Turbine: Steady and Unsteady Suction
Authors: Rezaeiha Abdolrahim , Montazeri Hamid , Blocken Bert
Published: September 2020

High-fidelity two-dimensional unsteady Reynolds-averaged Navier-Stokes (URANS) simulations are employed to investigate the influence of boundary layer suction through a slot located near the leading edge of a vertical axis wind turbine operating in dynamic stall. The analysis includes both steady and unsteady suction with different frequencies. The results shows that: (i) when the suction slot is located within the chordwise extent of the laminar separation bubble, dynamic stall can be avoided with minimal suction amplitude; (ii) the most promising suction location is the most upstream suction location studied, at 8.5%c where c is the blade chord length; (iii) the suction only needs to be applied during the azimuthal angles when dynamic stall occurs; (iv) the oscillation frequency of the suction velocity has insignificant influence on the obtained turbine power gain; (v) applying unsteady suction is interesting as it reduces the energy consumption of the suction system, thus the net power gain.
Best practice for verification of wind turbine numerical models
Authors: Huhn Matthias L. , Popko Wojciech
Published: September 2020

The analysis of wind turbines relies on aero-hydro-servo-elastic simulation tools. OC3, 4, 5, 6 projects showed that much effort is required to obtain consistency in numerical models set up and the agreement in the simulation results. To mitigate the uncertainty in the model setup and to reduce the time spent on its verification, a robust verification procedure is necessary. The presented verification procedure provides a structured and efficient way of checking and comparing aeroelastic wind turbine models. In case a discrepancy between the two models or the model and documentation is found, a procedure for finding the source of this discrepancy is suggested. During several successful applications of the presented verification procedure, it proved to reduce the effort, the number of iteration loops and thus the consumed time that is required to achieve a verified model.
Dynamic stall at high Reynolds numbers due to variant types of airfoil motion
Authors: Kiefer J , Brunner C E , Hultmark M , Hansen MOL
Published: September 2020

Unsteady airfoil experiments were conducted in a high-pressure wind tunnel at chord Reynolds numbers of Rec = 3.0 × 106. A moderately thick NACA0021 airfoil was pitched from rest beyond the static stall angle in six individual ramp tests with increasing and decreasing angles of attack. The variant types of motion of the pitching maneuvers were characterized by constant angular velocity, angular acceleration and angular jerk, respectively. The ramp-up experiments revealed a substantial and time-dependent excess of the aerodynamic forces from static values in all three test cases and exhibited a distinct time delay as a consequence of the variant motion types. Similarly, the ramp-down experiments were largely impacted by the progression of the pitching motion, resulting in pronounced differences in the temporal development of lift and drag. Results are shown as time series of integrated forces and surface pressure distributions.
Dynamic stall on an airfoil undergoing VAWT blade angle of attack variations
Authors: Henne Sabrina , Fouest Sébastien Le , Mulleners Karen
Published: September 2020

Vertical axis wind turbines have several attractive features in the context of energy production in urban areas, but the inherent aerodynamic complexity of the flow around them has challenged their development on a larger scale. They generally operate at low tip speed ratios, where dynamic stall occurs on the blades. The vortex shedding associated with dynamic stall causes highly transient and heavy stress cycles that reduce the aerodynamic performance and increase the risk of fatigue and failure. The flow around an airfoil undergoing VAWT blade angle of attack variations was investigated using particle image velocimetry and force measurements. The formation of vortices and the lift force were studied for different tip speed ratios. A special focus was put on the effect of the asymmetry of the motion. The role of dynamic stall vortices on aerodynamic coeffients was evidenced by comparing experimental data to analytical predictions obtained from Theodorsen’s model. For the lowest equivalent tip speed ratio clockwise and counter clockwise rotating dynamic stall vortices formed on the airfoil with increasing and decreasing angle of attack. The asymmetry in motion lead to an asymmetry in size of the clockwise and counter-clockwise vortices. As the asymmetry in motion has a strong effect on the flow behaviour, the local pitch rate was proposed as a governing parameter. The increase of extrema with increasing pitch rate varies for increasing and decreasing angle of attack, indicating an additional influence of the history of the flow development.
Prediction of an advanced spar’s horizontal motions, validated by full scale observation data
Authors: Yoshimoto Haruki , Wright Christopher , Wada Ryota , Takagi Ken
Published: September 2020

As the offshore wind industry moves into deeper waters, the number of different floating wind platform concepts continues to expand. Accurately predicting the motion characteristics of these novel platforms is crucial to the safe and economic conversion of wind energy into electricity. A challenge in the currently used numerical simulation methods involves successfully predicting the slow drift motions and damping, especially in complex realistic environmental conditions which include multi-directional spectral waves, current and wind loading. Of most uncertainty to these predictions is determining the low frequency viscous damping which dominates the resonant surge and sway motions. In this paper, full-scale motion observations of the Fukushima FORWARD’s floating wind substation are used to determine the platforms viscous drag forces. These drag coefficients are used in a combined potential flow and Morison’s equation model to capture the observed behaviour. This validated numerical model is then used to describe the required fidelity of mooring line models, in order to aid platform developers in the early stages of design.
Full scale rotor blade deformation measurements in comparison with aeroelastic simulations based on measured high-resolution wind fields
Authors: Lehnhoff S , Sekar AP Kidambi , van Dooren M F , Kühn M , Seume J R
Published: September 2020

Aeroelasticity is one of the biggest challenges in wind turbine rotor design, as the length of rotor blades increases which comes along with a slenderer design. The knowledge of the aeroelastic turbine behavior is of great importance. A comparison to field measurements is of huge importance when validating aeroelastic tools. However, the measurement of deformation and torsion in the field is not trivial and the conduction of realistic post-test simulations is a challenge. One crucial factor for these simulations is the wind field, which needs to be captured in a high spatial and temporal resolution. In this paper, the results of deformation measurements conducted in the field with an optical measurement method called Digital Image Correlation (DIC) on one rotor blade will be shown and compared to aeroelastic post-test simulations using highly resolved wind fields measured with a SpinnerLidar.
Study on cyclic pitch control of HAWT by using instantaneous inflow observation
Authors: Kamada Y , Maeda T , Takai K , Mizuno S
Published: September 2020

The power output of a wind turbine depends on both wind speed and turbine control. There is a fluctuation in the natural wind speed, which changes the turbine power output. In this paper blade pitch control based on detailed monitoring of the inflow wind, including vertical velocity distributions, has been experimentally evaluated in a field test wind turbine. The inflow wind speeds were observed by 11 sets of ultrasonic anemometers. In this first test, the blade pitch is changed to keep optimum angle of attack based on the local inflow wind speed in the rotor plane. The blade pitch is independently controlled as a reference radial position of 80% of rotor radius. As a result of the pitch controls, the wind turbine power output was increased and the power output fluctuation was decreased for the cyclic pitch control based on the local wind speed. With the cyclic pitch control, the fluctuation in rotor thrust and average rotor thrust were also reduced compere to collective pitch control.
Stress-based assessment of the lifetime extension for wind turbines
Authors: Saathoff M , Rosemeier M
Published: September 2020

To assess of the lifetime extension (LTE) of wind turbines, the remaining fatigue budget of different turbine components is predicted. The state-of-the-art approach to predicting the LTE uses a comparison of damage-equivalent loads (DEL) under site conditions and design conditions. The DEL-based approach entails several simplifications, i.e., neglecting the load direction and the mean load. An analysis based on stresses can mitigate the above simplifications. In this work, the LTE of a 1.5 MW turbine is assessed on the basis of the DEL-based approach and compared to that of the stress-based approach. The assessment focuses on components which are critical for the lifetime, i.e., the blade bolts, the blade root laminate, and the main shaft. Generic models of these components are implemented to calculate stress histories for the stress-based assessment. In addition, the main assumptions that may have to be based on estimates are outlined. The analysis shows that, depending on the component, the results of the stress-based approach may differ notably from those of the DEL-based approach. The stress-based approach can be used to improve model fidelity in LTE assessments.
Cage Loads of Wind Turbine Blade Bearing
Authors: Buescher M , Leupold S , Schelenz R , Jacobs G
Published: September 2020

Slewing bearings of wind turbine blades pitch system allow the required oscillation while transferring complex dynamical loads from the rotor blades towards the hub. Most common for this application are double rowed four-point contact ball bearings consisting of two rings and two rolling element sets either equipped with a ring cage or with spacers. By equally distributing the rolling elements along the circumference, the bearing cage balances the loads along the raceways and thereby actively prevents damage mechanisms. However, cage stress analyses imply further optimization potentials leading to higher load capacities and the prediction of cage damaging mechanisms via dynamic simulations. This contribution presents a simulation procedure that calculates rolling element dynamics at the presence of a ring cage by taking the perpendicular movement of the contact ellipses due to the elastic deformations of the bearing rings into account. The procedure is carried out exemplary by the load spectra of a 3 MW reference wind turbine and the actual geometry of a 2.4m diameter bearing.
DES vs RANS: The flatback airfoil case
Authors: Papadakis George , Manolesos Marinos , Diakakis Konstantinos , Riziotis Vasilis A.
Published: September 2020

Using flatback airfoils at the root of wind turbine (WT) blades is becoming more popular as the WTs increase in size. The reason is that they provide significant aerodynamic, aeroelastic and structural benefits. However, due to the blunt trailing edge (TE), the wake of such airfoils is highly unsteady and rich in three-dimensional vortical structures. This poses significant challenges on the numerical simulation of the flow around them, given the highly unsteady, three-dimensional turbulent character of their wake. In this work, computational predictions for a flatback airfoil employing both RANS and DES approaches on three successively refined grids up to 25 million cells are compared with available experimental data. Results suggest that even though URANS and DDES are in good agreement in terms of lift and drag, RANS simulations fail to accurately capture the turbulent wake unsteady characteristics.
Quantification of the Dynamic-stall Model Uncertainty in the Performance Prediction of Vertical Axis Wind Turbines
Authors: Persico Giacomo , Sanvito Andrea G. , Dossena Vincenzo
Published: September 2020

Low-fidelity predictions for vertical-axis wind turbines are affected by uncertainty due to the complexity of the rotor aerodynamics. In particular, in the most common operating conditions the blades undergo periodic excursions beyond the static stall limit, activating dynamic-stall effects. In this study we show how advanced dynamic-stall models, implemented in the frame of the Blade-Element-Momentum theory, are able to upgrade significantly the prediction of low-fidelity tools, both in deterministic and probabilistic terms. In particular, an uncertainty quantification is performed to investigate the epistemic uncertainty of the Strickland dynamic-stall model, introducing a large variability on the empirical parameters appearing in the formulation. The resulting variability in the power coefficient and torque exchange, compared to corresponding wind-tunnel and high-fidelity CFD values, remains relatively limited and, in the conditions around peak efficiency, it is comparable with the measurement uncertainty of the experiment. As a further relevant conclusion, the model uncertainty does not alter the general outcome of the deterministic model, thus demonstrating the robustness of the DMST predictions obtained in the present study.
Active Aerodynamic Load Control for Improved Wind Turbine Design
Authors: Griffith D. Todd , Fine Neal E. , Cooney John A. , Rotea Mario A. , Valerio Iungo G.
Published: September 2020

Historically, cost reduction in wind energy has been accomplished by increasing hub heights and rotor diameters to capture more energy per turbine. However, larger wind turbines cannot be expected to lead to lower LCOE without the addition of new technologies. Capital costs grow rapidly with rotor diameter, faster than the rated power, because as rotor diameter increases, the blades get heavier and more costly. The growth in blade mass with blade length is accelerated by the additional structure that must be added to withstand unsteady aerodynamic loads caused by turbulence, gusts, wind shear, misaligned yaw, upwind wakes, and the tower shadow. This paper presents a holistic design solution to integrate active load control via dielectric barrier discharge (DBD) plasma actuators into wind turbine rotors along with initial findings on load reduction, actuator development, and rotor mass reduction.
Effects of yaw misalignment on platform motions and fairlead tensions of the OO-Star Wind Floater Semi 10MW floating wind turbine
Authors: Özinan Umut , Kretschmer Matthias , Lemmer Frank , Cheng Po Wen
Published: September 2020

Floating offshore wind farms (FOWFs) are subject to wake effects similar to onshore and fixed-bottom offshore wind farms. Due to the smaller surface roughness, wake recovery is slower in offshore compared to onshore wind farms. Therefore, wake mitigation methods will become relevant for FOWFs as it is for onshore and fixed-bottom offshore wind farms. A common method is to apply yaw misalignment to steer the wake out of the rotor of the downwind turbine. However, it is necessary to investigate possible effects of yaw misalignment on a single turbine before farm-level investigations. This study focuses on the motion response of the platform and damage equivalent loads (DELs) of the mooring line tensions of the OO-Star Wind Floater Semi 10MW floating wind turbine. In order to satisfy environmental variability, the effect of yaw misalignment is investigated at different wind directions and wind/wave misalignments. DELs of three mooring line tensions at the fairleads were calculated using the rainflow algorithm and were reported as relative, normalized with respect to the aligned nacelle operation. Floater motions were analyzed to understand effects of misaligned operation. The results indicate that yawed inflow leads to a complex coupled response of floating offshore wind turbines (FOWTs). At slightly above rated wind speed, the yaw misalignment generally increases DELs due to the thrust increase. Conversely, yaw misalignment operation at below rated wind speeds leads to different responses on lines depending on environmental conditions. The steady state floater position has a large impact on DELs which may lead to a yet unknown response behavior of FOWFs. DEL trends in the presence of wind/wave misalignment are similar to those of aligned wind and wave.
Improving site-dependent power curve prediction accuracy using regression trees
Authors: Barber S , Nordborg H
Published: September 2020

The accurate prediction of the power production of a wind turbine at a particular site is important in both the planning and operation phases; however, the standard power curve binning method is not specific to the atmospheric conditions at the site. In this work, the application of machine learning for improving the accuracy of site-specific power predictions by taking into account turbulence intensity and shear is investigated, by creating a set of 8,000 ten-minute long aero-servo-elastic simulations of the NREL 5MW reference wind turbine at a random combination of hub-height wind speeds, turbulence intensities and shear factors using cloud computing with the software ASHES. A regression tree with maximum depth of eight and optimised with Adaptive Boosting is trained using a random selection of half of the data. For a set of 50 random test cases, the Root Mean Square Error of the predicted power compared to the simulated power is found to be three times smaller than for the standard power curve method of binning. OEMs could use this method to train a model for the dependency of power production on wind speed, turbulence intensity and shear in the certification phase of a given wind turbine type, which could then be applied by the wind farm planner or operator at any given site for which measurements of the atmospheric conditions are available. Similar success is observed for out-of-plane tip deflections. This result is highly dependent on the quality and distribution of the input data, and therefore this work is being used as a basis for the analysis of real measurement data, as well as for comparisons to other methods such as Artificial Neural Networks.
Large eddy simulation study of extended wind farms with large inter turbine spacing
Authors: Stevens Richard J.A.M. , Meneveau Charles
Published: September 2020

We study the performance of extended wind farms with very large inter turbine spacings, i.e. with an inter turbine spacing of more than 10 turbine diameters, using large-eddy simulations (LES) for the special case of neutral conditions. We compare the results with predictions from different analytical modeling approaches and discuss in which parameter regimes the different model predictions agree with the LES predictions. We find in LES that the normalized power output variance increases further downstream in the wind farm. Besides, we analyze the power output correlation between the subsequent downstream turbines. We find that the correlations decrease with increasing turbine spacing due to the increased mixing induced by the wind turbine wakes. For all cases considered here, the power output correlation with downstream turbines becomes negligible after about 40 turbine diameters.
Actual Total Cost reduction of commercial CFD modelling tools for Wind Resource Assessment in complex terrain
Authors: Barber S , Schubiger A , Koller S , Rumpf A , Knaus H , Nordborg H
Published: September 2020

In this paper, new automated processes for applying the commercial Computational Fluid Dynamics (CFD) tools ANSYS Fluent and ANSYS CFX to wind modelling in complex terrain are developed with the goal of decreasing the Actual Total Costs (ATC) related to planning wind energy projects. Simulations are carried out at the complex terrain site Stotten in southern Germany using ANSYS Fluent and ANSYS CFX, and the ATCs related to the simulations estimated. The simulation set-up and post-processing effort are identified as having the highest effect on the ATC, and therefore the automated processes focus on reducing the effort of these tasks. Simulations of the same test site are carried out with the new automated processes, and compared to the manual processes as well as to an industry-standard tool, WindSim. The new automated tools are found to reduce the ATC of this case by a factor of 12 for Fluent and seven for CFX, to approximately half the value of WindSim. All three simulations show similar deviations compared to measurements and therefore these results are comparable. It should be noted that these results are highly specific to this case, and the absolute cost-saving values cannot be directly transferred to other cases. Nevertheless, it can be concluded that these new processes have significantly reduced the Actual Total Cost and are likely to have a large effect on the choice of the most cost-effective model for a given wind energy project. On-going work involves quantifying the effect of these cost savings on the choice of most appropriate model for this simulation site and further comparing the results to measurements.
The effects of Open Cellular Convection on Wind Farm Operation and Wakes
Authors: Göçmen Tuhfe , Larsén Xiaoli Guo , Imberger Marc
Published: September 2020

Majority of the severe variability in power production of an offshore wind farm occurs when open cellular convection (OCC) is observed. With a diameter of 10-80 km, the open cells are essentially the main drivers of hour-scale wind fluctuations passing through the wind farm. Here we aim to quantify the impact of the OCC on Horns Rev-I offshore wind farm located in the North Sea, in terms of variance in the power production and turbulence intensity. Using mesoscale simulations, met-mast measurements and high frequency (1 Hz) SCADA data from all the operating turbines, the behaviour of power deficit and added turbulence intensity is explored comparatively with and without presence of open cells. The investigation is a case study performed on a ‘day-to-day’ basis with an in depth analysis of the in-farm effects, such as the wake behaviour and smaller scale atmospheric structures. For the investigated event, the study shows striking difference in wind farm operation under the open cell structures and underlines the importance of taking local mesoscale phenomena into account for wind farm operation monitoring and control, short-term wake estimation, forecasting and market participation.
Influence of the direction of rotation on the wake characteristics of closely spaced counter-rotating vertical-axis wind turbines
Authors: Vergaerde Antoine , Troyer Tim De , Muggiasca Sara , Bayati Ilmas , Belloli Marco , Runacres Mark C.
Published: September 2020

Closely spaced counter-rotating vertical-axis wind turbines (VAWTs) exhibit a considerable power improvement compared to the same turbines in isolation. It thus makes sense to study their potential for wind farm production optimisation. With this objective in mind, the wake of an isolated VAWT is compared experimentally to the wake of counter-rotating VAWTs. Because of the unsteady aerodynamics, the wake of an isolated VAWT deflects towards the region behind its upwind moving blade. The direction of rotation thus directly influences the deflection of the wake. For paired configurations, it is possible to use this wake deflection as an advantage. A pair of counter-rotating VAWTs where the upwind moving blades are at the centre of the pair, exhibits a particularly narrow wake. With the benefit of a power improvement and a narrow wake, closely spaced counter-rotating VAWTs exhibit promising characteristics to improve the power density in a wind farm.
WRF-Simulated Springtime Low-Level Jets over Iowa: Implications for Wind Energy
Authors: Aird J A , Barthelmie R J , Shepherd T J , Pryor S C
Published: September 2020

High-resolution simulations with the Weather Research and Forecasting (WRF) model are analyzed to characterize the frequency, intensity, height, and duration of springtime low-level jets (LLJ) and their implications for wind energy resource assessment and planning in Iowa. The time evolution of short-duration LLJ is analyzed to understand wind behavior around LLJ events and to illustrate their importance for high-frequency (few hours) variability in wind speeds and rotor plane turbulent kinetic energy (TKE). During spring, the LLJ core height has a spatiotemporal mean value of 217 m, but the LLJ depth means it frequently intersects typical wind turbine rotor planes. Nearly one-quarter of LLJ exhibit a maximum within the height interval 50-150 m AGL. LLJ profiles are found to have higher mean wind speeds across typical wind turbine rotor planes than non-LLJ profiles and to exhibit lower values of TKE. LLJ occur under stable stratification (i.e. positive Richardson numbers) and are associated with low TKE and the occurrence of high vertical wind shear. The frequency and duration of LLJ exhibit geospatial variability across Iowa with highest values in the northeast of the state. Analyses of daytime and night-time LLJ indicate topographic variability is an important factor in the development of LLJ.
Towards the development of a wake meandering model based on neural networks
Authors: Yang Xiaolei
Published: September 2020

In this work, we develop a neural network model for predicting the instantaneous wake position, which is crucial for a wake meandering model. The data used for training are from the large-eddy simulation of a utility-scale wind turbine. A neural network of four hidden layers with 128 units for each layer is found to be effective when training the model. Effects of different input features on the accuracy of the trained model are systematically tested. It is found that the input features including the downwind and crosswind velocities at two locations upwind of the turbine and the thrust and torque acting on the turbine are enough to guarantee the accuracy of the trained model. Without using the thrust and torque as the input features, the accuracy of the model is significantly worse.
The impact of weather patterns on offshore wind power production
Authors: Cheneka Bedassa R , Watson Simon J , Basu Sukanta
Published: September 2020

Large-scale weather systems have the potential to modulate offshore wind energy production. The Northern European sea areas have recently seen a rapid increase in wind power capacity and thus there is a need to understand how different weather systems affect offshore production from the perspective of energy system integration. In this study, mean sea level pressure data from a new-generation reanalysis (ERA5) are utilised to classify synoptic systems into 30 different weather patterns using a self-organising map (SOM) approach. ERA5 wind speeds are then used in conjunction with a reference 8 MW wind turbine power curve to estimate wind power values at selected offshore sites. We assess how wind power output varies for different weather patterns, specifically, the impact on power production and power ramps.
How accurate is a machine learning-based wind speed extrapolation under a round-robin approach?
Authors: Bodini Nicola , Optis Mike
Published: September 2020

As the size of commercial wind turbines keeps increasing, having accurate ways to vertically extrapolate wind speed is essential to obtain a precise characterization of the wind resource for wind energy production. Recently, machine learning has been proposed and applied to extrapolate wind speed to hub heights. However, previous studies trained and tested the machine learning methods at the same site, giving them an unfair advantage over the conventional extrapolation techniques, which are instead more universal. Here, we use data from four sites in Oklahoma to test a round-robin validation approach for machine learning, under which we train a random forest at a site, and test it at a different site, where the model has no prior knowledge of the wind resource. We quantify how the accuracy of this technique varies with distance from the training site, and we find that it outperforms conventional techniques for wind extrapolation at all the considered spatial separations. We then assess how the accuracy of the machine-learning based approach varies when it is used to predict wind speed in a wind farm far wake. Finally, we explore as case study the performance of the random forest in extrapolating winds during a low-level jet event.
Large-eddy simulations of the Northeastern US coastal marine boundary layer
Authors: Cheung Lawrence C. , Kaul Colleen M. , Hsieh Alan S. , Blaylock Myra L. , Churchfield Matthew J.
Published: September 2020

In this study, large eddy simulations (LES) of offshore boundary layers near the Nantucket coast are performed using Nalu-Wind. The marine boundary layer conditions are chosen to match the predominantly unstable and neutral conditions measured by the Cape Wind platform. The appropriate domain, resolution, and boundary condition settings required for the LES are established through this work. Differences between stable and unstable cases are found in the wind speed profiles, averaged statistics, and wind spectra, and explained in terms of stratification effects.

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2020-5996C.
Characterization of the wake behind a horizontal-axis wind turbine (HAWT) at very high Reynolds numbers
Authors: Pique Alexander , Miller Mark A. , Hultmark Marcus
Published: September 2020

The wake of a three-bladed horizontal axis wind turbine was studied at aerodynamic conditions similar to what is experienced by commercially available turbines. Field relevant Reynolds numbers and tip speed ratios were obtained through the use of a high-pressure wind tunnel, at relatively low velocities. Measurements of the streamwise velocity were acquired through the use of the novel nano-scale thermal anemometry probe (NSTAP), which yields very high spatial and temporal resolution, enabling unattenuated turbulence measurements. Profiles of the mean velocity and turbulent fluctuations are presented, as they demonstrate important features of the wake development, such as wake recovery and tip vortex evolution. One dimensional energy spectra are also presented to provide details on the dominant flow features present in the wake. Reynolds number invariance is shown for mean velocity deficit and streamwise variance profiles for all downstream positions presented. Downstream evolution of streamwise variance profiles provides insight to the dynamic interactions between the tip and root vortex, such as their eventual coalescence. Spectral analysis show that the near wake flow-structures are dominated by the tip vortex, but that other larger structures are present as well, which may be related to the wake meandering phenomenon.
Three-dimensional wind-turbine wake characterization via tomographic particle-image velocimetry
Authors: Dar Arslan Salim , Porte-Agel Fernando
Published: September 2020

Wind turbines are often sited on different topographical features. In the current work, we performed wind-tunnel measurements of the wake behind a single wind turbine sited on two escarpments differing in the windward side shape using tomographic particle-image velocimetry. The escarpments are classified as forward facing step (FFS) and ramp-shape. The turbine sited on the FFS experiences an inflow with high flow shear and turbulence due to flow separation from the escarpment leading edge compared to the one on the ramp-shaped escarpment. As a consequence, the wake characteristics behind the turbine are strongly affected by the shape of the topography. The velocity deficit in the wake of the turbine is relatively higher in the forward facing step shape, but it also shows a faster recovery. The rotation of the wake is stronger for the turbine on the ramp-shaped escarpment, whereas the meandering of the wake is higher for the FFS case. The spatial coherence is observed to be higher in the near wake of the turbine sited on the FFS escarpment, while it is very similar in the far wake for both cases. Instantaneous vortices identified by the Q-criterion show that the development of tip and hub vortices is affected by the topography as well.
Data assimilation for the prediction of wake trajectories within wind farms
Authors: Lejeune M , Moens M , Coquelet M , Coudou N , Chatelain P
Published: September 2020

In this paper, we formulate a physics-based surrogate wake model in the framework of online wind farm control. A flow sensing module is coupled with a wake model in order to predict the behavior of the wake downstream of a wind turbine based on its loads, wind probe data and operating settings. Information about the incoming flow is recovered using flow sensing techniques and then fed to the wake model, which reconstructs the wake based on this limited set of information. Special focus is laid on limiting the number of input parameters while keeping the computational cost low in order to facilitate the tuning procedure. Once calibrated, comparison with high-fidelity numerical results retrieved from Large Eddy Simulation (LES) of a wind farm confirms the good potential of the approach for online wake prediction within farms. The two approaches are further compared in terms of their wake center and time-averaged speed deficit predictions demonstrating good agreement in the process.
Assessment of weak compressibility in actuator line simulations of wind turbine wakes
Authors: Asmuth Henrik , Janßen Christian F. , Olivares-Espinosa Hugo , Nilsson Karl , Ivanell Stefan
Published: September 2020

The trend of increasing rotor diameters and tip-speeds has brought about concerns of non-negligible compressibility effects in wind turbine aerodynamics. The investigation of such effects on wakes is particularly difficult when using actuator line models (ALM). This is because crucial regions of the flow, i.e. the direct vicinity of the blade, are not simulated but represented by body forces. To separately assess the impact of compressibility on the wake and the ALM itself, we conduct large-eddy simulations (LES) where the forces of the ALM are prescribed and based on the local sampled velocity (standard procedure), respectively. The LES are based on the weakly-compressible Lattice Boltzmann Method (LBM). Further to the comparison of (near-)incompressible to compressible simulations we investigate cases with artificially increased compressibility. This is commonly done in weakly-compressible approaches to reduce the computational demand. The investigation with prescribed forces shows that compressibility effects in the wake flow are negligible. Small differences in the wake velocity (of max. 1%) are found to be related to local compressibility effects in the direct vicinity of the ALM. Most significantly, compressibility is found to affect the sampled velocity and thereby accuracy of the ALM.
Experimental analysis of time delays in wind turbine wake interactions
Authors: Macrì S , Duc T , Leroy A , Girard N , Aubrun S
Published: September 2020

Wind farm control is a current hot topic that deals with the capacity to improve the overall wind power production of a farm by controlling individual wind turbines in order to mitigate their wake effects. The dynamic properties of these different strategies need to be taken into account in order to improve wind farm control models. In this work a post-processing of SCADA data acquired with a high sampling frequency on two neighboring wind turbines is performed through inter-correlation functions in order to assess the time delays between the wind turbine responses depending on wind direction and wind speed.
Comparison of different machine learning algorithms for prediction of wind evolution
Authors: Chen Yiyin , Wen Cheng Po
Published: September 2020

Wind evolution, i.e. the evolution of turbulence structures over time, has become an increasingly interesting topic in recent years. Part of this increasing interest is resulted from the development of lidar-assisted wind turbine control, which requires accurate prediction of wind evolution to avoid unnecessary or even harmful control actions. Moreover, study of wind evolution can deepen our understanding of turbulence characteristics and, for example, could make 4D stochastic wind field simulations possible by integrating wind evolution into 3D simulations. This study compares different machine learning algorithms for the prediction of wind evolution, including three variants of Gaussian process regression, regression tree, support vector machine regression, and shallow neural network. The comparison is done using lidar data measured by a nacelle-mounted lidar, and it focuses on the prediction accuracy and the computational time of models, to provide some insights of the trade-off between these factors. In terms of computational time, both the training time of the final model and the time for hyperparameter optimization are taken into account. Moreover, up-scaling of the computational time with data size is also investigated. It is found that Gaussian process regression provides high prediction accuracy but needs long computational time, increasing significantly with data size. For cases where long computational time might be a critical problem, shallow neural network could be a good alternative thanks to its high training efficiency, although its prediction accuracy is lower than Gaussian process regression. The other methods have no advantages in wind evolution prediction compared to these two methods.
Validation of FAST.Farm Against Full-Scale Turbine SCADA Data for a Small Wind Farm
Authors: Shaler K. , Debnath M. , Jonkman J.
Published: September 2020

FAST.Farm is a new midfidelity engineering tool developed by the National Renewable Energy Laboratory targeted at accurately and efficiently predicting wind turbine power production and structural loading in wind farm settings, including wake interactions between turbines. FAST.Farm is based on some of the principles of the Dynamic Wake Meandering model—including passive tracer modeling of wake meandering—but addresses many of the limitations of previous Dynamic Wake Meandering (DWM) implementations. Previous FAST.Farm verification studies show the similarities and differences between FAST.Farm and large-eddy simulations for rigid and flexible turbines. In this validation study, FAST.Farm turbine responses are compared to multiturbine measurements from a subset of a full-scale wind farm. FAST.Farm predictions of turbine generator power, rotor speed, and blade pitch for five-turbine simulations are compared to supervisory control and data acquisition results. Results reveal that FAST.Farm generator power mean and standard deviation results reasonably match measured data for upstream and downstream turbines, as well as the mean rotor speed and blade pitch above rated wind speeds. However, FAST.Farm generally underpredicts the mean rotor speed and overpredicts the mean blade pitch below rated operation. These errors are likely related to inaccuracies in the generic controller simulated. Despite controller differences, FAST.Farm predicts the same overall relative rotor power trends for all waked turbines at all wind speeds.
Actuator grid method for turbulence generation applied to yawed wind turbines
Authors: Houtin–Mongrolle F. , Benard P. , Moureau V. , Lartigue G. , Bricteux L. , Reveillon J.
Published: September 2020

The aerodynamics of yawed wind turbine wakes remains a major investigation topic, especially for the use of yaw angle in control strategies. Large-Eddy Simulations are employed here to study the influence of yaw and inflow conditions on the prediction of the wind turbine wake structure. A single wind turbine setup with different yaw angles and three different inflow conditions is investigated and discussed with respect to experimental data. The wind turbine blades are modeled using the actuator line method (ALM) while tower and nacelle are represented with a body-fitted unstructured mesh. The high levels of upstream turbulence, experimentally generated by turbulence grids, are emulated here with oscillating ALM. Such approach demonstrates to be highly predictive on the turbulent flow characteristics compared to the emptied wind tunnel experimental data. Results with turbine show good agreement to the experiment data with only a slight overestimation on the magnitude of the wake deflection due to yaw. When compared to a deflection model, the confinement of the wind tunnel is highlighted. The radial and azimuthal time-averaged angle of attack exhibits a high probability of dynamic stall near the hub for a yawed turbine. These results show large discrepancies on the blade loading, highlighting the need for improved and specific models.