bluuebunny/crossref_metadata_2025 huggingface dataset:
Velocity-field based load estimation of an unsteady actuator disc
Authors: Yu Wei , Ferreira Carlos Simao
Published: June 2024

Traditional methods for determining the load of an object in unsteady cases, such as Control-volume Momentum Integration (CMI) and Noca methods, encounter challenges related to near-body acceleration and pressure estimation. This prompts the need for innovative techniques to overcome these limitations. This study introduces a novel vorticity-based approach to expand classical load determination methods. The numerical results of an unsteady actuator disc (AD) CFD simulation are used to verify and quantify the uncertainty of the three methods. In the AD model, the load is prescribed and used as a source term. The velocity and pressure fields are solved from the Navier-Stokes equations using the open-source CFD package OpenFOAM, which offers a robust validation framework. Systematic examination of the robustness and accuracy of the three methods across various load and motion unsteady scenarios reveals that the proposed vorticity-based method excels in steady-state scenarios, exhibiting the highest level of robustness and accuracy. In contrast, the traditional CMI method proves more robust and accurate in pure motion cases. In scenarios involving static and moving AD with load variations, the new vorticity-based method demonstrates superior robustness and accuracy, mainly when moderate vorticity dynamics. Conversely, in cases with increased vorticity dynamics in the wake, the accuracy of the vorticity-based method decreases, with the CMI method showing superiority.
Dynamics of the virtual center of wind pressure: An approach for the estimation of wind turbine loads
Authors: Moreno Daniela , Schubert Carsten , Friedrich Jan , Wächter Matthias , Schwarte Jörg , Pokriefke Gritt , Radons Günter , Peinke Joachim
Published: June 2024

A new stochastic method for the reconstruction of time series of bending moments at the main shaft of a wind turbine is presented. The method is based on the characterization of the dynamics of the virtual center of wind pressure (CoWP). The CoWP, calculated purely from the incoming wind field, provides an approach for correlating the bending moments at the shaft with large-scale turbulent structures of the wind acting on the rotor plane. The proposed method allows a fast procedure for generating time series of loads on the shaft. As a result, the computational and time requirements for maximum and fatigue load assessment could be reduced.
A semi-empirical model for time-domain tower Vortex induced Vibration load simulations of wind turbines
Authors: Arnold M , Filopoulos S , White W , Kamruzzaman M
Published: June 2024

A new method for simulating aeroelastic resonances between vortex shedding and structural eigenfrequencies of a wind turbine tower is presented in this publication. This aero-elastic effect of Vortex induced Vibrations (ViV) has the potential to disrupt installation processes and cause fatigue and extreme loads on the tower. Despite this issue, there are no established simulation methods available in literature, able and sufficiently efficient to predict the ViV in turbulent and site specific design load conditions. This state-of-the-art is extended by introducing an efficient semi-empirical, time-domain simulation method, which is capable of analyzing the tower ViV excitations and aeroelastic responses in wind turbine load simulations of the isolated tower or the full turbine for fatigue and extreme loads. The method is based on an adaptive harmonic equation, which is automatically tuned to the instantaneous tower motions.
Airfoil Icing Prediction with Improved Roughness Model
Authors: Özgen Serkan , Sarıbel Eda Bahar
Published: June 2024

Wind turbines are usually exposed to harsh environmental conditions, resulting in the icing of their structures. The production capability of iced wind turbines drops significantly compared to clean turbines. Understanding how ice build up is the first step in coping with its adverse effects. Analyzing the performance reduction and ice shapes on site can be challenging due to practical difficulties. Numerical analysis of iced blade sections combined with Blade Element Momentum Method can simulate the effects of exposure of wind turbines to icing weather. This paper aims to implement an improved ice accretion model for blade sections of wind turbines. The chosen analytical model is designed to compute roughness due to ice locally and employs three water state models due to icing. Roughness height characterizes the boundary layer development and alters the heat transfer coefficient distribution. The mass balance of the Extended Messinger model that is used for ice accretion prediction is improved by including the remaining water mass on the ice surface. The result of the icing simulation of NACA0012 in wet and dry regimes matches the experimental results well.
A CFD Analysis of Oscillating Airfoil with Leading Edge Roughness: Comparing Correlations for Equivalent Sand Grain Roughness
Authors: Min Seungin , Kim Taeseong
Published: June 2024

Numerical simulations express surface roughness as equivalent sand grain roughness values, so the correlation is required to convert realistic roughness into equivalent sand grain roughness values. The correlations were designed to match the wall velocity distributions for static cases with roughness, and they accurately predicted roughness effects when applied to URANS simulations. Several studies have examined the roughness effect on dynamic pitching airfoils. Still, they have only considered the presence of roughness, neglecting the process of converting the actual roughness to equivalent sand-grain roughness. Thus, in the present study, we apply a static case-based equivalent sand-grain roughness correlation to dynamic pitching analysis to validate the suitability of each correlation and verify the significance of correlation parameters. It was observed from a comparison study between numerical aerodynamic coefficients and experimental data from Ohio State University that physical parameters such as skewness and roughness height were important parameters to predict the dynamic stall behaviour more accurately. It was also observed that dynamic stall prediction accuracy is affected by the frequency and type of airfoil, and through this, it was confirmed that there are additional factors to consider when using an equivalent sand grain roughness correlation on pitching airfoils.
Experimental comparison of a NACA0021 airfoil in large plunging and surging motions at 90
◦
angle of attack
Authors: Xu Guanqun , Yu Wei , Ferreira Carlos , Sciacchitano Andrea , Iyer Sowmya
Published: June 2024

The topic of vortex-induced vibrations on a wind turbine blade has recently gained much attention due to its growing size and flexibility. To address this concern, a wind tunnel test was conducted to study the forced plunging and surging motion of a NACA0021 airfoil at 90° angle of attack. Results indicate that vortex lock-in occurred for a motion amplitude of one chord length even for a small frequency ratio (between motion frequency and static Strouhal frequency) of 0.39. Analysis of the drag coefficient, derived from the phase-averaged Particle Image Velocimetry (PIV) data, shows that a plunging airfoil experiences higher average loading than a surging airfoil, which is deemed to be more harmful considering the higher loading in the crossflow-direction due to the variation of effective angle of attack.
Unbounded Domain Modeling in Axisymmetric Rotor Wake Analysis
Authors: Lokken Thomas , Warncke Norbert , de Tavernier Delphine
Published: June 2024

Mitigating the effects of wind turbine wakes is a central part of wind farm design. This paper proposes a spectral solver for the axisymmetrical Ainslie wake model based on modified Laguerre basis functions over the semi-infinite radial domain and a marching scheme in the downstream direction. This orthogonal basis promises fast convergence and a low number of DOFs for discretizing the continuity and axial momentum equation, promising a computationally efficient method. The numerical implementation of the model could not be finished in time; preliminary results are presented but still show non-negligible conservation errors. The focus of this work lies, therefore, on a detailed derivation of the method and a discussion of the sources of numerical errors in the nonlinear terms, and due to the truncation of the spectral basis, a comparison of the solver outputs to other methods remains part of the ongoing work.
Aeroelastic simulations of the DTU 10 MW turbine using tight coupling integration techniques
Authors: Ntrelia Konstantina , Vandewalle Stefan , Meyers Johan
Published: June 2024

The present study aims to investigate a newly developed multirate time integration technique on aeroelastic simulations of the DTU 10 MW reference wind turbine inside a turbulent atmospheric boundary layer. The turbine is modelled using an actuator line model and a multibody structural solver is employed for the dynamic response. The turbine is studied under cases of laminar flow and a pressure driven boundary layer. Results show that the scheme exhibits high accuracy and matches the theoretical order of the Runge–Kutta scheme. During unsteady operations, substantial deformations were observed that are influenced mainly by the turbine’s rotation and the effect of turbulence in fatigue loading is highlighted.
Impact of rotor blade aerodynamics on tower vortex induced vibration of modern wind turbines
Authors: Ludlam David Vicente , Jacobs Pim , Ahmed Aqeel
Published: June 2024

Modern wind turbines in standstill or idling could experience vortex induced vibrations (VIV); the origin of these vibrations is either shedding from the wind turbine blade referred to as blade VIV or shedding from tower termed as tower (or turbine) VIV. When the whole structure of the wind turbine is considered and the blades are pitched out, the dominant 1st order mode for blade deformation in edgewise direction leads to negligible motion of the tower top, while when the whole turbine vibrates with first tower mode, blades also undergo significant periodic translations and deformations. In this study, forced motion is used to study the impact of aerodynamic damping due to rotor moving with 1st tower mode. In the literature no comprehensive work is available to characterize the impact of blades aerodynamics in the turbine mode either using systematic tests or high-fidelity computational fluid dynamics (CFD). In this article high-fidelity numerical simulations are performed to compute the power injections from the rotor blades when the turbine moves in 1st tower mode. Depending on the inflow angle and the azimuthal position, blades can inject significant power. Thus, the estimated damping from tower-only empirical models could severely underestimate the total aerodynamic power if the power injection from the rotor is neglected.
Investigating 3-D Flow Characteristics of Wind Turbine Airfoils using Delayed Detached Eddy Simulations at High Reynolds Numbers
Authors: Akcengiz Ezgi Orbay , Uzol Nilay Sezer
Published: June 2024

This numerical study investigates the 3-D flow field and aerodynamic characteristics of DU 00-W-212 wind turbine airfoil at high Reynolds numbers. The Computational Fluid Dynamics (CFD) simulations are performed at Reynolds number of 3 million at three different angles of attack for the pre-stall, stall, and post-stall conditions, by using an open source CFD solver SU2. The Delayed Detached Eddy Simulations (DDES) with the Spalart-Allmaras (SA) turbulence model and Langtry-Menter (LM) transition model are performed to address the challenge of predicting unsteady flow characteristics with transition, particularly on the suction side of the airfoil. The 3-D DDES with SA results with and without LM transition model are compared with the 2-D RANS with SA simulations and available experimental data.
Impact of rotor size on the aeroelastic behavior of large turbines: a LES study using flexible actuator lines
Authors: Trigaux François , Chatelain Philippe , Winckelmans Grégoire
Published: June 2024

This paper investigates the impact of rotor size on the structural displacements and loads of large wind turbines during power production. The actuator line method is used in Large Eddy Simulations and is coupled to a structural solver for the blades. The latter consists either of a linear solver based on the Euler-Bernoulli beam theory, or uses BeamDyn to account for the non-linearities. The effects of upscaling are investigated for three reference wind turbines of various sizes: the NREL-5 MW, the DTU-10 MW and the IEA-15 MW. The study reveals that the larger turbines exhibit higher bending relative to the radius and a significant torsion angle. The torsion angle is primarily linked to the structural non-linearities and substantially affects the mean blade loads of the largest turbines. Consequently, the power and thrust coefficients predicted using the linear structural model differ from those obtained using BeamDyn. However, the variations of the root bending moments are predicted similarly using both structural solvers; also suggesting that a linear structural solver is still sufficient for the fatigue analysis. Finally, the fatigue analysis is extended to the shaft loads due to the entire rotor, and empirical scaling trends are derived.
Determination of annual energy production loss due to erosion on wind turbine blades
Authors: Özçakmak Özge Sinem , Bretos David , Méndez Beatriz , Bak Christian
Published: June 2024

Increasing size of the modern wind turbines amplifies the issues of leading-edge erosion, especially on the outboard sections of the blades, impacting both their structural integrity and aerodynamic efficiency. Predicting and detection of the aerodynamic losses which occurs before a noticeable structural degradation on the blade can be crucial for operational predictive maintenance strategies to avoid significant loss production. This paper presents the results from the collaborative study between DTU and CENER in order to investigate the influence of leading-edge erosion on wind turbine aerodynamic performance. For this purpose, three distinct erosion scenarios are analyzed by means of computational fluid dynamics (CFD), both 2D and 3D, blade-element momentum theory (BEM) based solver (OpenFAST) and a Simplified Aerodynamic Loss Tool (SALT). The results from previous studies are used as an input for these tools, with outputs from each tool complementing and reinforcing one another. Furthermore, annual energy production (AEP) reductions due to leading-edge erosion across these tools are compared and validation of the SALT tool is presented. It is observed that the thrust and power losses from both CFD and OpenFAST exhibit comparable results and for a severe erosion case, spanning the last third of the blade, results in a 4.3 % reduction in the annual energy production.
A correction model for the effect of spanwise flow on the viscous force contribution in BEM and Lifting Line methods
Authors: Gaunaa Mac , Sørensen Niels N. , Li Ang
Published: June 2024

Design optimization and aeroelastic load evaluation for wind turbines are still infeasible for CFD due to computational cost. These tasks are carried out using 3D engineering aerodynamic methods, where the local aerodynamic loads are obtained from tabulated 2D aerodynamic polars, which makes the models fast. With recent developments such as highly flexible blades, coned/prebent/swept blades, the relative inflow direction to the “inner” 2D airfoil section systems can have a significant component in the spanwise direction. The Crossflow Principle (CP) is used to treat the effects of this in a physically consistent manner. Cases dominated by pressure forces are described well with the CP method, but it is shown in the paper that CP fails to describe the part of the forces stemming from the friction forces correctly. It is shown in the paper that the power loss due to friction forces will be underestimated with the crossflow principle for rotors with significantly swept blades or other designs with a significant amount of local crossflow on the blades. The present work presents a simple model to correct the baseline crossflow principle method to take into account also the friction force part in a consistent manner. The model is validated with 3D CFD results on a 2D airfoil section. It is shown that the new model successfully corrects for the addition of the viscous forces due to spanwise flow component. The paper includes examples of the effect of using the model on rotor designs with different amounts of blade sweep simulated using a blade element momentum (BEM) and blade element vortex cylinder (BEVC) methods.
Automatically generated state observers – toolchain and validation with real measurements
Authors: Geisler Jens
Published: June 2024

State estimation of wind turbines is the basis for many advanced control strategies and analysis applications such as condition monitoring, fault diagnosis, and much more. It depends on the application and its goals, which states of the real turbine are relevant. Therefore, estimators with different levels of detail and sets of states suitable for the problem at hand are needed. This paper describes a toolchain that generates custom-tailored code for an extended Kalman filter. The aim is to create computationally highly efficient estimators for a wide range of applications. Automatic generation of source code allows for agile experimentation and reduces the risk of time-consuming implementation errors. The new contributions are the selection and combination of all parts of the toolchain, the extension of the integration algorithm to include the Jacobian of the transition function, and the adaptation of an efficient covariance auto-tuning algorithm. Four different models are validated in a three-stage process, including measurement data from a real turbine.
Inter-turn Short Circuit Fault Diagnosis and Severity Estimation for Wind Turbine Generators
Authors: Yan Jingyi , Senemmar Soroush , Zhang Jie
Published: June 2024

While preventive maintenance is crucial in wind turbine operation, conventional condition monitoring systems face limitations in terms of cost and complexity when compared to innovative signal processing techniques and artificial intelligence. In this paper, a cascading deep learning framework is proposed for the monitoring of generator winding conditions, specifically to promptly detect and identify inter-turn short circuit faults and estimate their severity in real time. This framework encompasses the processing of high-resolution current signal samples, coupled with the extraction of current signal features in both time and frequency domains, achieved through discrete wavelet transform. By leveraging long short-term memory recurrent neural networks, our aim is to establish a cost-efficient and reliable condition monitoring system for wind turbine generators. Numeral experiments show an over 97% accuracy for fault diagnosis and severity estimation. More specifically, with the intrinsic feature provided by wavelet transform, the faults can be 100% identified by the diagnosis model.
Combined Individual Pitch and Flap Control for Load Reduction of Wind Turbines
Authors: Dittmer Antje , Osterwinter Bernhard , Ossmann Daniel
Published: June 2024

In this paper individual pitch control is combined with trailing-edge flap (TEF) control, both designed as multi-loop proportional-integral-derivative (PID) controllers, to significantly reduce blade damage equivalent loads. OpenFAST NREL 5MW aerodynamics are enhanced with dedicated aerodynamic polars of TEF blade elements. The NREL 5MW model, including the TEF extension, is incorporated into Simulink, and PID controller parameters are optimized in a closed-loop optimization setup. The DEL decrease is confirmed via an extensive simulation campaign using the non-linear wind turbine simulation environment.
A wind turbine digital shadow with tower and blade degrees of freedom - Preliminary results and comparison with a simple tower fore-aft model
Authors: Hoghooghi H , Bertelè M , Anand A , Bottasso C L
Published: June 2024

This paper analyzes the formulation of a wind turbine digital shadow using a Kalman filter to estimate tower loads. At first, a simple model is considered, which is limited to the sole fore-aft dynamics of the tower. Next, to quantify the potential benefits of a more refined approach, the tower side-side motion and the blade flapwise and edgewise degrees of freedom are added to the filter-internal model. For both the simple and refined formulations, the model coefficients are optionally scheduled as functions of the inflow conditions. Preliminary results, limited to non-waked and non-misaligned conditions, indicate that the refined formulation has some positive – but limited – effects on the quality of the tower fore-aft loading. Additionally, it is found that the scheduling of the coefficients does not further improve the results.
Wind pattern clustering of high frequent field measurements for dynamic wind farm flow control
Authors: Becker M , Allaerts D , Van Wingerden J W
Published: June 2024

In this work, we investigate a method to derive characteristic dynamic flow field behavior from field measurements. We further explore how these changes impact the performance of a wind farm flow control strategy. For a long time, hourly to 10-min averaged data has been the predominant form to store meteorological quantities such as wind speeds and wind directions. With the decreasing cost of digital storage and improvements in measurement technology, the assimilation of higher frequent data has become more feasible. We use one of these open-source datasets provided by the KNMI to explore what characteristic flow behavior is described in the high-frequency recordings of a Wind-LiDAR located in the North-Sea. To this end we employ a K-Means algorithm to cluster 10-min time series of wind direction changes sampled at 20 s. Our study finds that the majority of wind direction changes within this time window can be described by five main clusters with clock- and counterclockwise changes of the wind direction in the range of ±4 deg. Subsequently we investigate the implications for quasi-steady wind farm flow control. We employ look-up table yaw-steering control next to baseline control in selected cases in a turbulent Large Eddy Simulation to verify the predictions made by a dynamic parametric engineering wake model. We find good agreement between both simulation environments and use the engineering model to investigate all wind directions in 2 deg resolution. The results show that the identified wind direction changes can have a significant negative impact on the power generated by a 10 turbine wind farm. The study also shows that the fixed yaw-steering set-points are still favorable over baseline operation for wind direction changes in the range of ±1.6 deg, but can act detrimental for larger changes.
Data-driven wind turbine sensor health validation
Authors: Badarinath K , Hoebeke P , Schillebeeckx D , Yazicioglu H
Published: June 2024

This paper presents a data-driven approach for detecting anomalies in wind turbine sensors, specifically anemometers and wind vanes, and the development of a smart alerting system. The study focuses on utilizing SCADA and reanalysis (ERA5) data for accurate anomaly detection and reducing false alarms through smart change point detection algorithms. The methodology involves modeling normal behavior, detecting change points, and comparing power curves before and after these points. For anemometer anomaly detection, a three-year SCADA dataset from an offshore wind farm and a synthetic dataset is used, employing an XGBoost model and the PELT algorithm for change point detection. Wind vane anomalies are identified using a nine month dataset from seven turbines, with synthetic alterations to simulate misalignments. Results show successful detection of sudden changes in wind speed and direction, with smart alarms assisting operators in decision-making. This research enhances wind turbine condition monitoring, improving reliability and efficiency.
Wind turbine main shaft crack detection with SCADA generator speed measurement
Authors: Hougaard H. A. , Madsen M. B. , Pedersen A. S.
Published: June 2024

Preventing failure of structural components is a necessity for safe and economic operation of wind farms. This paper presents a novel detection method of wind turbine main shaft fractures based on data from the turbine SCADA system thus not needing retrofit sensors. The authors developed the crack detection method in the wake of a catastrophic failure on an offshore 3.6 MW wind turbine and applied it across multiple wind farms totalling more than a thousand turbines of the same type, minimising any further risk of failure. The novel method consists of tracking the amplitude of the 2P rotor harmonic in the generator speed and is found to outperform the most common metrics proposed in shaft crack detection literature: Rotor harmonics measured in fore-aft and side-side accelerations and estimates of the drivetrain torsional eigenfrequencies. The generator speed 2P amplitude of the cracked shaft turbine was significantly elevated 16 months before failure while all other benchmark metrics failed to detect the crack. The analysis showed that no other turbine in the fleet were exhibiting similar indications of main shaft cracks and indicated that any such failure would have a long lead time.
First experimental results on lifetime-aware wind farm control
Authors: Braunbehrens R , Anand A , Campagnolo F , Bottasso C L
Published: June 2024

The study presents the methodology, implementation, and first results of the experimental test of a lifetime-aware wind farm control (WFC) approach. The novel strategy goes beyond the conventional WFC formulations and aims to maximise profit while ensuring fulfilment of a desired lifetime. Damage due to fatigue is formulated using a cost model and is also limited by a lifetime constraint. The control strategy is based on yaw-induced wake steering and utilises a tool chain of power and damage estimators. The experiment was conducted with three model turbines in a boundary layer wind tunnel, which allowed the simulation of a realistic dynamic variation of the wind direction. The novel strategy is compared to conventional greedy operation, as well as to the classical maximum power strategy. The results show that the novel control strategy can improve the economic performance of the farm.
An advanced farm flow estimator for the real-time evaluation of the potential wind power of a down-regulated wind farm
Authors: Moens Maud , Lejeune Maxime , Chatelain Philippe
Published: June 2024

This work aims at verifying the predictions of OnWaRDS, an open-source wake modelling framework that captures the main features of the wake dynamics, including its meandering, in ancillary services scenarios. OnWaRDS brings together Lagrangian flow modeling and flow sensing and runs in parallel with a wind farm environment (here Large-Eddy simulations coupled to an Actuator Disk model (LES-AD)) in order to use the available rotor states to predict the flow field. The performances of OnWaRDS are first assessed when it runs synchronously with the LES-AD of a down-regulated wind farm and tends to mimic the LES-AD behavior. This synchronous mode implies a continuous feeding of the wake model with LES-AD rotor data. Then, OnWaRDS is used in a predictive mode, in order to predict an alternate reality for the wind farm. In this study, OnWaRDS aims at evaluating, in real-time, what the potential power production would be when the LES-AD is down-regulated to provide operating reserve capacity to the electricity network. Switching to a predictive mode implies that certain measurements at the wind turbine level can no longer be used, because the flow and the rotor behavior change between LES-AD and OnWaRDS. The second part of this study thus aims at verifying the predictions of OnWaRDS, and highlighting the impact of switching from a synchronous to a predictive mode in OnWaRDS.
Maximizing value through optimized annual selection of Pareto-optimal wind turbine operating strategies
Authors: Requate Niklas , Meyer Tobias , Hofmann René
Published: June 2024

Wind turbines as an investment aim at turning an initial expense into a profit. Naturally, the aim of developers and operators alike is to create an economic benefit that is as high as possible. Little changes to a wind turbine structure are possible once it is built, and wind as the ultimate power source cannot be influenced. The only available means to achieve a high economic benefit is through improved operations and maintenance. We developed a method for optimizing the operation of wind turbines that builds on condition-based adaptation of the power setpoint. It aims at balancing loads and power generation such that lifetime is increased, and the total economic value is improved over simpler operating schemes. In this contribution, we extend the method with an annually varying selection of different optimal operating strategies from an initial multiobjective optimization. We show three case studies that highlight the potential of annual variation and the margin with which it improves on operating at nominal power and over a fixed optimized operating strategy. In each case study, the net present value can be improved slightly over a lifetime-constant operating point that is selected once from the Pareto-front.
Assessing Closed-Loop Data-Driven Wind Farm Control Strategies within a Wind Tunnel
Authors: Hulsman P. , Howland M. , Göçmen T. , Petrović V.
Published: June 2024

This paper introduces a framework to assess a hybrid data-driven wake steering strategy combining the advantages of an analytical model for the initial data gathering together with a data-driven model for modelling error correction. The main building blocks of the control strategy (required input domain, data gathering and model generation) are evaluated within the wind tunnel, utilising a newly developed setup that can simulate dynamic wind direction variations and which was specifically designed to examine wake steering control strategies. The control strategy employs a machine-learning algorithm to generate a turbine and wake model based on the measurement data, allowing this approach to be extrapolated for an arbitrarily large wind farm. The machine-learning model is used to estimate the optimal yaw angle in a closed-loop format. To implement the developed control strategy, steady measurements are analysed first to determine the required input variables. This is followed by an investigation of the potential power gain and the impact of utilising a grid-search procedure. The procedure minimises adverse conditions as it collects the required data points, still achieving a power gain.
Results of wear endurance runs of wind turbine pitch bearings
Authors: Stammler Matthias , Geibel Martin
Published: June 2024

Pitch bearings of wind turbines connect the rotor blade and the rotor hub. They have to cope with highly dynamic and stochastic loads and oscillating movements for lifetimes of 20 years and more. While several test rigs for pitch bearings are in operation, only very limited data is publicly accessible. Oscillating bearings typically suffer from wear, and this work covers the results of wear endurance tests of full-scale pitch bearings. Four bearings were tested approximately 120 days each under realistic conditions which included dynamic loads in five degrees of freedom. The bearings did not show any or very limited signs of raceway wear, in contrast to results of small-scale tests and short-term tests under worst-case conditions.
A General Method For The Diagnosis Of Wind Turbine Systematic Yaw Error Based Solely On SCADA Data
Authors: Astolfi D , Pasetti M , Lombardi A , Terzi L , Girard N , Poncet P , Masson J , Dieudegard T , Castellani F
Published: June 2024

Accurate diagnosis of systematic errors affecting wind turbine operation is fundamental to maximize the energy capture. Based on this, this work deals with the systematic yaw error, occurring when the wind vane sensor is incorrectly aligned with the rotor shaft. The objective is formulating a method for individuating the presence and estimating the amount of systematic yaw error, based solely on Supervisory Control And Data Acquisition (SCADA) data analysis. The state of the art is based on inferring the presence of the static yaw error by detecting an under-performance. Therefore, there is a gap as regards the estimation of how much the static yaw error really is. The proposed method introduces major methodological novelties for tackling such issue. Indeed, nacelle wind speed measurements are used in this work because the presence of the systematic yaw error has a detectable effect on them and they are not influenced by the control system. Furthermore, this work is the first in the literature employing measurements collected with wind turbine stopped, which allows circumventing the presence of the assembly angle induced by the rotor rotation. The proposed method is based on the idea that, if two nacelle anemometers are present, the ratio between the two wind speed measurements should change in presence of a static yaw error. Through a test case discussion, it is shown that with the proposed method it is possible to estimate the static yaw error as reliably as with LiDAR measurements.
Design of a robotic platform for hybrid wind tunnel experiments of floating wind farms
Authors: Fontanella A. , Palombini G. , Piffer A. , Giberti H. , Belloli M.
Published: June 2024

Wind tunnel experiments incorporating factors like realistic ambient wind conditions, merging of multiple wakes, and active wake controls are needed to understand and improve modeling of floating wind farms. A key technology for this kind of experiments is the robotic system emulating the wind turbine motion. This article addresses the design of a robotic platform with three degrees-of-freedom (surge, pitch, and yaw) specifically tailored for wind tunnel experiments on floating wind farms. This robotic system aims to accurately reproduce the motion spectrum of floating wind turbines of 10-22MW and to simulate rotor-atmospheric wind interactions. The robotic platform has a compact design to be positioned in multiple units inside the wind tunnel and avoid disturbing the wake of the wind turbine on top of it. To achieve these goals, the wind turbine is partially integrated in the robotic platform that employs a parallel kinematic scheme and has all actuators close to the wind tunnel floor.
Quality assessment of the GPM IMERG product for lifetime prediction of turbine blades in complex terrain
Authors: Dimitriadou Krystallia , Hasager Charlotte Bay , Nouqueret Elena Cantero , Hannesdóttir Ásta
Published: June 2024

Wind turbine blades may suffer leading edge erosion when rain hits the blades extremely fast, resulting in blade damage that will negatively impact power production. Since wind turbines are growing in size, this translates into higher tip speeds when the blades rotate and, therefore, are more prone to erosion. Wind turbines in mountainous terrain may also suffer erosion due to the high winds and precipitation rates. Therefore, it becomes important to estimate blade lifetimes in wind farm sites with terrain complexity. Blade lifetime prediction models utilize a time series of rainfall intensity, wind speeds, and a turbine-specific tip speed curve. In our study, we assess the quality of the Integrated Multi-satellitE Retrievals for GPM (IMERG) final product in a blade lifetime prediction model for a mountainous area during the period 2015-2020. We first compare the IMERG rainfall intensities against in situ observations at 28 stations in Navarra in Northern Spain. We find that the two datasets are closer to agreement when the rainfall intensities are aggregated in monthly rather than 30-minute temporal scales with correlation coefficients between 0.74 - 0.93. We calculate the average annual rainfall in the period, and we find that IMERG over(under)estimates precipitation in 15 (8) stations, in line with previous studies that have pinpointed the limitations of IMERG in complex terrain. We then input the 30-minute IMERG, in situ rainfall intensities, and the 30-minute New European Wind Atlas (NEWA) wind speeds, extracted at each station location and interpolated at 119 m height, into a blade lifetime model. Our results indicate blade lifetimes of 6-17 years in 13 stations, with the in situ data to provide, on average, longer estimates than the IMERG product. Despite the limitations, we conclude that the satellite-based precipitation from IMERG may become a useful dataset for the lifetime estimation of wind turbine blades in complex terrain, with calibration and adjustments of the IMERG data.
Experimental campaign for the characterization of precipitation in a complex terrain site using high resolution observations
Authors: Méndez Beatriz , Saenz Ernesto , Pires Óscar , Cantero Elena , Bech Joan , Polls Francesc , Peinó Eric , Udina Mireia , Garcia-Benadí Albert
Published: June 2024

Precipitation has an effect on wind power at several levels. It affects the wind current, blade status, wake development and power production. Power production is affected by the harmful effect of precipitation on the blades eroding its surface and altering their aerodynamic performance. In the past decades, wind has been characterized using different techniques, but less effort has been devoted to precipitation measurement. In this work, the results of an experimental campaign performed at a high altitude complex terrain site to characterize precipitation using high resolution observations are presented. The campaign, carried out at CENER’s experimental wind farm (Alaiz) during 2023 within the framework of the Horizon Europe AIRE project, lasted nine months and different precipitation types (rain, snow, graupel) were recorded using a Micro Rain Radar (MRR), a Parsivel disdrometer and a rain gauge co-located with an instrumented wind mast with anemometers and wind vanes at different heights. Two case studies are selected to illustrate the wide range of variability found in precipitation conditions, particularly during the cool season. Precipitation characterization is very challenging at high temporal resolution, making necessary measurement campaigns with different precipitation equipment to optimize their performance and optimise its calibration. The study of precipitation profiles with MRR will support the study of precipitation impingement on wind turbine blades responsible of blade erosion. Moreover, these measurements will contribute to create the link between in-field wind farm data, laboratory experiments in rain erosion test rig and blade damage models necessary to improve wind turbine and wind farm design and operation.
Uncertainty and bias on velocities determined from an arc-scanning lidar
Authors: Mann Jakob , Hannesdóttir Ásta , Coimbra Isadora
Published: June 2024

Accurate determination of wind speed offshore is important for the progression of offshore wind energy. Arc-scanning lidars offer precise measurements of both wind speed and direction. They can be placed on a fixed footing, such as a transition piece of a fixed-bottom wind turbine, or on the coast. However, the procedure to derive the wind vector relies on the assumption of homogeneous flow, i.e., that the wind vector is constant along the scanning arc. In this study, we derive a theoretical expression for the wind speed bias due to inhomogeneity in the mean flow. We show that inhomogeneity in the flow will mostly affect the wind component tangential to the arc. The dominating term in the bias equation is equal to the range gate distance times the gradient of the wind speed away from the lidar in the direction along the arc, i.e. crudely, how fast the wind component away from the lidar changes with the scan angle. Atmospheric simulations using the Weather Research and Forecast (WRF) model of flow near mountainous coasts (Madeira Island), where the wind gradients are supposed to be largest, are used to estimate the gradient and, thereby, the bias in a real case. Errors in special situations exceed 50%.
The impact of blockage and wakes on seven power performance tests conducted at two wind farms
Authors: Bleeg J , Vishwakarma P , Del Hoyo M , Simmons L
Published: June 2024

Blockage and wakes can potentially influence wind turbine power performance measurements (PPM), distorting the measured power curve relative to the true performance of the test turbine. In this study, we take a previously proposed method to correct for the impact of blockage and wakes and test it on seven PPM conducted in simple terrain at two wind farms. Each PPM was completed according to the prevailing standard from the International Electrotechnical Commission. The correction factors derive from Reynolds-Averaged Navier-Stokes simulations of the two wind farms, and we apply these factors to the measured wind speed data on a record-by-record basis. The wind speed corrections clearly reduce variability in the measured power coefficients for the three PPM affected by long-distance wakes. The corrections do not reduce performance variability within the other four PPM. They also do not reduce differences in measured performance between the turbines at each wind farm, though numerical site calibrations do. Given these results, and considering uncertainty in the measurements, including confounding influences like terrain and turbine differences, validation against many more PPM is likely needed to adequately assess the reliability and utility of the correction method.
Lidar error in complex terrain - case study based on two measurement campaigns
Authors: Bischoff Oliver , Hofsäß Martin , Clement Dominic , Schmitt Carolin , Cheng Po Wen
Published: June 2024

Nowadays, lidar devices are increasingly being used to determine wind potential. The decision to use a lidar device or a meteorological measuring mast depends, among other things, on the topology of the terrain. In flat terrain lidar profilers are sufficiently accurate compared to previously used measuring masts. Due to their measuring principle, however, there are differences in measuring accuracy depending on the terrain. This deviation compared to a measurement with a measuring mast or with anemometers attached to it is referred to as lidar error. However, there are still uncertainties regarding the measurement accuracy of lidar profilers, especially in complex terrain.

Among other things, the size of the lidar error in relation to terrain complexity or terrain type is unclear. The lidar error can also differ for different lidar devices with different measuring principles. In order to investigate this in more detail, various lidar devices are compared in this work with regard to their measurement uncertainty in complex terrain. For this purpose, measurement data from two measurement campaigns lasting several months were analyzed. In both measurement campaigns, the lidar devices are compared with data from a measuring mast.

There are clear differences between the lidar devices. These are type-dependent, wind speed-dependent and also wind direction-dependent. The latter is due in particular to different terrain topographies from the different cardinal directions. These differences are analyzed with the help of suitable statistical parameters and then evaluated in the context of current scientific research.
Digitalization of Large-Scale Testing Facilities for the Wind Industry: DIGIT-BENCH Digital Twin
Authors: Baş Elif Ecem , Abbiati Giuseppe , Gonçalves Gomes Cláudio Ângelo , Jassmann Uwe , Larsen Peter Gorm
Published: June 2024

Testing of large wind turbine components plays a central role in delivering reliable yet cost-effective technology. However, these experiments are often lengthy and costly. Fatigue testing of a wind turbine blade might take up to 12-14 months, whereas highly accelerated lifetime testing of a nacelle demands 6-8 months. The exchange of simulation models and data between OEMs and test facilities is recognized as a critical factor in the planning of an experimental campaign. In fact, OEMs are typically very protective of their industrial secrets, and sharing such sensitive information may constitute a threat. It follows that the use of simulation models to enable more effective experimentation is not pursued efficiently.

Digital twins are emerging as a key enabling technology to improve the operation & maintenance of test benches for the wind industry. A digital twin combines physical systems and their digital models into a cyber-physical system to provide functionalities that cannot be attained by either physical or digital assets independently. The seamless integration of the test bench with digital models offered by a digital twin is expected to enhance the interaction between OEM and test bench operators.

This proceeding illustrates the status of the development of the DIGIT-BENCH digital twin developed by R&D Test Systems (R&D) and Aarhus University to serve large-scale test facilities for the wind industry. The digital twin utilizes FMI-based co-simulation to enable the coupling of physical/digital components in an industrial-secret-friendly environment. The digital twin concept is demonstrated on a 2-degrees-of-freedom test bench installed at Aarhus University.
Constrained synthetic wind fields from high-resolution 3D WindScanner measurements
Authors: Meyer Paul Julian , Giyanani Ashim , Gottschall Julia
Published: June 2024

The limited spatial and temporal resolution of wind measurements within the inflow of a wind turbine requires statistical modeling of synthetic wind fields, integrating actual measurements or derived statistics along with selected turbulence models. The short-range WindScanner technology enhances atmospheric wind measurements with high resolution in both spatial and temporal dimensions. This contribution utilizes 3D turbulent inflow measurements from three synchronized WindScanner to generate synthetic turbulent wind fields. Both, mean wind field parameters and turbulent time series are analyzed, and different input configurations for the constrained wind field generation are evaluated.

Our findings indicate the presence of periods characterized by dominant horizontal shear and veer events, with wind speed and direction differences up to 1.53 ms−1 or 8.45° across the rotor span. Additionally, the study reveals that the optimal measurement configuration for constrained turbulence modeling varies depending on the specific evaluated location and velocity component being analyzed. Another observation is that excessive constraints, placed too closely, may lead to overfitting, thereby diminishing the representativeness of the synthetic field for the lateral velocity component.
Validation of the stochastic inversion algorithm for acoustic travel-time tomography: a large eddy simulation study
Authors: Maric Emina , Hamilton Nicholas , Quon Eliot , Lee Bumseok , Thedin Regis
Published: June 2024

Acoustic tomography (AT) is explored as a remote sensing technique to obtain instantaneous snapshots of temperature and velocity fluctuations for wind energy applications. This study integrates Large Eddy Simulation (LES) with the Stochastic Inversion (SI) method to validate the algorithm’s capacity for accurate reconstruction of atmospheric fluctuations. The initial findings demonstrate the efficacy of the method in accurately capturing the predominant flow structures. Normalized L2 error evaluations further inform the algorithm’s precision, with errors accentuated in less sampled peripheral regions. The results underscore the method’s promise as a non-intrusive observational tool, with ongoing development poised to improve its precision and reliability.