Articles | Volume 7, issue 1
https://doi.org/10.5194/wes-7-323-2022
© 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-7-323-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Validation of a coupled atmospheric–aeroelastic model system for wind turbine power and load calculations
Sonja Krüger
CORRESPONDING AUTHOR
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 Kraft
ForWind, Institute of Physics, Carl von Ossietzky University Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
Laura J. Lukassen
ForWind, Institute of Physics, Carl von Ossietzky University Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
Related authors
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Johannes Paulsen, Jörge Schneemann, Gerald Steinfeld, Frauke Theuer, and Martin Kühn
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-118, https://doi.org/10.5194/wes-2025-118, 2025
Preprint under review for WES
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While Low-Level Jets (LLJs) have been well-characterized, their impact on offshore wind farms is not well understood. This study uses multi-elevation lidar scans to derive vertical wind profiles up to 350 m and detect LLJs in up to 22.6 % of available measurements. Further, we analyze their effect on power production using operational wind farm data, observing a slightly negative influence and increased power fluctuations during LLJ events.
Sonja Steinbrück, Thorben Eilers, Lukas Vollmer, Kerstin Avila, and Gerald Steinfeld
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-146, https://doi.org/10.5194/wes-2024-146, 2024
Preprint withdrawn
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This paper introduces an enhanced coupling between the LES code PALM and the aeroelastic code FAST, enabling detailed turbine output in temporally and spatially heterogeneous atmospheric flows while maintaining computational efficiency. A wind speed correction is added to reduce errors from force smearing on the numerical grid. Results were evaluated through comparisons between different model setups and turbine measurements, including assessments in a two-turbine wake situation.
Leo Höning, Laura J. Lukassen, Bernhard Stoevesandt, and Iván Herráez
Wind Energ. Sci., 9, 203–218, https://doi.org/10.5194/wes-9-203-2024, https://doi.org/10.5194/wes-9-203-2024, 2024
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This study analyzes the impact of wind turbine rotor blade flexibility on the aerodynamic loading of the blades and the consequential wind characteristics in the near wake of the turbine. It is shown that gravitation leads to rotational periodic fluctuations of blade loading, which directly impacts the trajectory of the blade tip vortex at different rotor blade positions while also resulting in a non-uniform wind velocity deficit in the wake of the wind turbine.
Andreas Rott, Leo Höning, Paul Hulsman, Laura J. Lukassen, Christof Moldenhauer, and Martin Kühn
Wind Energ. Sci., 8, 1755–1770, https://doi.org/10.5194/wes-8-1755-2023, https://doi.org/10.5194/wes-8-1755-2023, 2023
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This study examines wind vane measurements of commercial wind turbines and their impact on yaw control. The authors discovered that rotor interference can cause an overestimation of wind vane measurements, leading to overcorrection of the yaw controller. A correction function that improves the yaw behaviour is presented and validated in free-field experiments on a commercial wind turbine. This work provides new insights into wind direction measurements and suggests ways to optimize yaw control.
Balthazar Arnoldus Maria Sengers, Andreas Rott, Eric Simley, Michael Sinner, Gerald Steinfeld, and Martin Kühn
Wind Energ. Sci., 8, 1693–1710, https://doi.org/10.5194/wes-8-1693-2023, https://doi.org/10.5194/wes-8-1693-2023, 2023
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Unexpected wind direction changes are undesirable, especially when performing wake steering. This study explores whether the yaw controller can benefit from accessing wind direction information before a change reaches the turbine. Results from two models with different fidelities demonstrate that wake steering can indeed benefit from preview information.
Khaled Yassin, Arne Helms, Daniela Moreno, Hassan Kassem, Leo Höning, and Laura J. Lukassen
Wind Energ. Sci., 8, 1133–1152, https://doi.org/10.5194/wes-8-1133-2023, https://doi.org/10.5194/wes-8-1133-2023, 2023
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The current turbulent wind field models stated in the IEC 61400-1 standard underestimate the probability of extreme changes in wind velocity. This underestimation can lead to the false calculation of extreme and fatigue loads on the turbine. In this work, we are trying to apply a random time-mapping technique to one of the standard turbulence models to adapt to such extreme changes. The turbulent fields generated are compared with a standard wind field to show the effects of this new mapping.
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.
Balthazar Arnoldus Maria Sengers, Matthias Zech, Pim Jacobs, Gerald Steinfeld, and Martin Kühn
Wind Energ. Sci., 7, 1455–1470, https://doi.org/10.5194/wes-7-1455-2022, https://doi.org/10.5194/wes-7-1455-2022, 2022
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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.
Janna Kristina Seifert, Martin Kraft, Martin Kühn, and Laura J. Lukassen
Wind Energ. Sci., 6, 997–1014, https://doi.org/10.5194/wes-6-997-2021, https://doi.org/10.5194/wes-6-997-2021, 2021
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Fluctuations in the power output of wind turbines are one of the major challenges in the integration and utilisation of wind energy. By analysing the power output fluctuations of wind turbine pairs in an offshore wind farm, we show that their correlation depends on their location within the wind farm and their inflow. The main outcome is that these correlation dependencies can be characterised by statistics of the power output of the wind turbines and sorted by a clustering algorithm.
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Short summary
Detailed numerical simulations of turbines in atmospheric conditions are challenging with regard to their computational demand. We coupled an atmospheric flow model and a turbine model in order to deliver extensive details about the flow and the turbine response within reasonable computational time. A comparison to measurement data was performed and showed a very good agreement. The efficiency of the tool enables applications such as load calculation in wind farms or during low-level-jet events.
Detailed numerical simulations of turbines in atmospheric conditions are challenging with regard...
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