Articles | Volume 8, issue 5
https://doi.org/10.5194/wes-8-849-2023
© Author(s) 2023. 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-8-849-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
31 May 2023
Research article |
| 31 May 2023
| 31 May 2023
The dynamic coupling between the pulse wake mixing strategy and floating wind turbines
Daniel van den Berg
CORRESPONDING AUTHOR
Delft Center for Systems and Control, Delft University of Technology, Mekelweg 2, 2628 CD Delft, the Netherlands
Delphine de Tavernier
Department of Flow Physics and Technology, Delft University of Technology, Kluyverweg 1, 2629 HS Delft, the Netherlands
Jan-Willem van Wingerden
Delft Center for Systems and Control, Delft University of Technology, Mekelweg 2, 2628 CD Delft, the Netherlands
Related authors
No articles found.
Maria Cristina Vitulano, Delphine De Tavernier, Giuliano De Stefano, and Dominic von Terzi
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-125, https://doi.org/10.5194/wes-2025-125, 2025
Preprint under review for WES
Short summary
Short summary
Wind turbines are increasing in size, pushing blade tips to operate at high speed. This study employs URANS simulations to investigate the unsteady aerodynamic response of a wind turbine airfoil to angle-of-attack changes across the transonic flow threshold. By varying reduced frequency and inflow Mach number, the analysis reveals the impact of compressibility on aerodynamic performance, including a hysteresis effect, which highlights its importance for the design of next-generation rotors.
Simone Chellini, Delphine De Tavernier, and Dominic von Terzi
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-121, https://doi.org/10.5194/wes-2025-121, 2025
Preprint under review for WES
Short summary
Short summary
Growing interest in high-velocity physics is justifying research in new experimental aerodynamics. Our work provides the knowledge foundations for the next generation of large wind turbine rotors. We highlight airfoil-dependent structures and forces found in a large-scale wind tunnel experiment, for which different trends are observed. Importantly, the results delve into the force enhancement due to dynamic angle of attack oscillation, leading to higher aerodynamic loads for the blade.
Guido Lazzerini, Jacob Deleuran Grunnet, Tobias Gybel Hovgaard, Fabio Caponetti, Vasu Datta Madireddi, Delphine De Tavernier, and Sebastiaan Paul Mulders
Wind Energ. Sci., 10, 1303–1327, https://doi.org/10.5194/wes-10-1303-2025, https://doi.org/10.5194/wes-10-1303-2025, 2025
Short summary
Short summary
Large wind turbines face design challenges due to increased flexibility of blades. Conventional control strategies fail under large deformations, impacting performance. We present a feedforward–feedback control scheme, addressing flexibility and overcoming the limitations of conventional strategies. By testing it on a large-scale reference turbine with realistic wind conditions, we demonstrated improvements to power by up to 5 % while constraining blade deflections.
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.
Abhyuday Aditya, Delphine De Tavernier, Ferdinand Schrijer, Bas van Oudheusden, and Dominic von Terzi
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-65, https://doi.org/10.5194/wes-2025-65, 2025
Preprint under review for WES
Short summary
Short summary
This study is the first to experimentally test how wind turbine blades behave at near-supersonic speeds, a condition expected in the largest turbines. In the experiments, we observed unstable and potentially detrimental shock waves that become stronger at higher speeds and angles. Basic prediction tools in wind turbine design miss these details, highlighting the need for better tools and experiments to understand the extreme conditions faced by modern wind turbines.
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.
Adhyanth Giri Ajay, David Bensason, and Delphine De Tavernier
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-54, https://doi.org/10.5194/wes-2025-54, 2025
Revised manuscript accepted for WES
Short summary
Short summary
We studied the airflow around a new type of wind turbine called the X-Rotor, which could help reduce the cost of offshore wind energy. Comparing a computer simulation model and wind tunnel experiments, we found that the model correlates well under normal conditions but becomes less accurate when the blades turn. Our results show that future designs of this turbine category must consider complex three-dimensional flow effects to better predict and improve wind turbine performance.
Unai Gutierrez Santiago, Aemilius A. W. van Vondelen, Alfredo Fernández Sisón, Henk Polinder, and Jan-Willem van Wingerden
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
Short summary
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.
Maria Cristina Vitulano, Delphine De Tavernier, Giuliano De Stefano, and Dominic von Terzi
Wind Energ. Sci., 10, 103–116, https://doi.org/10.5194/wes-10-103-2025, https://doi.org/10.5194/wes-10-103-2025, 2025
Short summary
Short summary
Next-generation wind turbines are the largest rotating machines ever built, experiencing local flow Mach where the incompressibility assumption is violated, and even transonic flow can occur. This study assesses the transonic features over the FFA-W3-211 wind turbine tip airfoil for selected industrial test cases, defines the subsonic–supersonic flow threshold and evaluates the Reynolds number effects on transonic flow occurrence. Shock wave occurrence is also depicted.
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.
Shyam VimalKumar, Delphine De Tavernier, Dominic von Terzi, Marco Belloli, and Axelle Viré
Wind Energ. Sci., 9, 1967–1983, https://doi.org/10.5194/wes-9-1967-2024, https://doi.org/10.5194/wes-9-1967-2024, 2024
Short summary
Short summary
When standing still without a nacelle or blades, the vibrations on a wind turbine tower are of concern to its structural health. This study finds that the air which flows around the tower recirculates behind the tower, forming so-called wakes. These wakes initiate the vibration, and the movement itself causes the vibration to increase or decrease depending on the wind speed. The current study uses a methodology called force partitioning to analyse this in depth.
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.
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.
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
Ananthan, S. and Leishman, J. G.: Role of Filament Strain in the
Free‐Vortex Modeling of Rotor Wakes, J. Am. Helicopt. Soc., 49, 176–191, https://doi.org/10.4050/JAHS.49.176, 2004. a
Astrom, K. J. and Murray, R. M.: Feedback Systems: An Introduction for
Scientists and Engineers, Princeton University Press, USA, ISBN 0691135762, 2008. a
Barthelmie, R. J., Hansen, K., Frandsen, S. T., Rathmann, O., Schepers, J. G., Schlez, W., Phillips, J., Rados, K., Zervos, A., Politis, E. S., and
Chaviaropoulos, P. K.: Modelling and measuring flow and wind turbine wakes in
large wind farms offshore, Wind Energy, 12, 431–444, https://doi.org/10.1002/we.348,
2009. a
Barthelmie, R. J., Pryor, S. C., Frandsen, S. T., Hansen, K. S., Schepers,
J. G., Rados, K., Schlez, W., Neubert, A., Jensen, L. E., and Neckelmann, S.:
Quantifying the Impact of Wind Turbine Wakes on Power Output at
Offshore Wind Farms, J. Atmos. Ocean. Tech., 27, 1302–1317, https://doi.org/10.1175/2010JTECHA1398.1, 2010. a
Bastankhah, M. and Porté-Agel, F.: Experimental and theoretical study of wind
turbine wakes in yawed conditions, J. Fluid Mech., 806, 506–541,
https://doi.org/10.1017/jfm.2016.595, 2016. a
Becker, M., Ritter, B., Doekemeijer, B., van der Hoek, D., Konigorski, U.,
Allaerts, D., and van Wingerden, J. W.: The revised FLORIDyn model:
implementation of heterogeneous flow and the Gaussian wake, Wind Energ. Sci., 7, 2163–2179, https://doi.org/10.5194/wes-7-2163-2022, 2022. a
Berdowski, T.: Three-Dimensional Free-Wake Vortex Simulations of an Actuator
Disc in Yaw and Tilt, ARC, https://doi.org/10.2514/6.2018-0513, 2018. a
Bossanyi, E., Ruisi, R., Larsen, G. C., and Pedersen, M. M.: Axial induction
control design for a field test at Lillgrund wind farm, J. Phys.: Conf. Ser., 2265, 042032, https://doi.org/10.1088/1742-6596/2265/4/042032, 2022. a, b
Campagnolo, F., Petrovic, V., Bottasso, C., and Croce, A.: Wind tunnel testing of wake control strategies, in: 2016 American Control Conference (ACC), 513–518, https://doi.org/10.1109/ACC.2016.7524965, 2016.
a, b, c
Ciri, U., Rotea, M. A., and Leonardi, S.: Model-free control of wind farms: A comparative study between individual and coordinated extremum seeking,
Renew. Energy, 113, 1033–1045, https://doi.org/10.1016/j.renene.2017.06.065, 2017. a
Fleming, P., Gebraad, P. M. O., Lee, S., van Wingerden, J. W., Johnson, K.,
Churchfield, M., Michalakes, J., Spalart, P., and Moriarty, P.: Simulation
comparison of wake mitigation control strategies for a two-turbine case, Wind
Energy, 18, 2135–2143, https://doi.org/10.1002/we.1810, 2015. a
Fleming, P., Annoni, J., Shah, J. J., Wang, L., Ananthan, S., Zhang, Z.,
Hutchings, K., Wang, P., Chen, W., and Chen, L.: Field test of wake steering
at an offshore wind farm, Wind Energ. Sci., 2, 229–239,
https://doi.org/10.5194/wes-2-229-2017, 2017. a
Floatech: Floatech Project Website, https://www.floatech-project.com
(last access: 15 May 2023), 2022. a
Frederik, J. A. and van Wingerden, J.-W.: On the load impact of dynamic wind
farm wake mixing strategies, Renew. Energy, 194, 582–595, 2022. a
Frederik, J. A., Doekemeijer, B. M., Mulders, S. P., and van Wingerden, J. W.: The helix approach: Using dynamic individual pitch control to enhance wake mixing in wind farms, Wind Energy, 23, 1739–1751,
https://doi.org/10.1002/we.2513, 2020a. a, b, c
Frederik, J. A., Weber, R., Cacciola, S., Campagnolo, F., Croce, A., Bottasso, C., and van Wingerden, J. W.: Periodic dynamic induction control of wind farms: proving the potential in simulations and wind tunnel experiments, Wind Energy Science, 5, 245–257, https://doi.org/10.5194/wes-5-245-2020, 2020b. a
Gebraad, P. M., Teeuwisse, F. W., van Wingerden, J.-W., Fleming, P. A., Ruben, S. D., Marden, J. R., and Pao, L. Y.: A data-driven model for wind plant power optimization by yaw control, in: IEEE 2014 American Control Conference, 3128–3134, https://doi.org/10.1109/ACC.2014.6859118, 2014. a
Gebraad, P. M. O., Teeuwisse, F. W., van Wingerden, J. W., Fleming, P. A.,
Ruben, S. D., Marden, J. R., and Pao, L. Y.: Wind plant power optimization
through yaw control using a parametric model for wake effects – a CFD
simulation study, Wind Energy, 19, 95–114, https://doi.org/10.1002/we.1822, 2016. a
Goit, J. and Meyers, J.: Optimal control of energy extraction in wind-farm
boundary layers, J. Fluid Mech., 768, 5–50, https://doi.org/10.1017/jfm.2015.70, 2015. a, b
Han, C. and Nagamune, R.: Platform position control of floating wind turbines
using aerodynamic force, Renew. Energy, 151, 896–907,
https://doi.org/10.1016/j.renene.2019.11.079, 2020. a
Jensen, N. O.: A note on wind generator interaction, no. 2411 in Risø-M,
Risø National Laboratory, ISBN 87-550-0971-9, 1983. a
Jiménez, A., Crespo, A., and Migoya, E.: Application of a LES technique to characterize the wake deflection of a wind turbine in yaw, Wind Energy, 13, 559–572, https://doi.org/10.1002/we.380, 2010. a
Jonkman, J.: Definition of the Floating System for Phase IV of OC3, OSTI.GOV,
https://doi.org/10.2172/979456, 2010. a, b
Jonkman, J., Butterfield, S., Musial, W., and Scott, G.: Definition of a 5-MW
Reference Wind Turbine for Offshore System Development, OSTI.GOv, https://doi.org/10.2172/947422, 2009. a
Kheirabadi, A. C. and Nagamune, R.: Real-time relocation of floating offshore
wind turbine platforms for wind farm efficiency maximization: An assessment
of feasibility and steady-state potential, Ocean Eng., 208, 107445,
https://doi.org/10.1016/j.oceaneng.2020.107445, 2020. a, b, c
Kirchner-Bossi, N. and Porté-Agel, F.: Realistic Wind Farm Layout
Optimization through Genetic Algorithms Using a Gaussian Wake
Model, Energies, 11, 3268, https://doi.org/10.3390/en11123268, 2018. a
Komusanac, I., Brindley, G., Fraile, D., and Ramirez, L.: WindEurope Annual
Statistics 2021,
https://windeurope.org/intelligence-platform/product/wind-energy-in-europe-2021-statistics-and-the-outlook-for
(last access: 15 May 2023), 2021. a
Leishman, J., Beddoes, T. S., and Ltd, W. H.: A Generalised Model for
Airfoil Unsteady Aerodynamic Behaviour and Dynamic Stall Using
the Indicial Method, in: 42nd Annual Forum of the American Helicopter Society, https://www.osti.gov/biblio/6806820 (last access: 15 May 2023), 1986. a
Leishman, J. G., Bhagwat, M. J., and Bagai, A.: Free-Vortex Filament
Methods for the Analysis of Helicopter Rotor Wakes, J. Aircraft, 39, 759–775, https://doi.org/10.2514/2.3022, 2002. a
Leishman, J. G., Bhagwat, M. J., and Ananthan, S.: The Vortex Ring State as a Spatially and Temporally Developing Wake Instability, J. Am. Helicopt. Soc., 49, 160–175, https://doi.org/10.4050/JAHS.49.160, 2004. a
Lemmer, F., Yu, W., Müller, K., and Cheng, P. W.: Semi-submersible wind
turbine hull shape design for a favorable system response behavior, Mar.
Struct., 71, 102725, https://doi.org/10.1016/j.marstruc.2020.102725, 2020. a
Marden, J. R., Ruben, S. D., and Pao, L. Y.: A Model-Free Approach to
Wind Farm Control Using Game Theoretic Methods, in: IEEE
Transactions on Control Systems Technology, 1207–1214, https://doi.org/10.1109/TCST.2013.2257780, 2013. a
Marten, D., Paschereit, C. O., Huang, X., Meinke, M., Schröder, W., Müller,
J., and Oberleithner, K.: Predicting Wind Turbine Wake Breakdown Using a Free
Vortex Wake Code, AIAA J., 58, 4672–4685, https://doi.org/10.2514/1.J058308, 2020. a
Meyers, J., Bottasso, C., Dykes, K., Fleming, P., Gebraad, P., Giebel, G., Göçmen, T., and van Wingerden, J.-W.: Wind farm flow control: prospects and challenges, Wind Energ. Sci., 7, 2271–2306, https://doi.org/10.5194/wes-7-2271-2022, 2022. a
Mosetti, G., Poloni, C., and Diviacco, B.: Optimization of wind turbine
positioning in large windfarms by means of a genetic algorithm, Wind Eng. Indust. Aerodynam., 51, 105–116, https://doi.org/10.1016/0167-6105(94)90080-9, 1994. a
Munters, W. and Meyers, J.: Effect of wind turbine response time on optimal
dynamic induction control of wind farms, J. Phys.: Conf. Ser., 753, 052007, https://doi.org/10.1088/1742-6596/753/5/052007, 2016. a
Munters, W. and Meyers, J.: Towards practical dynamic induction control of wind farms: analysis of optimally controlled wind-farm boundary layers and
sinusoidal induction control of first-row turbines, Wind Energ. Sci., 3,
409–425, https://doi.org/10.5194/wes-3-409-2018, 2018. a, b, c, d
Nanos, E. M., Letizia, S., Clemente, D. J. B., Wang, C., Rotea, M., Iungo,
V. I., and Bottasso, C. L.: Vertical wake deflection for offshore floating
wind turbines by differential ballast control, J. Phys.: Conf. Ser., 1618, 022047, https://doi.org/10.1088/1742-6596/1618/2/022047, 2020. a, b
NREL: FLORIS, GitHub [code], https://github.com/NREL/floris (last access: 15 May 2023), 2021. a
Panwara, N. L., Kaushikb, S. C., and Kotharia, S.: Role of renewable energy
sources in environmental protection: A review, Renew. Sustain. Energ. Rev., 15, 1513–1524, 2011. a
Pereira, R., Schepers, G., and Pavel, M. D.: Validation of the
Beddoes–Leishman dynamic stall model for horizontal axis wind turbines
using MEXICO data, Wind Energy, 16, 207–219, https://doi.org/10.1002/we.541, 2013. a
Petersen, E. L., Mortensen, N. G., Landberg, L., Højstrup, J., and Frank,
H. P.: Wind power meteorology. Part I: climate and turbulence, Wind
Energy, 1, 25–45,
https://doi.org/10.1002/(SICI)1099-1824(199804)1:1+<25::AID-WE4>3.0.CO;2-D, 1998. a
QBLADE: The QBlade Software, https://qblade.org (last access: 16 May 2023), 2023. a
Ramirez, L., Fraille, D., and Brindley, G.: The European offshore wind
industry – key trends and statistics 2020,
https://windeurope.org/intelligence-platform/product/offshore-wind-in-europe-key-trends-and-statistics-2020/
(last access: 15 May 2023), 2020. a
Rodrigues, S. F., Teixeira Pinto, R., Soleimanzadeh, M., Bosman, P. A. N., and Bauer, P.: Wake losses optimization of offshore wind farms with moveable
floating wind turbines, Energy Convers. Manage., 89, 933–941,
https://doi.org/10.1016/j.enconman.2014.11.005, 2015. a
Rodriguez, S. N., Jaworski, J. W., and Michopoulos, J. G.: Stability of helical vortex structures shed from flexible rotors, J. Fluids Struct., 104, 103279, https://doi.org/10.1016/j.jfluidstructs.2021.103279, 2021. a
Shaler, K., Branlard, E., Platt, A., and Jonkman, J.: Preliminary
Introduction of a Free Vortex Wake Method Into OpenFAST, J. Phys.: Conf. Ser., 1452, 012064, https://doi.org/10.1088/1742-6596/1452/1/012064, 2020. a, b, c
van den Berg, D., de Tavernier, D., and van Wingerden, J. W.: Using The Helix Mixing Approach on Floating Offshore Wind Turbines, J.
Phys.: Conf. Ser., 2265, 042011, https://doi.org/10.1088/1742-6596/2265/4/042011, 2022. a
van den Berg, D., de Tavernier, D., and van Wingerden, J. W.: Frequency and Time Response Data presented in the publication: The Dynamic Coupling Between the Pulse Wake Mixing Strategy and Floating Wind Turbines. Version 1, 4TU.ResearchData [code and data set], https://doi.org/10.4121/507c8652-4aef-494e-8a73-3f3a68bb6b97.v1, 2023. a, b
van den Broek, M. J., Berg, D. v. d., Sanderse, B., and van Wingerden, J. W.:
Optimal Control for Wind Turbine Wake Mixing on Floating Platforms,
ARXIV [preprint], https://doi.org/10.48550/ARXIV.2210.17347, 2022. a, b
van der Hoek, D., Kanev, S., Allin, J., Bieniek, D., and Mittelmeier, N.:
Effects of axial induction control on wind farm energy production – A field test, Renew. Energy, 140, 994–1003, https://doi.org/10.1016/j.renene.2019.03.117, 2019.
a, b
van Vondelen, A. A. W., Navalkar, S. T., Kerssemakers, D. R. H., and van Wingerden, J. W.: Enhanced wake mixing in wind farms using the Helix
approach: A loads sensitivity study, in: IEEE 2023 American Control Conference, in preparation, 2023. a
WindEurope: Floating Offshore Wind Vision Statement,
https://windeurope.org/about-wind/reports/floating-vision-statement/
(last access: 15 May 2023), 2017. a
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.
Wind turbines placed in farms interact with their wake, lowering the power production of the...
Altmetrics
Final-revised paper
Preprint