Articles | Volume 11, issue 5
https://doi.org/10.5194/wes-11-1705-2026
© Author(s) 2026. 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-11-1705-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 May 2026
Research article |
| 11 May 2026
| 11 May 2026
Wind field estimation for lidar-assisted control: a comparison of proper orthogonal decomposition and interpolation techniques
Department of Wind and Energy Systems, Technical University of Denmark, Roskilde, Denmark
Søren Juhl Andersen
Department of Wind and Energy Systems, Technical University of Denmark, Roskilde, Denmark
Ásta Hannesdóttir
Department of Wind and Energy Systems, Technical University of Denmark, Roskilde, Denmark
Jennifer Marie Rinker
Department of Wind and Energy Systems, Technical University of Denmark, Roskilde, Denmark
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Julia Steiner, Emily Louise Hodgson, Maarten Paul van der Laan, Leonardo Alcayaga, Mads Pedersen, Søren Juhl Andersen, Gunner Larsen, and Pierre-Elouan Réthoré
Wind Energ. Sci., 11, 1679–1703, https://doi.org/10.5194/wes-11-1679-2026, https://doi.org/10.5194/wes-11-1679-2026, 2026
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Wake steering is a promising strategy for wind farm optimization, but its success hinges on accurate wake models. We assess models of varying fidelity for a 22 MW reference turbine, comparing single- and two-turbine cases against large-eddy simulations. All models reproduced qualitative trends for power and loads (if applicable), but quantitative agreement varied, and in general the error increased with increasing yaw angle.
Alex Rybchuk, Henrik Asmuth, Armin Haghshenas, Ásta Hannesdóttir, Jan Friedrich, Jaime Liew, Jennifer M. Rinker, Daniel R. Houck, Regis Thedin, and Patrick Moriarty
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2026-77, https://doi.org/10.5194/wes-2026-77, 2026
Preprint under review for WES
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Wind turbine engineers use wind simulation tools as part of the design process. We conducted a benchmark study for these tools. We collected detailed wind data from two sets of environments (a field campaign and a research-grade simulation). We gave benchmark participants limited information about this data, and they used their wind simulation tools of choice to reconstruct the winds. We compared the output of the different simulation codes, identifying strengths and shortcomings.
Stefan Ivanell, Warit Chanprasert, Luca Lanzilao, James Bleeg, Johan Meyers, Antoine Mathieu, Søren Juhl Andersen, Rem-Sophia Mouradi, Eric Dupont, Hugo Olivares-Espinosa, and Niels Troldborg
Wind Energ. Sci., 11, 937–960, https://doi.org/10.5194/wes-11-937-2026, https://doi.org/10.5194/wes-11-937-2026, 2026
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This study explores how the height of the atmosphere's boundary layer impacts wind farm performance, focusing on how this factor influences energy output. By simulating different boundary layer heights and conditions, this research reveals that deeper layers promote better energy recovery. The findings highlight the importance of considering atmospheric conditions when simulating wind farms to maximize energy efficiency, offering valuable insights for the wind energy industry.
Shadan Mozafari, Jennifer Marie Rinker, Paul Veers, and Katherine Dykes
Wind Energ. Sci., 11, 621–641, https://doi.org/10.5194/wes-11-621-2026, https://doi.org/10.5194/wes-11-621-2026, 2026
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The study showcases the added value of using structural response measurements in lifetime extension assessments within wind farms. In addition, it answers two of the common questions in different methods of assessment. First, it assesses the applicability of the Frandsen model for estimating conservative waked turbulence in the compact layout of wind farms. Second, it showcases probabilistic extrapolation of short- to mid-term data for long-term site-specific fatigue assessments.
Abdul Haseeb Syed, Ásta Hannesdóttir, and Jakob Mann
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2026-4, https://doi.org/10.5194/wes-2026-4, 2026
Revised manuscript under review for WES
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Large offshore wind turbines are exposed to slow changes in wind speed, which are often overlooked in design studies. We investigate how these slow wind variations impact the forces and motions of both fixed and floating wind turbines through computer simulations. Slow wind changes can lead to increased long-term structural wear and significantly impact platform motion in floating turbines. Accounting for these variations is crucial for the design and lifetime assessment of future turbines.
Emily Louise Hodgson and Søren Juhl Andersen
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-243, https://doi.org/10.5194/wes-2025-243, 2025
Revised manuscript accepted for WES
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This work investigates the impact of wind direction uncertainty on wake steering, a promising flow control strategy that aims to increase the efficiency of wind farms, using high-fidelity computational fluid dynamics. It concludes that wake steering is sensitive to both bias and uncertainty in inflow wind direction due to having a relatively small range over which gains are predicted and showing significant decreases in peak power output with increasing wind direction uncertainty.
Mads Greve Pedersen, Jennifer Marie Rinker, Isaac Farreras Alcover, and Jan Høgsberg
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-89, https://doi.org/10.5194/wes-2025-89, 2025
Revised manuscript accepted for WES
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Offshore wind turbines are prone to fatigue caused by loads from wind, waves, and operation. It may be possible to extend their life by monitoring stress histories. However, this is challenging, as part of the structure is sub-sea and sub-soil. Model-based virtual sensing offers a solution, however, current models simplify the rotor, which can lead to errors. This work addresses this error and concludes that an improved rotor model must be implemented to improve the stress history estimates.
Juan Felipe Céspedes Moreno, Juan Pablo Murcia León, and Søren Juhl Andersen
Wind Energ. Sci., 10, 597–611, https://doi.org/10.5194/wes-10-597-2025, https://doi.org/10.5194/wes-10-597-2025, 2025
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Using a global base in a proper orthogonal decomposition provides a common base for analyzing flows, such as wind turbine wakes, across an entire parameter space. This can be used to compare flows with different conditions using the same physical interpretation. This work shows the convergence of the global base, its small error compared to the truncation error in the flow reconstruction, and the insensitivity to which datasets are included for generating the global base.
Jens Visbech, Tuhfe Göçmen, Özge Sinem Özçakmak, Alexander Meyer Forsting, Ásta Hannesdóttir, and Pierre-Elouan Réthoré
Wind Energ. Sci., 9, 1811–1826, https://doi.org/10.5194/wes-9-1811-2024, https://doi.org/10.5194/wes-9-1811-2024, 2024
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Leading-edge erosion (LEE) can impact wind turbine aerodynamics and wind farm efficiency. This study couples LEE prediction, aerodynamic loss modeling, and wind farm flow modeling to show that LEE's effects on wake dynamics can affect overall energy production. Without preventive initiatives, the effects of LEE increase over time, resulting in significant annual energy production (AEP) loss.
Shadan Mozafari, Paul Veers, Jennifer Rinker, and Katherine Dykes
Wind Energ. Sci., 9, 799–820, https://doi.org/10.5194/wes-9-799-2024, https://doi.org/10.5194/wes-9-799-2024, 2024
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Turbulence is one of the main drivers of fatigue in wind turbines. There is some debate on how to model the turbulence in normal wind conditions in the design phase. To address such debates, we study the fatigue load distribution and reliability following different models of the International Electrotechnical Commission 61400-1 standard. The results show the lesser importance of load uncertainty due to turbulence distribution compared to the uncertainty of material resistance and Miner’s rule.
Ásta Hannesdóttir, David R. Verelst, and Albert M. Urbán
Wind Energ. Sci., 8, 231–245, https://doi.org/10.5194/wes-8-231-2023, https://doi.org/10.5194/wes-8-231-2023, 2023
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In this work we use observations of large coherent fluctuations to define a probabilistic gust model. The gust model provides the joint description of the gust rise time, amplitude, and direction change. We perform load simulations with a coherent gust according to the wind turbine safety standard and with the probabilistic gust model. A comparison of the simulated loads shows that the loads from the probabilistic gust model can be significantly higher due to variability in the gust parameters.
Xiaoli Guo Larsén, Marc Imberger, Ásta Hannesdóttir, and Andrea N. Hahmann
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2022-102, https://doi.org/10.5194/wes-2022-102, 2023
Revised manuscript not accepted
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We study how climate change will impact extreme winds and choice of turbine class. We use data from 18 CMIP6 members from a historic and a future period to access the change in the extreme winds. The analysis shows an overall increase in the extreme winds in the North Sea and the southern Baltic Sea, but a decrease over the Scandinavian Peninsula and most of the Baltic Sea. The analysis is inconclusive to whether higher or lower classes of turbines will be installed in the future.
Merete Badger, Haichen Zuo, Ásta Hannesdóttir, Abdalmenem Owda, and Charlotte Hasager
Wind Energ. Sci., 7, 2497–2512, https://doi.org/10.5194/wes-7-2497-2022, https://doi.org/10.5194/wes-7-2497-2022, 2022
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When wind turbine blades are exposed to strong winds and heavy rainfall, they may be damaged and their efficiency reduced. The problem is most pronounced offshore where turbines are tall and the climate is harsh. Satellites provide global half-hourly rain observations. We use these rain data as input to a model for blade lifetime prediction and find that the satellite-based predictions agree well with predictions based on observations from weather stations on the ground.
Søren Juhl Andersen and Juan Pablo Murcia Leon
Wind Energ. Sci., 7, 2117–2133, https://doi.org/10.5194/wes-7-2117-2022, https://doi.org/10.5194/wes-7-2117-2022, 2022
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Simulating the turbulent flow inside large wind farms is inherently complex and computationally expensive. A new and fast model is developed based on data from high-fidelity simulations. The model captures the flow dynamics with correct statistics for a wide range of flow conditions. The model framework provides physical insights and presents a generalization of high-fidelity simulation results beyond the case-specific scenarios, which has significant potential for future turbulence modeling.
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.
Niels Troldborg, Søren J. Andersen, Emily L. Hodgson, and Alexander Meyer Forsting
Wind Energ. Sci., 7, 1527–1532, https://doi.org/10.5194/wes-7-1527-2022, https://doi.org/10.5194/wes-7-1527-2022, 2022
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This article shows that the power performance of a wind turbine may be very different in flat and complex terrain. This is an important finding because it shows that the power output of a given wind turbine is governed by not only the available wind at the position of the turbine but also how the ambient flow develops in the region behind the turbine.
Mark Kelly, Søren Juhl Andersen, and Ásta Hannesdóttir
Wind Energ. Sci., 6, 1227–1245, https://doi.org/10.5194/wes-6-1227-2021, https://doi.org/10.5194/wes-6-1227-2021, 2021
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Via 11 years of measurements, we made a representative ensemble of wind ramps in terms of acceleration, mean speed, and shear. Constrained turbulence and large-eddy simulations were coupled to an aeroelastic model for each ensemble member. Ramp acceleration was found to dominate the maxima of thrust-associated loads, with a ramp-induced increase of 45 %–50 % plus ~ 3 % per 0.1 m/s2 of bulk ramp acceleration magnitude. The LES indicates that the ramps (and such loads) persist through the farm.
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Short summary
Large wind turbines are highly sensitive to changing winds, yet current measurements miss important details. This study compares three methods to reconstruct the full wind field ahead of a turbine in real time using lidar data and simulations. The results show these approaches can capture detailed inflow structures, which could help turbines anticipate wind changes, improve control strategies, and reduce structural loads.
Large wind turbines are highly sensitive to changing winds, yet current measurements miss...
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