Articles | Volume 9, issue 8
https://doi.org/10.5194/wes-9-1669-2024
© Author(s) 2024. 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-9-1669-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The potential of wave feedforward control for floating wind turbines: a wave tank experiment
Delft Center for Systems and Control, Delft University of Technology, Mekelweg 2, 2628 CD Delft, the Netherlands
Peter Naaijen
Maritime and Transport Technology, Delft University of Technology, Mekelweg 2, 2628 CD Delft, the Netherlands
Vincent Leroy
École Centrale de Nantes, CNRS, LHEEA, UMR 6598, Nantes Université, 44000 Nantes, France
Félicien Bonnefoy
École Centrale de Nantes, CNRS, LHEEA, UMR 6598, Nantes Université, 44000 Nantes, France
Mohammad Rasool Mojallizadeh
École Centrale de Nantes, CNRS, LHEEA, UMR 6598, Nantes Université, 44000 Nantes, France
Yves Pérignon
École Centrale de Nantes, CNRS, LHEEA, UMR 6598, Nantes Université, 44000 Nantes, France
Jan-Willem van Wingerden
Delft Center for Systems and Control, Delft University of Technology, Mekelweg 2, 2628 CD Delft, the Netherlands
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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.
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Wind Energ. Sci., 10, 207–225, https://doi.org/10.5194/wes-10-207-2025, https://doi.org/10.5194/wes-10-207-2025, 2025
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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
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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
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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
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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
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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.
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Wind Energ. Sci., 9, 623–649, https://doi.org/10.5194/wes-9-623-2024, https://doi.org/10.5194/wes-9-623-2024, 2024
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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
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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
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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
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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, M.: Feedforward control for wave disturbance rejection on floating offshore wind turbines, MS thesis, Delft University of Technology, Delft, the Netherlands, https://repository.tudelft.nl/record/uuid:8b4851ef-02f7-4c1e-a949-6c7d18371873 (last access: 2 December 2023), 2020. a
Al, M., Fontanella, A., van der Hoek, D., Liu, Y., Belloli, M., and van Wingerden, J. W.: Feedforward control for wave disturbance rejection on floating offshore wind turbines, J. Phys.: Conf. Ser., 1618, 022048, https://doi.org/10.1088/1742-6596/1618/2/022048, 2020. a, b
Bak, C., Zahle, F., Bitsche, R., Kim, T., Yde, A., Henriksen, L. C., Hansen, M. H., Blasques, J. P. A. A., Gaunaa, M., and Natarajan, A.: The DTU 10-MW reference wind turbine, in: Danish wind power research 2013, https://backend.orbit.dtu.dk/ws/portalfiles/portal/55645274/The_DTU_10MW_Reference_Turbine_Christian_Bak.pdf (last access: 2 December 2023), 2013. a, b
Becker, S., Saverin, J., Behrens de Luna, R., Papi, F., Combreau, C., Ducasse, M.-L., Marten, D., and Bianchini, A.: FLOATECH D2.2. Validation Report of QBlade-Ocean, Tech. rep., https://www.researchgate.net/publication/364360061_FLOATECH_D22_Validation_Report_of_QBlade-Ocean/stats (last access: 2 December 2023), 2022. a
Bonnefoy, F., Leroy, V., Mojallizadeh, M. R., Delacroix, S., Arnal, V., and Gilloteaux, J.-C.: Multidimensional hybrid software-in-the-loop modeling approach for experimental analysis of a floating offshore wind turbine in wave tank experiments, Ocean Eng., 309, 118390, https://doi.org/10.1016/j.oceaneng.2024.118390, 2024. a
Chen, C., Ma, Y., and Fan, T.: Review of model experimental methods focusing on aerodynamic simulation of floating offshore wind turbines, Renew. Sustain. Energ. Rev., 157, 112036, https://doi.org/10.1016/j.rser.2021.112036, 2022. a
European Commission: European Wind Power Action Plan, https://energy.ec.europa.eu/system/files/2023-10/COM_2023_669_1_EN_ACT_part1_v8.pdf (last access: 16 November 2023), 2023. a
Fischer, B.: Reducing rotor speed variations of floating wind turbines by compensation of non‐minimum phase zeros, IET Renew. Power Generat., 7, 413–419, https://doi.org/10.1049/iet-rpg.2012.0263, 2013. a, b
Fleming, P. A., Pineda, I., Rossetti, M., Wright, A. D., and Arora, D.: Evaluating methods for control of an offshore floating turbine, in: International Conference on Offshore Mechanics and Arctic Engineering, vol. 45547, 8–13 June 2014, San Francisco, California, USA, American Society of Mechanical Engineers, V09BT09A019, https://doi.org/10.1115/OMAE2014-24107, 2014. a
Fontanella, A., Al, M., van Wingerden, J., and Belloli, M.: Model-based design of a wave-feedforward control strategy in floating wind turbines, Wind Energ. Sci., 6, 885–901, https://doi.org/10.5194/wes-6-885-2021, 2021. a, b, c
Fontanella, A., Facchinetti, A., Daka, E., and Belloli, M.: Modeling the coupled aero-hydro-servo-dynamic response of 15 MW floating wind turbines with wind tunnel hardware in the loop, Renew. Energy, 219, 119442, https://doi.org/10.1016/j.renene.2023.119442, 2023. a
Hegazy, A., Naaijen, P., and van Wingerden, J. W.: A novel control architecture for floating offshore wind turbines, in: 22nd IFAC World Congress, 9–14 July 2023, Yokohama, Japan, https://doi.org/10.1016/j.ifacol.2023.10.1163, 2023a. a, b
Hegazy, A., Naaijen, P., and van Wingerden, J.-W.: Wave Feedforward Control for Large Floating Wind Turbines, in: 2023 IEEE Conference on Control Technology and Applications (CCTA), 16–18 August 2023, Bridgetown, Barbados, 593–598, https://doi.org/10.1109/CCTA54093.2023.10252529, 2023b. a, b
Jonkman, J.: Influence of Control on the Pitch Damping of a Floating Wind Turbine, in: 46th AIAA Aerospace Sciences Meeting and Exhibit, American Institute of Aeronautics and Astronautics, ISBN 978-1-62410-128-1, https://doi.org/10.2514/6.2008-1306, 2008. a, b
Kim, I.-C., Ducrozet, G., Bonnefoy, F., Leroy, V., and Perignon, Y.: Real-time phase-resolved ocean wave prediction in directional wave fields: Enhanced algorithm and experimental validation, Ocean Eng., 276, 114212, https://doi.org/10.1016/j.oceaneng.2023.114212, 2023. a, b, c
Kim, I.-C., Ducrozet, G., Leroy, V., Bonnefoy, F., Perignon, Y., and Bourguignon, S.: A real-time wave prediction in directional wave fields: Strategies for accurate continuous prediction in time, Ocean Eng., 291, 116445, https://doi.org/10.1016/j.oceaneng.2023.116445, 2024a. a, b
Kim, I.-C., Ducrozet, G., Leroy, V., Bonnefoy, F., Perignon, Y., and Delacroix, S.: Numerical and experimental investigation on deterministic prediction of ocean surface wave and wave excitation force, Appl. Ocean Res., 142, 103834, https://doi.org/10.1016/j.apor.2023.103834, 2024b. a, b
Larsen, T. J. and Hanson, T. D.: A method to avoid negative damped low frequent tower vibrations for a floating, pitch controlled wind turbine, J. Phys: Conf. Ser., 75, 012073, https://doi.org/10.1088/1742-6596/75/1/012073, 2007. a, b, c
Lemmer, F., Yu, W., Schlipf, D., and Cheng, P. W.: Robust gain scheduling baseline controller for floating offshore wind turbines, Wind Energy, 23, 17–30, https://doi.org/10.1002/we.2408, 2020. a
Ma, Y., Sclavounos, P. D., Cross-Whiter, J., and Arora, D.: Wave forecast and its application to the optimal control of offshore floating wind turbine for load mitigation, Renew. Energy, 128, 163–176, 2018. a
Mojallizadeh, M. R., Bonnefoy, F., Leroy, V., Plestan, F., Delacroix, S., Ohana, J., and Bouscasse, B.: Control design for thrust generators with application to wind turbine wave-tank testing: a sliding-mode control approach with Euler backward time-discretization, Control Eng. Pract., 146, 105894, https://doi.org/10.1016/j.conengprac.2024.105894, 2024a. a
Mojallizadeh, M. R., Bonnefoy, F., Plestan, F., Hamida, M. A., and Ohana, J.: Euler implicit time-discretization of multivariable sliding-mode controllers, ISA Trans., 147, 140–152, https://doi.org/10.1016/j.isatra.2024.01.031, 2024b. a, b
Naaijen, P. and Wijaya, A. P.: Phase Resolved Wave Prediction From Synthetic Radar Images, in: Vol. 8A: Ocean Engineering of International Conference on Offshore Mechanics and Arctic Engineering, 8–13 June 2014, San Francisco, California, USA, https://doi.org/10.1115/OMAE2014-23470, 2014. a
Navalkar, S. T., van Wingerden, J. W., Fleming, P. A., and Van Kuik, G.: Integrating robust lidar-based feedforward with feedback control to enhance speed regulation of floating wind turbines, in: IEEE 2015 American Control Conference (ACC), 1–3 July 2015, Chicago, IL, USA, 3070–3075, https://doi.org/10.1109/ACC.2015.7171804, 2015. a
Newman, J. N.: Marine hydrodynamics, The MIT Press, ISBN 9780262534826, 2018. a
Nielsen, F. G., Hanson, T. D., and Skaare, B.: Integrated Dynamic Analysis of Floating Offshore Wind Turbines, ASMEDC, 671–679, ISBN 978-0-7918-4746-6, ISBN 978-0-7918-3777-1, https://doi.org/10.1115/OMAE2006-92291, 2006. a
Raach, S., Schlipf, D., Sandner, F., Matha, D., and Cheng, P. W.: Nonlinear model predictive control of floating wind turbines with individual pitch control, in: 2014 American Control Conference, 4–6 June 2014, Portland, OR, USA, 4434–4439, https://doi.org/10.1109/ACC.2014.6858718, 2014. a
Saenz-Aguirre, A., Ulazia, A., Ibarra-Berastegi, G., and Saenz, J.: Floating wind turbine energy and fatigue loads estimation according to climate period scaled wind and waves, Energ. Convers. Manage., 271, 116303, https://doi.org/10.1016/j.enconman.2022.116303, 2022. a
Schlipf, D., Schlipf, D. J., and Kühn, M.: Nonlinear model predictive control of wind turbines using LIDAR, Wind Energy, 16, 1107–1129, https://doi.org/10.1002/we.1533, 2013. a
Schlipf, D., Fleming, P., Haizmann, F., Scholbrock, A., Hofsäß, M., Wright, A., and Cheng, P. W.: Field testing of feedforward collective pitch control on the CART2 using a nacelle-based lidar scanner, J. Phys.: Conf. Ser., 555, 012090, https://doi.org/10.1088/1742-6596/555/1/012090, 2014. a
Schlipf, D., Lemmer, F., and Raach, S.: Multi-variable feedforward control for floating wind turbines using lidar, in: ISOPE International Ocean and Polar Engineering Conference, 11–16 October 2020, virtual, https://onepetro.org/ISOPEIOPEC/proceedings-pdf/ISOPE20/All-ISOPE20/ISOPE-I-20-1174/2249085/isope-i-20-1174.pdf (last access: 2 December 2023), 2020. a
Scholbrock, A., Fleming, P., Fingersh, L., Wright, A., Schlipf, D., Haizmann, F., and Belen, F.: Field testing LIDAR-based feed-forward controls on the NREL controls advanced research turbine, in: 51st AIAA Aerospace Sciences Meeting, including the New Horizons Forum and Aerospace Exposition, 7–10 January 2013, Grapevine, Texas p. 818, https://doi.org/10.2514/6.2013-818, 2013. a
van der Veen, G., van Wingerden, J. W., Bergamasco, M., Lovera, M., and Verhaegen, M.: Closed-loop subspace identification methods: an overview, IET Control Theor. Appl., 7, 1339–1358, 2013. a
van der Veen, G. J., Couchman, I. J., and Bowyer, R.: Control of floating wind turbines, in: 2012 American Control Conference (ACC), 27–29 June 2012, Montreal, QC, Canada, 3148–3153, https://doi.org/10.1109/ACC.2012.6315120, 2012. a, b
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.
Successful wave tank experiments were conducted to evaluate the feedforward (FF) control...
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