The Science of Making Torque from Wind 2022 (TORQUE 2022)

Wind energy continues to make great strides in its contribution to the net CO2-zero targets of countries around the world. Both wind farms onshore and offshore are being built, but scientific challenges lie ahead if their generation is to be both reliable and economic. These challenges relate to better understanding the characteristics of the wind, how the wind inflow translates to loads and performance, and how best to build and operate the wind farms of the future so that their output can best be integrated into a 21st century energy system. Europe continues to be a hub for scientific research in wind energy and the European Academy of Wind Energy (EAWE) was created to bring together the top research institutes active in wind energy to cooperate, share knowledge and promote scientific excellence. As part of this remit, the conference, The Science of Making Torque from Wind (or TORQUE, for short) was inaugurated in 2004 in the beautiful city of Delft. The conference has gone from strength to strength and is probably the largest scientific conference devoted to wind energy in the world. History came full circle and the eighth edition, TORQUE 2020 was due to be held in Delft. Unfortunately, the global pandemic meant that this conference had to be held online, but the TU Delft Wind Energy Institute was given a further opportunity to host the ninth edition, TORQUE 2022, in person.Following the call for three-page abstracts, 435 submissions were made and, after a two-stage peer review process by over 100 reviewers, 300 full papers were accepted for publication in the proceedings. The conference consisted of three plenary sessions, 28 parallel oral sessions and two poster sessions. Oral presenters had 15 minutes to present their work followed by 5 minutes of questions. All poster presenters were allowed a recorded one-minute pitch which could be accessed in advance of the live 90-minute poster sessions.Delft University Wind energy research instituteWind Energ

The Science of Making Torque from Wind 2020 (TORQUE 2020)

Wind Energ

Modelling the impact of trapped lee waves on offshore wind farm power output

Mesoscale meteorological phenomena, including atmospheric gravity waves (AGWs) and including trapped lee waves (TLWs), can result from flow over topography or coastal transition in the presence of stable atmospheric stratification, particularly with strong capping inversions. Satellite images show that topographically forced TLWs frequently occur around near-coastal offshore wind farms. Yet current understanding of how they interact with individual turbines and whole farm energy output is limited. This parametric study investigates the potential impact of TLWs on a UK near-coastal offshore wind farm, Westermost Rough (WMR), resulting from westerly-southwesterly flow over topography in the southeast of England. Computational fluid dynamics (CFD) modelling (using Ansys CFX) of TLW situations based on real atmospheric conditions at WMR was used to better understand turbine level and whole wind farm performance in this parametric study based on real inflow conditions. These simulations indicated that TLWs have the potential to significantly alter the wind speeds experienced by and the resultant power output of individual turbines and the whole wind farm. The location of the wind farm in the TLW wave cycle was an important factor in determining the magnitude of TLW impacts, given the expected wavelength of the TLW. Where the TLW trough was coincident with the wind farm, the turbine wind speeds and power outputs were more substantially reduced compared with when the TLW peak was coincident with the location of the wind farm. These reductions were mediated by turbine wind speeds and wake losses being superimposed on the TLW. However, the same initial flow conditions interacting with topography under different atmospheric stability settings produce differing near-wind-farm flow. Factors influencing the flow within the wind farm under the different stability conditions include differing, hill and coastal transition recovery, wind farm blockage effects, and wake recovery. Determining how much of the differences in wind speed and power output in the wind farm resulted from the TLW is an area for future development. Wind Energ

Atmospheric gravity wave impacts on an offshore wind farm

Atmospheric Gravity Waves (AGWs) frequently occur around near coastal offshore wind farms. Yet our understanding of how they interact with individual turbines and whole farm energy output is limited. This research uses computational fluid dynamics modelling to investigate the impact of near coastal, topographically forced AGWs on offshore wind farm power output in a theoretical wind farm. Preliminary results show the farm contained within one wavelength (4.9km) of the topographically forced AGW. The AGW causes a substantial variation in wind speed across the farm with a subsequent 76% variation in power output compared to 29% in the control case. Wind Energ

Wind turbine blade trailing edge crack detection based on airfoil aerodynamic noise: An experimental study

In recent years, with the development of the wind power industry and the increase in the number of wind turbines, the condition monitoring of blades and the detection of damage are increasingly important. In this work, a new non-contact damage-detection approach is experimentally investigated based on the measurement of airfoil aerodynamic noise. A NACA 0018 airfoil with chord of 200 mm with different trailing edge crack sizes, 0.2, 0.5, 1.0 and 2.0 mm, is investigated. Experiments are conducted at different mean flow velocities, inflow turbulence intensities and angles of attack. Far-field noise scattered from the airfoil is measured by means of a microphone array. The spectral differences of sound pressure level between the damaged cases and the baseline (without any damage) are compared. As expected, at small angles of attack, with clean or low turbulence intensities (e.g. ∼ 4% in the experiment) flow, by increasing the size of the crack, tonal noise appears at trailing-edge thickness-based Strouhal number,Sth , approximatively equal to 0.1. However, at higher angles of attack (e.g. ± 10° and ± 15°) or under conditions of high turbulence intensity (e.g. ∼ 7%), the amplitude of the tonal peak diminishes suggesting that complementary measurements or longer acquisition time to remove inflow turbulence effects are needed to monitor trailing edge cracks.Wind Energ

New indicator for damage localization in a thick adhesive joint of a composite material used in a wind turbine blade

In this paper, a new indicator to localize fatigue damage in a fibre glass composite structure, i.e. spar cap to shear web thick adhesive joint of a wind turbine blade, is presented. This indicator is based on the effect of damping on the phase of the mode shapes of the structure. When fatigue damage occurs, damping increases in the defective area and this leads to an increase in the local energy dissipation. This non-uniformity in the energy dissipation throughout the structure causes the structure to vibrate with mode shapes whose structural elements no longer have the same phase creating complex mode shapes. A visco-elastic finite element (FE) vibration model is developed for a thick adhesive joint of a wind turbine blade. The mass, stiffness, and damping matrix extracted from the FE model are used to determine the complex mode shapes. The results show that the damaged area is located where the spatial derivative of the phase of the components of the mode shapes is minimum. Changes in the phase of mode shapes of the structural elements are strongly dependent on the location of damage. In the locations where the strain modal energy is greater, the change in the phase is also higher.Wind EnergyStructural Integrity & Composite

Associating Synoptic-Scale Weather Patterns with Aggregated Offshore Wind Power Production and Ramps

Large-scale weather patterns and their variability can influence both the amount of wind power production and its temporal variation, i.e., wind power ramps. In this study, we use a self-organizing map to cluster hourly sea level pressure into a discrete number of weather patterns. The dependency of wind power production and wind power ramps on these weather patterns is studied for the Belgian offshore wind farm fleet. A newly developed wavelet-surrogate ramp-detection algorithm is used for the identification of wind power ramps. It was observed that low-pressure systems, southwesterly and northeasterly wind flows are often associated with high levels of wind power production. Regarding wind power ramps, the type of transition between weather patterns was shown to determine whether ramp up or ramp down events would occur. Ramp up events tend to occur due to the transition from a high-pressure to a low-pressure system, or the weakening of the intensity of a deep low-pressure system. The reverse is associated with ramp down events.Wind EnergyAtmospheric Remote Sensin

Quantifying the impacts of synoptic weather patterns on North Sea wind power production and ramp events under a changing climate

Only a few studies on the overall impact of climate change on offshore wind power production and wind power ramps in the North Sea region have been published. This study focuses on the characteristics of expected wind power production and wind power ramps in the future climate aided by the classification of circulations patterns using a self-organizing map (SOM). A SOM is used to cluster high-resolution CMIP5-CORDEX sea level pressure data into 30 European area weather patterns. These patterns are used to better understand wind power production trends and any potential changes. An increased frequency of occurrence and extended persistence of high pressure systems lasting at least 24 h is projected in the future. Whereas a contrasting reducing tendency for low-pressure systems is estimated. No significant evidence is seen for a change in wind power capacity factor over the North Sea, though tentative evidence is seen for a reduction in wind power ramps. Annual energy production is seen to be dominated by a small number of weather patterns with westerly, south-westerly or north-westerly winds. Future wind power production is projected to become less from westerly winds and more from south-westerly and north-westerly flows. Ramp up events are primarily associated with strong south-westerly winds or weather patterns with a weak pressure gradient. Ramp down events have a stronger association with more north-westerly flow. In a future climate, a reduction in ramp up events associated with weak pressure gradients is projected.Wind EnergyAtmospheric Remote Sensin

The impact of weather patterns on offshore wind power production

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. Wind EnergyAtmospheric Remote Sensin

An experimental study on trailing edge crack detection for wind turbine blade using airfoil aerodynamic noise

Recent decades have witnessed more and more wind turbines (WTs) being installed onshore and offshore. Health condition monitoring for WTs structures and components is increasingly becoming a compelling concern for stable power output and operational safety of a wind farm [1]. Blade damages seem to occur with a higher probability ahead of other components (e.g., gearbox and generator) damages [2]. After reviewing traditional damage detection approaches and their limitations [3], in this research a new non-contactable approach to detecting trailing edge (TE) damages is proposed based on airfoil aerodynamic noise measurements using a microphone array. In the experiment, four changeable TE parts with rectangular cracks (damaged width W of 0.2mm, 0.5mm, 1.0mm and 2.0mm) for a NACA0018 airfoil (chord C=200mm, span L=400mm) are designed and an example with W=0.2mm is shown in Fig.(a). The TEs with cracks have the same solid thickness as the baseline one (h_solid=0.76mm, standard NACA0018 airfoil TE thickness with chord of 200mm) but different dimensions of total TE thickness (h=W+h_solid). A phased microphone array with 64 microphones is used for acoustic measurement then beamforming is applied to extract TE noise and source power integration is performed within a 200×200mm2 region centred at TE midpoint [4][5]. Fig.(b) shows sound pressure levels (SPLs) L_p at the integrated region of four damaged cases as well as baseline with the frequency resolution of 10Hz under the freestream velocity U of 35m/s and geometrical angle of attack (AoA) alpha of 0º. The cases with smaller cracks show less remarkable tonal peaks compared with the one of W=2.0mm (~4dB); when the crack size is smaller the spectral peak broadens. These peaks or humps are attributed to the periodic vortex shedding from blunt TEs. Fig.(c) shows the SPL differences Delta L_p between the damaged cases and baseline; frequency is normalized as TE-thickness-based Strouhal number St. Local maxima of Lp are present at approximately St = 0.1 [6]. In the experiment, it is difficult to extract the spectral peaks or humps if the effective AoA (alpha*) [6] is more than 2.40º because the boundary layer on suction side becomes thicker and the asymmetry of boundary layers prevents coherent and periodic vortex shedding [7]. In Fig.(d), the discrete points are the St at peak L_p (St_peak) versus the ratio of TE thickness and averaged displacement thickness of pressure and suction sides (overline delta *) extracted from available cases (U=15m/s, 20m/s, 25m/s, 30m/s and 35m/s); the grey and blue curves are obtained from models reported in [6] with solid angle (Psi) of 20º and 23.76º (baseline solid angle), respectively. The points of St_peak versus thickness ratio show a good agreement with the prediction model [6]. This means that particularly for smaller cracks at the first stage of damaged process, the effect of solid angle can be neglected and considered as a minor and adjunctive factor. The TE thickness retrieved through the application of the model can be used as a prediction of the damage level. Additional data obtained from experiments with turbulent inflow will be presented to assess if the approach proposed is still feasible in more realistic turbulent inflow conditions. Keywords: wind turbine blade; trailing edge crack; damage detection; aerodynamic noise. Images: Link: https://s3-eu-west-1.amazonaws.com/static.vcongress.de/cms/forwind/paper/417dd783-7a7c-424d-a4d3- 55ce31fa41e1.png Description: (a) An example of NACA0018 airfoil with a TE crack of 0.2mm. (b) SPLs with resolution of 10Hz (U=35m/s and alpha=0º). (c) Corresponding SPL differences compared with baseline case normalized as peak St. (d) Relations of peak St and thickness ratio: discrete points are the experimental date; grey and black curves are prediction models Brooks et al. proposed with solid angle of 20º and 23.76º. References: [1] Tautz-Weinert, J. and Watson, S.J., 2016. Using SCADA data for wind turbine condition monitoring–a review. IET Renewable Power Generation, 11(4), pp.382-394. [2] Yang, W., Peng, Z., Wei, K. and Tian, W., 2016. Structural health monitoring of composite wind turbine blades: challenges, issues and potential solutions. IET Renewable Power Generation, 11(4), pp.411-416. [3] Du, Y., Zhou, S., Jing, X., Peng, Y., Wu, H. and Kwok, N., 2020. Damage detection techniques for wind turbine blades: A review. Mechanical Systems and Signal Processing, 141, p.106445. [4] Merino-Martínez, R., Carpio, A.R., Pereira, L.T.L., van Herk, S., Avallone, F., Ragni, D. and Kotsonis, M., 2020. Aeroacoustic design and characterization of the 3D-printed, open-jet, anechoic wind tunnel of Delft University of Technology. Applied Acoustics, 170, p.107504. [5] Carpio, A.R., Avallone, F., Ragni, D., Snellen, M. and van der Zwaag, S., 2020. Quantitative criteria to design optimal permeable trailing edges for noise abatement. Journal of Sound and Vibration, 485, p.115596. [6] Brooks, T.F., Pope, D.S. and Marcolini, M.A., 1989. Airfoil self-noise and prediction. [7] Moreau, D.J. and Doolan, C.J., 2016. Tonal noise production from a wall-mounted finite airfoil. Journal of Sound and Vibration, 363, pp.199-224.Wind Energ