Articles | Volume 7, issue 4
https://doi.org/10.5194/wes-7-1455-2022
© Author(s) 2022. 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-7-1455-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Jul 2022
Research article |
| 15 Jul 2022
| 15 Jul 2022
A physically interpretable data-driven surrogate model for wake steering
Balthazar Arnoldus Maria Sengers
CORRESPONDING AUTHOR
ForWind, Institute of Physics, Carl von Ossietzky University Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
Matthias Zech
German Aerospace Center (DLR), Institute of Networked Energy Systems, Carl-von-Ossietzky-Str. 15, 26129 Oldenburg, Germany
Pim Jacobs
ForWind, Institute of Physics, Carl von Ossietzky University Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
Gerald Steinfeld
ForWind, Institute of Physics, Carl von Ossietzky University Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
Martin Kühn
ForWind, Institute of Physics, Carl von Ossietzky University Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
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Andreas Rott, Bart Doekemeijer, Janna Kristina Seifert, Jan-Willem van Wingerden, and Martin Kühn
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Niko Mittelmeier and Martin Kühn
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Laura Valldecabres, Alfredo Peña, Michael Courtney, Lueder von Bremen, and Martin Kühn
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Lukas Vollmer, Gerald Steinfeld, and Martin Kühn
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Davide Trabucchi, Lukas Vollmer, and Martin Kühn
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Niko Mittelmeier, Julian Allin, Tomas Blodau, Davide Trabucchi, Gerald Steinfeld, Andreas Rott, and Martin Kühn
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Marijn Floris van Dooren, Filippo Campagnolo, Mikael Sjöholm, Nikolas Angelou, Torben Mikkelsen, and Martin Kühn
Wind Energ. Sci., 2, 329–341, https://doi.org/10.5194/wes-2-329-2017, https://doi.org/10.5194/wes-2-329-2017, 2017
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We conducted measurements in a wind tunnel with the remote sensing technique lidar to map the flow around a row of three model wind turbines. Two lidars were positioned near the wind tunnel walls to measure the two-dimensional wind vector over a defined scanning line or area without influencing the flow itself. A comparison of the lidar measurements with a hot-wire probe and a thorough uncertainty analysis confirmed the usefulness of lidar technology for such flow measurements in a wind tunnel.
Niko Mittelmeier, Tomas Blodau, and Martin Kühn
Wind Energ. Sci., 2, 175–187, https://doi.org/10.5194/wes-2-175-2017, https://doi.org/10.5194/wes-2-175-2017, 2017
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Lukas Vollmer, Gerald Steinfeld, Detlev Heinemann, and Martin Kühn
Wind Energ. Sci., 1, 129–141, https://doi.org/10.5194/wes-1-129-2016, https://doi.org/10.5194/wes-1-129-2016, 2016
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The wake flow downstream of yaw misaligned wind turbines is studied in numeric simulations of different atmospheric turbulence and shear conditions. We find that the average trajectory of the wake as well as the variation about this average is influenced by the thermal stability of the atmosphere. The results suggest that an intentional intervention in the yaw control of individual turbines to increase overall wind farm performance might be not successful during unstable thermal conditions.
Juan José Trujillo, Janna Kristina Seifert, Ines Würth, David Schlipf, and Martin Kühn
Wind Energ. Sci., 1, 41–53, https://doi.org/10.5194/wes-1-41-2016, https://doi.org/10.5194/wes-1-41-2016, 2016
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We present the analysis of the trajectories followed by the wind, in the immediate vicinity, behind an offshore wind turbine and their dependence on its yaw misalignment. We apply wake tracking on wind fields measured with a lidar (light detection and ranging) system located at the nacelle of the wind turbine and pointing downstream. The analysis reveals discrepancies of the estimated mean wake paths against theoretical and wind tunnel experiments using different wake-tracking techniques.
Related subject area
Thematic area: Dynamics and control | Topic: Wind farm control
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Revised manuscript accepted for WES
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Wake steering can be integrated within the 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-tubrines farm and a multi-objective implementation is used to limit the loss in case wake steering is not used during the farm operation.
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.
Eric Simley, Dev Millstein, Seongeun Jeong, and Paul Fleming
Wind Energ. Sci., 9, 219–234, https://doi.org/10.5194/wes-9-219-2024, https://doi.org/10.5194/wes-9-219-2024, 2024
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Wake steering is a wind farm control technology in which turbines are misaligned with the wind to deflect their wakes away from downstream turbines, increasing total power production. In this paper, we use a wind farm control model and historical electricity prices to assess the potential increase in market value from wake steering for 15 US wind plants. For most plants, we find that the relative increase in revenue from wake steering exceeds the relative increase in energy production.
Regis Thedin, Garrett Barter, Jason Jonkman, Rafael Mudafort, Christopher J. Bay, Kelsey Shaler, and Jasper Kreeft
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-6, https://doi.org/10.5194/wes-2024-6, 2024
Revised manuscript accepted for WES
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This work investigates asymmetries in terms of power performance and fatigue loading on a 5-turbine wind farm subject to wake steering strategies. Both the yaw misalignment angle and the wind direction were varied from negative to positive. We highlight conditions in which fatigue loading is lower while still maintenance good power gains and show that partial wake is the source of the asymmetries observed. We provide recommendations in terms of yaw misalignment angles for a given wind direction.
Nick Janssens and Johan Meyers
Wind Energ. Sci., 9, 65–95, https://doi.org/10.5194/wes-9-65-2024, https://doi.org/10.5194/wes-9-65-2024, 2024
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Proper wind farm control may vastly contribute to Europe's plan to go carbon neutral. However, current strategies don't account for turbine–wake interactions affecting power extraction. High-fidelity models (e.g., LES) are needed to accurately model this but are considered too slow in practice. By coarsening the resolution, we were able to design an efficient LES-based controller with real-time potential. This may allow us to bridge the gap towards practical wind farm control in the near future.
Peter Bachant, Peter Ireland, Brian Burrows, Chi Qiao, James Duncan, Danian Zheng, and Mohit Dua
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2023-175, https://doi.org/10.5194/wes-2023-175, 2024
Revised manuscript accepted for WES
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Intentional misalignment of upstream turbines in wind plants in order to steer wakes away from downstream turbines has been a topic of research interest for years, but has not yet achieved widespread commercial adoption. We deploy one such wake steering system to a utility-scale wind plant, then create a model to predict plant behavior and enable successful control. We apply calibrations to a physics-based model and use machine learning to correct its outputs to improve predictive capability.
Filippo Gori, Sylvain Laizet, and Andrew Wynn
Wind Energ. Sci., 8, 1425–1451, https://doi.org/10.5194/wes-8-1425-2023, https://doi.org/10.5194/wes-8-1425-2023, 2023
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Wake steering is a promising strategy to increase the power output of modern wind farms by mitigating the negative effects of aerodynamic interaction among turbines. As farm layouts grow in size to meet renewable targets, the complexity of wake steering optimisation increases too. With the objective of enabling robust and predictable wake steering solutions, this study investigates the sensitivity of wake steering optimisation for three different farm layouts with increasing complexity levels.
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.
Balthazar Arnoldus Maria Sengers, Gerald Steinfeld, Paul Hulsman, and Martin Kühn
Wind Energ. Sci., 8, 747–770, https://doi.org/10.5194/wes-8-747-2023, https://doi.org/10.5194/wes-8-747-2023, 2023
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The optimal misalignment angles for wake steering are determined using wake models. Although mostly analytical, data-driven models have recently shown promising results. This study validates a previously proposed data-driven model with results from a field experiment using lidar measurements. In a comparison with a state-of-the-art analytical model, it shows systematically more accurate estimates of the available power. Also when using only commonly available input data, it gives good results.
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).
Mou Lin and Fernando Porté-Agel
Wind Energ. Sci., 7, 2215–2230, https://doi.org/10.5194/wes-7-2215-2022, https://doi.org/10.5194/wes-7-2215-2022, 2022
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Large-eddy simulation (LES) is a widely used method to study wind turbine flow. To save computational resources, the turbine-inducing forces in LES are often modelled by parametrisations. We validate three widely used turbine parametrisations in LES in different yaw and offset configurations with wind tunnel measurements, and we find that, in comparison with other parametrisations, the blade element actuator disk model strikes a good balance of accuracy and computational cost.
Konstanze Kölle, Tuhfe Göçmen, Irene Eguinoa, Leonardo Andrés Alcayaga Román, Maria Aparicio-Sanchez, Ju Feng, Johan Meyers, Vasilis Pettas, and Ishaan Sood
Wind Energ. Sci., 7, 2181–2200, https://doi.org/10.5194/wes-7-2181-2022, https://doi.org/10.5194/wes-7-2181-2022, 2022
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The paper studies wind farm flow control (WFFC) in simulations with variable electricity prices. The results indicate that considering the electricity price in the operational strategy can be beneficial with respect to the gained income compared to focusing on the power gain only. Moreover, revenue maximization by balancing power production and structural load reduction is demonstrated at the example of a single wind turbine.
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.
Julian Quick, Ryan N. King, Garrett Barter, and Peter E. Hamlington
Wind Energ. Sci., 7, 1941–1955, https://doi.org/10.5194/wes-7-1941-2022, https://doi.org/10.5194/wes-7-1941-2022, 2022
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Wake steering is an emerging wind power plant control strategy where upstream turbines are intentionally yawed out of alignment with the incoming wind, thereby steering wakes away from downstream turbines. Trade-offs between the gains in power production and fatigue loads induced by this control strategy are the subject of continuing investigation. In this study, we present an optimization approach for efficiently exploring the trade-offs between power and loading during wake steering.
Florian Pöschke and Horst Schulte
Wind Energ. Sci., 7, 1593–1604, https://doi.org/10.5194/wes-7-1593-2022, https://doi.org/10.5194/wes-7-1593-2022, 2022
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The paper compares two different strategies for wind turbine control when following a power command. A model-based control scheme for a 5 MW wind turbine is designed, and a comparison in terms of the mechanical loading and the attainable power dynamics is drawn based on simulation studies. Reduced-order models suitable for integration into an upper-level control design are discussed. The dependence of the turbine behavior on the chosen strategy is illustrated and analyzed.
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.
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Short summary
Wake steering aims to redirect the wake away from a downstream turbine. This study explores the potential of a data-driven surrogate model whose equations can be interpreted physically. It estimates wake characteristics from measurable input variables by utilizing a simple linear model. The model shows encouraging results in estimating available power in the far wake, with significant improvements over currently used analytical models in conditions where wake steering is deemed most effective.
Wake steering aims to redirect the wake away from a downstream turbine. This study explores the...
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