Articles | Volume 10, issue 1
https://doi.org/10.5194/wes-10-207-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-10-207-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Jan 2025
Research article |
| 22 Jan 2025
| 22 Jan 2025
Identification of operational deflection shapes of a wind turbine gearbox using fiber-optic strain sensors on a serial production end-of-line test bench
Unai Gutierrez Santiago
CORRESPONDING AUTHOR
Faculty of Mechanical Engineering, Delft University of Technology, Mekelweg 2, 2628 CD Delft, the Netherlands
Siemens Gamesa Renewable Energy, Parque Tecnológico de Bizkaia, 48170 Zamudio, Spain
Aemilius A. W. van Vondelen
Faculty of Mechanical Engineering, Delft University of Technology, Mekelweg 2, 2628 CD Delft, the Netherlands
Alfredo Fernández Sisón
Siemens Gamesa Renewable Energy, Parque Tecnológico de Bizkaia, 48170 Zamudio, Spain
Henk Polinder
Faculty of Mechanical Engineering, Delft University of Technology, Mekelweg 2, 2628 CD Delft, the Netherlands
Jan-Willem van Wingerden
Faculty of Mechanical Engineering, Delft University of Technology, Mekelweg 2, 2628 CD Delft, the Netherlands
Related authors
Unai Gutierrez Santiago, Alfredo Fernández Sisón, Henk Polinder, and Jan-Willem van Wingerden
Wind Energ. Sci., 7, 505–521, https://doi.org/10.5194/wes-7-505-2022, https://doi.org/10.5194/wes-7-505-2022, 2022
Short summary
Short summary
The gearbox is one of the main contributors to the overall cost of wind energy, and it is acknowledged that we still do not fully understand its loading. The study presented in this paper develops a new alternative method to measure input rotor torque in wind turbine gearboxes, overcoming the drawbacks related to measuring on a rotating shaft. The method presented in this paper could make measuring gearbox torque more cost-effective, which would facilitate its adoption in serial wind turbines.
Marcus Becker, Maxime Lejeune, Philippe Chatelain, Dries Allaerts, Rafael Mudafort, and Jan-Willem van Wingerden
Wind Energ. Sci., 10, 1055–1075, https://doi.org/10.5194/wes-10-1055-2025, https://doi.org/10.5194/wes-10-1055-2025, 2025
Short summary
Short summary
Established turbine wake models are steady-state. This paper presents an open-source dynamic wake modeling framework that complements established steady-state wake models with dynamics. It is advantageous over steady-state wake models to describe wind farm power and energy over shorter periods. The model enables researchers to investigate the effectiveness of wind farm flow control strategies. This leads to a better utilization of wind farms and allows them to be used to their fullest extent.
Amr Hegazy, Peter Naaijen, and Jan-Willem van Wingerden
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-68, https://doi.org/10.5194/wes-2025-68, 2025
Preprint under review for WES
Short summary
Short summary
Floating wind turbines face stability issues when traditional onshore control methods are used, due to their motion at sea. This research reviews existing control strategies and introduces a new controller that improves stability without needing extra sensors. Simulations show it outperforms others in maintaining performance and reducing structural stress. The study highlights key trade-offs and the need for smarter, tailored control in offshore wind energy.
Aemilius Adrianus Wilhelmus van Vondelen, Marion Coquelet, Sachin Tejwant Navalkar, and Jan-Willem van Wingerden
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-51, https://doi.org/10.5194/wes-2025-51, 2025
Revised manuscript accepted for WES
Short summary
Short summary
Wind farms suffer energy losses due to wake effects between turbines. We present a new control strategy that synchronizes turbine wakes to enhance power output. By estimating and aligning the phase shifts of periodic wake structures using an advanced filtering method, downstream turbines recover more energy. Simulations show up to 10 % increased power at the third turbine. These results offer a promising path to improving wind farm efficiency while mixing wakes.
Claudia Muscari, Paolo Schito, Axelle Viré, Alberto Zasso, and Jan-Willem van Wingerden
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-149, https://doi.org/10.5194/wes-2024-149, 2025
Publication in WES not foreseen
Short summary
Short summary
This paper presents the findings of a study aimed at describing the flow system downstream of a wind turbine operated with a novel control technology. Results from heavy high-fidelity simulations are used to obtain a low-fidelity model that is quick enough to be used for the optimization of such technologies. Additionally, we were able to retrieve an improved understanding of the physics of such systems under different inflow conditions.
Majid Bastankhah, Marcus Becker, Matthew Churchfield, Caroline Draxl, Jay Prakash Goit, Mehtab Khan, Luis A. Martinez Tossas, Johan Meyers, Patrick Moriarty, Wim Munters, Asim Önder, Sara Porchetta, Eliot Quon, Ishaan Sood, Nicole van Lipzig, Jan-Willem van Wingerden, Paul Veers, and Simon Watson
Wind Energ. Sci., 9, 2171–2174, https://doi.org/10.5194/wes-9-2171-2024, https://doi.org/10.5194/wes-9-2171-2024, 2024
Short summary
Short summary
Dries Allaerts was born on 19 May 1989 and passed away at his home in Wezemaal, Belgium, on 10 October 2024 after battling cancer. Dries started his wind energy career in 2012 and had a profound impact afterward on the community, in terms of both his scientific realizations and his many friendships and collaborations in the field. His scientific acumen, open spirit of collaboration, positive attitude towards life, and playful and often cheeky sense of humor will be deeply missed by many.
Matteo Baricchio, Pieter M. O. Gebraad, and Jan-Willem van Wingerden
Wind Energ. Sci., 9, 2113–2132, https://doi.org/10.5194/wes-9-2113-2024, https://doi.org/10.5194/wes-9-2113-2024, 2024
Short summary
Short summary
Wake steering can be integrated into wind farm layout optimization through a co-design approach. This study estimates the potential of this method for a wide range of realistic conditions, adopting a tailored genetic algorithm and novel geometric yaw relations. A gain in the annual energy yield between 0.3 % and 0.4 % is obtained for a 16-tubrine farm, and a multi-objective implementation is used to limit loss in the case that wake steering is not used during farm operation.
Marion Coquelet, Maxime Lejeune, Laurent Bricteux, Aemilius A. W. van Vondelen, Jan-Willem van Wingerden, and Philippe Chatelain
Wind Energ. Sci., 9, 1923–1940, https://doi.org/10.5194/wes-9-1923-2024, https://doi.org/10.5194/wes-9-1923-2024, 2024
Short summary
Short summary
An extended Kalman filter is used to estimate the wind impinging on a wind turbine based on the blade bending moments and a turbine model. Using large-eddy simulations, this paper verifies how robust the estimator is to the turbine control strategy as it impacts loads and operating parameters. It is shown that including dynamics in the turbine model to account for delays between actuation and bending moments is needed to maintain the accuracy of the estimator when dynamic pitch control is used.
Amr Hegazy, Peter Naaijen, Vincent Leroy, Félicien Bonnefoy, Mohammad Rasool Mojallizadeh, Yves Pérignon, and Jan-Willem van Wingerden
Wind Energ. Sci., 9, 1669–1688, https://doi.org/10.5194/wes-9-1669-2024, https://doi.org/10.5194/wes-9-1669-2024, 2024
Short summary
Short summary
Successful wave tank experiments were conducted to evaluate the feedforward (FF) control strategy benefits in terms of structural loads and power quality of floating wind turbine components. The wave FF control strategy is effective when it comes to alleviating the effects of the wave forces on the floating offshore wind turbines, whereas wave FF control requires a significant amount of actuation to minimize the platform pitch motion, which makes such technology unfavorable for that objective.
Maarten J. van den Broek, Marcus Becker, Benjamin Sanderse, and Jan-Willem van Wingerden
Wind Energ. Sci., 9, 721–740, https://doi.org/10.5194/wes-9-721-2024, https://doi.org/10.5194/wes-9-721-2024, 2024
Short summary
Short summary
Wind turbine wakes negatively affect wind farm performance as they impinge on downstream rotors. Wake steering reduces these losses by redirecting wakes using yaw misalignment of the upstream rotor. We develop a novel control strategy based on model predictions to implement wake steering under time-varying conditions. The controller is tested in a high-fidelity simulation environment and improves wind farm power output compared to a state-of-the-art reference controller.
Livia Brandetti, Sebastiaan Paul Mulders, Roberto Merino-Martinez, Simon Watson, and Jan-Willem van Wingerden
Wind Energ. Sci., 9, 471–493, https://doi.org/10.5194/wes-9-471-2024, https://doi.org/10.5194/wes-9-471-2024, 2024
Short summary
Short summary
This research presents a multi-objective optimisation approach to balance vertical-axis wind turbine (VAWT) performance and noise, comparing the combined wind speed estimator and tip-speed ratio (WSE–TSR) tracking controller with a baseline. Psychoacoustic annoyance is used as a novel metric for human perception of wind turbine noise. Results showcase the WSE–TSR tracking controller’s potential in trading off the considered objectives, thereby fostering the deployment of VAWTs in urban areas.
Maarten J. van den Broek, Delphine De Tavernier, Paul Hulsman, Daan van der Hoek, Benjamin Sanderse, and Jan-Willem van Wingerden
Wind Energ. Sci., 8, 1909–1925, https://doi.org/10.5194/wes-8-1909-2023, https://doi.org/10.5194/wes-8-1909-2023, 2023
Short summary
Short summary
As wind turbines produce power, they leave behind wakes of slow-moving air. We analyse three different models to predict the effects of these wakes on downstream wind turbines. The models are validated with experimental data from wind tunnel studies for steady and time-varying conditions. We demonstrate that the models are suitable for optimally controlling wind turbines to improve power production in large wind farms.
Livia Brandetti, Sebastiaan Paul Mulders, Yichao Liu, Simon Watson, and Jan-Willem van Wingerden
Wind Energ. Sci., 8, 1553–1573, https://doi.org/10.5194/wes-8-1553-2023, https://doi.org/10.5194/wes-8-1553-2023, 2023
Short summary
Short summary
This research presents the additional benefits of applying an advanced combined wind speed estimator and tip-speed ratio tracking (WSE–TSR) controller compared to the baseline Kω2. Using a frequency-domain framework and an optimal calibration procedure, the WSE–TSR tracking control scheme shows a more flexible trade-off between conflicting objectives: power maximisation and load minimisation. Therefore, implementing this controller on large-scale wind turbines will facilitate their operation.
Daniel van den Berg, Delphine de Tavernier, and Jan-Willem van Wingerden
Wind Energ. Sci., 8, 849–864, https://doi.org/10.5194/wes-8-849-2023, https://doi.org/10.5194/wes-8-849-2023, 2023
Short summary
Short summary
Wind turbines placed in farms interact with their wake, lowering the power production of the wind farm. This can be mitigated using so-called wake mixing techniques. This work investigates the coupling between the pulse wake mixing technique and the motion of floating wind turbines using the pulse. Frequency response experiments and time domain simulations show that extra movement is undesired and that the
optimalexcitation frequency is heavily platform dependent.
Johan Meyers, Carlo Bottasso, Katherine Dykes, Paul Fleming, Pieter Gebraad, Gregor Giebel, Tuhfe Göçmen, and Jan-Willem van Wingerden
Wind Energ. Sci., 7, 2271–2306, https://doi.org/10.5194/wes-7-2271-2022, https://doi.org/10.5194/wes-7-2271-2022, 2022
Short summary
Short summary
We provide a comprehensive overview of the state of the art and the outstanding challenges in wind farm flow control, thus identifying the key research areas that could further enable commercial uptake and success. To this end, we have structured the discussion on challenges and opportunities into four main areas: (1) insight into control flow physics, (2) algorithms and AI, (3) validation and industry implementation, and (4) integrating control with system design
(co-design).
Marcus Becker, Bastian Ritter, Bart Doekemeijer, Daan van der Hoek, Ulrich Konigorski, Dries Allaerts, and Jan-Willem van Wingerden
Wind Energ. Sci., 7, 2163–2179, https://doi.org/10.5194/wes-7-2163-2022, https://doi.org/10.5194/wes-7-2163-2022, 2022
Short summary
Short summary
In this paper we present a revised dynamic control-oriented wind farm model. The model can simulate turbine wake behaviour in heterogeneous and changing wind conditions at a very low computational cost. It utilizes a three-dimensional turbine wake model which also allows capturing vertical wind speed differences. The model could be used to maximise the power generation of with farms, even during events like a wind direction change. It is publicly available and open for further development.
Tuhfe Göçmen, Filippo Campagnolo, Thomas Duc, Irene Eguinoa, Søren Juhl Andersen, Vlaho Petrović, Lejla Imširović, Robert Braunbehrens, Jaime Liew, Mads Baungaard, Maarten Paul van der Laan, Guowei Qian, Maria Aparicio-Sanchez, Rubén González-Lope, Vinit V. Dighe, Marcus Becker, Maarten J. van den Broek, Jan-Willem van Wingerden, Adam Stock, Matthew Cole, Renzo Ruisi, Ervin Bossanyi, Niklas Requate, Simon Strnad, Jonas Schmidt, Lukas Vollmer, Ishaan Sood, and Johan Meyers
Wind Energ. Sci., 7, 1791–1825, https://doi.org/10.5194/wes-7-1791-2022, https://doi.org/10.5194/wes-7-1791-2022, 2022
Short summary
Short summary
The FarmConners benchmark is the first of its kind to bring a wide variety of data sets, control settings, and model complexities for the (initial) assessment of wind farm flow control benefits. Here we present the first part of the benchmark results for three blind tests with large-scale rotors and 11 participating models in total, via direct power comparisons at the turbines as well as the observed or estimated power gain at the wind farm level under wake steering control strategy.
Daan van der Hoek, Joeri Frederik, Ming Huang, Fulvio Scarano, Carlos Simao Ferreira, and Jan-Willem van Wingerden
Wind Energ. Sci., 7, 1305–1320, https://doi.org/10.5194/wes-7-1305-2022, https://doi.org/10.5194/wes-7-1305-2022, 2022
Short summary
Short summary
The paper presents a wind tunnel experiment where dynamic induction control was implemented on a small-scale turbine. By periodically changing the pitch angle of the blades, the low-velocity turbine wake is perturbed, and hence it recovers at a faster rate. Small particles were released in the flow and subsequently recorded with a set of high-speed cameras. This allowed us to reconstruct the flow behind the turbine and investigate the effect of dynamic induction control on the wake.
Yichao Liu, Riccardo Ferrari, and Jan-Willem van Wingerden
Wind Energ. Sci., 7, 523–537, https://doi.org/10.5194/wes-7-523-2022, https://doi.org/10.5194/wes-7-523-2022, 2022
Short summary
Short summary
The objective of the paper is to develop a data-driven output-constrained individual pitch control approach, which will not only mitigate the blade loads but also reduce the pitch activities. This is achieved by only reducing the blade loads violating a user-defined bound, which leads to an economically viable load control strategy. The proposed control strategy shows promising results of load reduction in the wake-rotor overlapping and turbulent sheared wind conditions.
Unai Gutierrez Santiago, Alfredo Fernández Sisón, Henk Polinder, and Jan-Willem van Wingerden
Wind Energ. Sci., 7, 505–521, https://doi.org/10.5194/wes-7-505-2022, https://doi.org/10.5194/wes-7-505-2022, 2022
Short summary
Short summary
The gearbox is one of the main contributors to the overall cost of wind energy, and it is acknowledged that we still do not fully understand its loading. The study presented in this paper develops a new alternative method to measure input rotor torque in wind turbine gearboxes, overcoming the drawbacks related to measuring on a rotating shaft. The method presented in this paper could make measuring gearbox torque more cost-effective, which would facilitate its adoption in serial wind turbines.
Amir R. Nejad, Jonathan Keller, Yi Guo, Shawn Sheng, Henk Polinder, Simon Watson, Jianning Dong, Zian Qin, Amir Ebrahimi, Ralf Schelenz, Francisco Gutiérrez Guzmán, Daniel Cornel, Reza Golafshan, Georg Jacobs, Bart Blockmans, Jelle Bosmans, Bert Pluymers, James Carroll, Sofia Koukoura, Edward Hart, Alasdair McDonald, Anand Natarajan, Jone Torsvik, Farid K. Moghadam, Pieter-Jan Daems, Timothy Verstraeten, Cédric Peeters, and Jan Helsen
Wind Energ. Sci., 7, 387–411, https://doi.org/10.5194/wes-7-387-2022, https://doi.org/10.5194/wes-7-387-2022, 2022
Short summary
Short summary
This paper presents the state-of-the-art technologies and development trends of wind turbine drivetrains – the energy conversion systems transferring the kinetic energy of the wind to electrical energy – in different stages of their life cycle: design, manufacturing, installation, operation, lifetime extension, decommissioning and recycling. The main aim of this article is to review the drivetrain technology development as well as to identify future challenges and research gaps.
Aemilius A. W. van Vondelen, Sachin T. Navalkar, Alexandros Iliopoulos, Daan C. van der Hoek, and Jan-Willem van Wingerden
Wind Energ. Sci., 7, 161–184, https://doi.org/10.5194/wes-7-161-2022, https://doi.org/10.5194/wes-7-161-2022, 2022
Short summary
Short summary
The damping of an offshore wind turbine is a difficult physical quantity to predict, although it plays a major role in a cost-effective turbine design. This paper presents a review of all approaches that can be used for damping estimation directly from operational wind turbine data. As each use case is different, a novel suitability table is presented to enable the user to choose the most appropriate approach for the given availability and characteristics of measurement data.
Alessandro Fontanella, Mees Al, Jan-Willem van Wingerden, and Marco Belloli
Wind Energ. Sci., 6, 885–901, https://doi.org/10.5194/wes-6-885-2021, https://doi.org/10.5194/wes-6-885-2021, 2021
Short summary
Short summary
Floating wind is a key technology to harvest the abundant wind energy resource of deep waters. This research introduces a new way of controlling the wind turbine to better deal with the action of waves. The turbine is made aware of the incoming waves, and the information is exploited to enhance power production.
Bart M. Doekemeijer, Stefan Kern, Sivateja Maturu, Stoyan Kanev, Bastian Salbert, Johannes Schreiber, Filippo Campagnolo, Carlo L. Bottasso, Simone Schuler, Friedrich Wilts, Thomas Neumann, Giancarlo Potenza, Fabio Calabretta, Federico Fioretti, and Jan-Willem van Wingerden
Wind Energ. Sci., 6, 159–176, https://doi.org/10.5194/wes-6-159-2021, https://doi.org/10.5194/wes-6-159-2021, 2021
Short summary
Short summary
This article presents the results of a field experiment investigating wake steering on an onshore wind farm. The measurements show that wake steering leads to increases in power production of up to 35 % for two-turbine interactions and up to 16 % for three-turbine interactions. However, losses in power production are seen for various regions of wind directions. The results suggest that further research is necessary before wake steering will consistently lead to energy gains in wind farms.
Cited articles
Al-Khazali, H. and Askari, M.: System Identification in Rotating Structures Using Vibration and Modal Analysis, in: Topics in Modal Analysis I, Vol. 5, edited by: Allemang, R., De Clerck, J., Niezrecki, C., and Blough, J., Springer, New York, NY, 481–497, ISBN 978-1-4614-2425-3, 2012. a
Azzam, B., Baseer, A., Schelenz, R., and Jacobs, G.: Development of a Wind Turbine Gearbox Virtual Sensor using Multibody Simulation and Artificial Neural Networks, Forschung im Ingenieurwesen, 85, 1–19, https://doi.org/10.1007/s10010-021-00460-3, 2021. a
Bucher, I. and Ewins, D.: Modal analysis and testing of rotating structures, Philos. T. Roy. Soc. Lond. A, 359, 61–96, https://doi.org/10.1098/rsta.2000.0714, 2001. a
Cappelle, C., Cattebeke, M., Bosmans, J., Kirchner, M., Croes, J., and Desmet, W.: Sensor selection for cost-effective virtual torque measurements on a wind turbine gearboxAuswahl der Sensoren für kostengünstige virtuelle Momentenmessung eines Windenergieanlagengetriebes, Forschung im Ingenieurwesen, 85, 325–334, https://doi.org/10.1007/s10010-021-00464-z, 2021. a
Crameri, F.: Scientific Colour Maps, Zenodo [data set], https://doi.org/10.5281/zenodo.1243862, 2019. a
Di Lorenzo, E., Manzato, S., Peeters, B., Marulo, F., Desmet, W., Schober, W., Bienert, J., Aenlle, M., and Fernandez, P.: Operational Modal Analysis For Rotating Machines: Challenges and Solutions, Università degli Studi di Napoli Federico II, https://doi.org/10.6093/UNINA/FEDOA/11469, 2017. a
Dykes, K. L., Veers, P. S., Lantz, E. J., Holttinen, H., Carlson, O., Tuohy, A., Sempreviva, A. M., Clifton, A., Rodrigo, J. S., Berry, D. S., Laird, D., Carron, W. S., Moriarty, P. J., Marquis, M., Meneveau, C., Peinke, J., Paquette, J., Johnson, N., Pao, L., Fleming, P. A., Bottasso, C., Lehtomaki, V., Robertson, A. N., Muskulus, M., Manwell, J., Tande, J. O., Sethuraman, L., Roberts, J. O., and Fields, M. J.: IEA Wind TCP: Results of IEA Wind TCP Workshop on a Grand Vision for Wind Energy Technology, https://doi.org/10.2172/1508509, 2019. a
Egeling, T., Hidding, E., Hövelbrinks, N.and Endemann, D., Uhlending, M., Bonnet, P.and Dekkers, R., Hendicx, W., and Vandermeulen, W.: Digital gearbox use case, https://www.winergy-group.com/en/DigitalGearboxUseCase (last access: 24 November 2021), 2018. a
Greś, S., Döhler, M., Andersen, P., and Mevel, L.: Kalman filter-based subspace identification for operational modal analysis under unmeasured periodic excitation, Mech. Syst. Sig. Process., 146, 106996, https://doi.org/10.1016/j.ymssp.2020.106996, 2021. a, b
Gutierrez Santiago, U.: QBOX fiber-optic strain data for identification of operational deflection shapes, Version 1, 4TU.ResearchData [data set], https://doi.org/10.4121/8e6138ca-ad8e-4639-98d5-3ae95bcf9ef5.v1, 2024. a
Gutierrez Santiago, U., Fernández Sisón, A., Polinder, H., and van Wingerden, J.-W.: Input torque measurements for wind turbine gearboxes using fiber-optic strain sensors, Wind Energ. Sci., 7, 505–521, https://doi.org/10.5194/wes-7-505-2022, 2022. a, b, c
GWEC: Global Wind Report 2022, https://gwec.net/global-wind-report-2022/ (last access: 23 May 2023), 2023. a
Hermans, L. and van der Auweraer, H.: Modal Testing And Analysis Of Structures Under Operational Conditions: industrial applications, Mech. Syst. Sig. Process., 13, 193–216, https://doi.org/10.1006/mssp.1998.1211, 1999. a, b
Houtzager, I.: LTI System Identification Toolbox, https://www.dcsc.tudelft.nl/~jwvanwingerden/lti/ltitoolbox_product_page.html (last access: 13 June 2024), 2012. a
IEC 61400-4: Wind turbines – Part 4: Design requirements for wind turbine gearboxes, https://www.iso.org/standard/44298.html (last access: 8 May 2024), 2012. a
IRENA: International Wind Energy Development: World Market Update, https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2013/GWEC/IRENA_GWEC_WindReport_Global-Wind-Market-Update.pdf?la=en&hash=C93BDEB6DE8C4ED9EB0899B8AE7C62E3978F2985 (last access: 23 May 2023), 2013. a
Mehlan, F., Keller, J., and Nejad, A. R.: Virtual sensing of wind turbine hub loads and drivetrain fatigue damage, Forschung im Ingenieurwesen, 87, 1–12, https://doi.org/10.1007/s10010-023-00627-0, 2023. a
Mora, B., Basurko, J., Sabahi, I., Leturiondo, U., and Albizuri, J.: Strain Virtual Sensing for Structural Health Monitoring under Variable Loads, Sensors, 23, 4706, https://doi.org/10.3390/s23104706, 2023. a
Musial, W., Spitsen, P., Duffy, P., Beiter, P. Marquis, M., Hammond, R., and Shields, M.: 2022 Offshore Wind Market Report, https://www.energy.gov/sites/default/files/2022-09/offshore-wind-market-report-2022-v2.pdf (last access: 23 May 2023), 2023. a
Nejad, A. R., Keller, J., Guo, Y., Sheng, S., Polinder, H., Watson, S., Dong, J., Qin, Z., Ebrahimi, A., Schelenz, R., Gutiérrez Guzmán, F., Cornel, D., Golafshan, R., Jacobs, G., Blockmans, B., Bosmans, J., Pluymers, B., Carroll, J., Koukoura, S., Hart, E., McDonald, A., Natarajan, A., Torsvik, J., Moghadam, F. K., Daems, P.-J., Verstraeten, T., Peeters, C., and Helsen, J.: Wind turbine drivetrains: state-of-the-art technologies and future development trends, Wind Energ. Sci., 7, 387–411, https://doi.org/10.5194/wes-7-387-2022, 2022. a
Oyague, F.: Gearbox Reliability Collaborative (GRC) Description and Loading, https://doi.org/10.2172/1030848, 2011. a
Ozbek, M., Meng, F., and Rixen, D. J.: Challenges in testing and monitoring the in-operation vibration characteristics of wind turbines, Mech. Syst. Sig. Process., 41, 649–666, https://doi.org/10.1016/j.ymssp.2013.07.023, 2013. a
Perišić, N., Kirkegaard, P. H., and Pedersen, B. J.: Cost-effective shaft torque observer for condition monitoring of wind turbines, Wind Energy, 18, 1–19, https://doi.org/10.1002/we.1678, 2015. a, b
sensing360.com: Sensing 360 B.V., https://sensing360.com (last access: 30 April 2021), 2021. a
Thibault, L., Marinone, T., Avitabile, P., and Van Karsen, C.: Comparison of Modal Parameters Estimated from Operational and Experimental Modal Analysis Approaches, in: Topics in Modal Analysis I, Vol. 5, edited by: Allemang, R., De Clerck, J., Niezrecki, C., and Blough, J., Springer, New York, NY, 77–88, ISBN 978-1-4614-2425-3, 2012. a
van Kuik, G. A. M., Peinke, J., Nijssen, R., Lekou, D., Mann, J., Sørensen, J. N., Ferreira, C., van Wingerden, J. W., Schlipf, D., Gebraad, P., Polinder, H., Abrahamsen, A., van Bussel, G. J. W., Sørensen, J. D., Tavner, P., Bottasso, C. L., Muskulus, M., Matha, D., Lindeboom, H. J., Degraer, S., Kramer, O., Lehnhoff, S., Sonnenschein, M., Sørensen, P. E., Künneke, R. W., Morthorst, P. E., and Skytte, K.: Long-term research challenges in wind energy – a research agenda by the European Academy of Wind Energy, Wind Energ. Sci., 1, 1–39, https://doi.org/10.5194/wes-1-1-2016, 2016. a
van Vondelen, A. A. W., Navalkar, S. T., Iliopoulos, A., van der Hoek, D. C., and van Wingerden, J.-W.: Damping identification of offshore wind turbines using operational modal analysis: a review, Wind Energ. Sci., 7, 161–184, https://doi.org/10.5194/wes-7-161-2022, 2022. a
van Vondelen, A. A. W., Iliopoulos, A., Navalkar, S. T., van der Hoek, D. C., and van Wingerden, J.-W.: Modal analysis of an operational offshore wind turbine using enhanced Kalman filter-based subspace identification, Wind Energy, 26, 923–945, https://doi.org/10.1002/we.2849, 2023. a
Veers, P., Dykes, K., Lantz, E., Barth, S., Bottasso, C. L., Carlson, O., Clifton, A., Green, J., Green, P., Holttinen, H., Laird, D., Lehtomäki, V., Lundquist, J. K., Manwell, J., Marquis, M., Meneveau, C., Moriarty, P., Munduate, X., Muskulus, M., Naughton, J., Pao, L., Paquette, J., Peinke, J., Robertson, A., Rodrigo, J. S., Sempreviva, A. M., Smith, J. C., Tuohy, A., and Wiser, R.: Grand challenges in the science of wind energy, Science, 366, eaau2027, https://doi.org/10.1126/science.aau2027, 2019. a
Veers, P., Bottasso, C. L., Manuel, L., Naughton, J., Pao, L., Paquette, J., Robertson, A., Robinson, M., Ananthan, S., Barlas, T., Bianchini, A., Bredmose, H., Horcas, S. G., Keller, J., Madsen, H. A., Manwell, J., Moriarty, P., Nolet, S., and Rinker, J.: Grand challenges in the design, manufacture, and operation of future wind turbine systems, Wind Energ. Sci., 8, 1071–1131, https://doi.org/10.5194/wes-8-1071-2023, 2023. a, b
Verhaegen, M. and Dewilde, P.: Subspace model identification Part 1. The output-error state-space model identification class of algorithms, Int. J. Control, 56, 1187–1210, https://doi.org/10.1080/00207179208934363, 1992. a
Winergy: High Density Gear Units Winergy Website, https://www.winergy-group.com/en/Products/Gear-Units/High-Density/p/HighDensityX (last access: 23 May 2023), 2020. a
ZF-Wind-Power: ZF Wind Power breaks 200 Nm/kg torque density barrier with the modular gearbox platform SHIFT 7k, https://press.zf.com/press/en/releases/release_22016.html (last access: 23 May 2023), 2020. a
Zhang, H., Ortiz de Luna, R., Pilas, M., and Wenske, J.: A study of mechanical torque measurement on the wind turbine drive train – ways and feasibilities, Wind Energy, 21, 1406–1422, https://doi.org/10.1002/we.2263, 2018. a
Short summary
Knowing the loads applied to wind turbine gearboxes throughout their service life is becoming increasingly important as maintaining reliability with higher torque density demands is proving to be challenging. Operational deflection shapes identified from fiber-optic strain measurements have enabled the estimation of input torque, improving the assessment of the consumed life. Tracking operational deflection shapes recursively over time can potentially be used as an indicator of fault detection.
Knowing the loads applied to wind turbine gearboxes throughout their service life is becoming...
Altmetrics
Final-revised paper
Preprint