Articles | Volume 8, issue 10
https://doi.org/10.5194/wes-8-1511-2023
© 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-8-1511-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Oct 2023
Research article |
| 12 Oct 2023
| 12 Oct 2023
Revealing inflow and wake conditions of a 6 MW floating turbine
Department of Wind and Energy Systems, Technical University of Denmark, Frederiksborgvej 399, 4000, Roskilde, Denmark
Jakob Mann
Department of Wind and Energy Systems, Technical University of Denmark, Frederiksborgvej 399, 4000, Roskilde, Denmark
Camille Dubreuil-Boisclair
Equinor ASA, Sandslivegen 90, 5254, Sandsli, Norway
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Nikolas Angelou and Camille Dubreuil-Boisclair
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2026-20, https://doi.org/10.5194/wes-2026-20, 2026
Revised manuscript under review for WES
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We examined how variations in vertical wind profiles influence floating offshore wind turbines. Using data from a turbine in Scotland, we found that wind speed can change unexpectedly with height. These conditions occur frequently and, if not fully characterised, can complicate power curve verification. Our findings highlight that measuring wind across the entire rotor using nacelle-mounted lidars is essential for improving performance assessment and turbine efficiency.
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By sampling the spectra from continuous-wave Doppler lidars very fast, the rain-induced Doppler signal can be suppressed and the bias in the wind velocity estimation can be reduced. The method normalizes 3 kHz spectra by their peak values before averaging them down to 50 Hz. Over 3 h, we observe a significant reduction in the bias of the lidar data relative to the reference sonic data when the largest lidar focus distance is used. The more it rains, the more the bias is reduced.
Nikolas Angelou, Jakob Mann, and Ebba Dellwik
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In this study we use state-of-the-art scanning wind lidars to investigate the wind field in the near-wake region of a mature, open-grown tree. Our measurements provide for the first time a picture of the mean and the turbulent spatial fluctuations in the flow in the wake of a tree in its natural environment. Our observations support the hypothesis that even simple models can realistically simulate the turbulent fluctuations in the wake and thus predict the effect of trees in flow models.
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Wind turbine blades bend and twist during operation, making reliable monitoring important for performance and safety. This study presents a novel non-contact measurement system using three low-cost automotive lidar sensors to track blade motion on a full-scale wind turbine. The results agree well with existing monitoring systems and reveal how blade movement changes with operating conditions. The findings demonstrate a practical and affordable method for monitoring large wind turbines.
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Wind Energ. Sci., 11, 1147–1162, https://doi.org/10.5194/wes-11-1147-2026, https://doi.org/10.5194/wes-11-1147-2026, 2026
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This study shows that
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Predicting wind farm energy production is challenging because wind patterns are complex. We tested 16 different models against real data from a major field experiment to see which worked best. Surprisingly, the most expensive and detailed models were not always more accurate than simpler ones. We found that feeding models better weather data was the most effective way to improve accuracy. These results help the industry choose the right tools for designing more efficient wind farms.
Jakob Mann, Ansh Patel, Mikael Sjöholm, Gunhild Rolighed Thorsen, Elliot Irving Simon, Lin-Ya Hung, and Julia Gottschall
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Turbulence over the ocean at heights relevant for modern offshore wind turbines, i.e. up to 300 m or more, is not well studied. It is important to know the properties of this turbulence because it is responsible for most of the dynamic loads on these structures, and consequently how they should be designed. This data description paper explains the efforts made to provide measurements of this offshore turbulence, using five Doppler lidars.
Mohammadreza Manami, Guillaume Léa, Jakob Mann, Mikael Sjöholm, and Guillaume Gorju
Wind Energ. Sci., 11, 585–596, https://doi.org/10.5194/wes-11-585-2026, https://doi.org/10.5194/wes-11-585-2026, 2026
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A simple adaptive variant of the Doppler Beam Swinging (DBS) method is presented to improve the availability of wind velocity measurements in profiling lidars, particularly at higher altitudes. Following validation at the Østerild test site in Denmark, using three profiling lidars compared with cup anemometers and wind vanes, excellent agreement was observed. Availability assessments indicated a maximum increase of 16.9 percentage points over the standard approach.
Nikolas Angelou and Camille Dubreuil-Boisclair
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We examined how variations in vertical wind profiles influence floating offshore wind turbines. Using data from a turbine in Scotland, we found that wind speed can change unexpectedly with height. These conditions occur frequently and, if not fully characterised, can complicate power curve verification. Our findings highlight that measuring wind across the entire rotor using nacelle-mounted lidars is essential for improving performance assessment and turbine efficiency.
Carlo L. Bottasso, Sandrine Aubrun, Nicolaos A. Cutululis, Julia Gottschall, Athanasios Kolios, Jakob Mann, and Paul Veers
Wind Energ. Sci., 11, 347–348, https://doi.org/10.5194/wes-11-347-2026, https://doi.org/10.5194/wes-11-347-2026, 2026
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This editorial celebrates the 10th anniversary of Wind Energy Science, reflecting on a decade of rapid scientific progress and the journal’s role in advancing fundamental, interdisciplinary research. It highlights key developments in wind energy, the importance of open science and academia–industry collaboration, and emerging challenges such as data sharing and artificial intelligence. Above all, it honors the research community that has shaped the journal and looks ahead to the next decade.
Abdul Haseeb Syed, Ásta Hannesdóttir, and Jakob Mann
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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.
Stefan Ivanell, Bjarke T. Olsen, Antoine Mathieu, Cristina Mulet-Benzo, Abdul Haseeb Syed, Warit Chanprasert, Mikael Sjöholm, Jakob Mann, and Julia Gottschall
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-286, https://doi.org/10.5194/wes-2025-286, 2026
Revised manuscript under review for WES
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Modern GW-scale offshore wind farms face challenges from atmospheric dynamics. This study examines how boundary layer height (BLH) and large-scale turbulence affect efficiency and loads. Using WRF simulations, lidar data, and CFD modeling for a 100-turbine, 15 MW wind farm at three representative sites, we show that low BLH reduces performance. Turbulence-induced low-frequency fluctuations increase fatigue loads, underscoring the need to include BLH and turbulence in design models.
Mohammadreza Manami, Jakob Mann, Mikael Sjöholm, Guillaume Léa, and Guillaume Gorju
Atmos. Meas. Tech., 18, 7513–7523, https://doi.org/10.5194/amt-18-7513-2025, https://doi.org/10.5194/amt-18-7513-2025, 2025
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This research investigates a novel method for directly estimating wind velocity variances from averaged Doppler spectra in the frequency domain. Compared to the conventional time-domain approach, the proposed method offers a substantial improvement. Despite some limitations, this study marks a significant advancement in turbulence estimation using pulsed Doppler lidars, which presents promising potential for wind turbine load assessments.
Shokoufeh Malekmohammadi, Etienne Cheynet, Joachim Reuder, Claus Linnemann, Mikael Sjöholm, Jakob Mann, and Gregor Giebel
EGUsphere, https://doi.org/10.5194/egusphere-2025-3148, https://doi.org/10.5194/egusphere-2025-3148, 2025
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This paper presents a novel measurement technique for long-term, high-temporal resolution wind velocity observations in offshore wind farms, while also addressing the need for spatial coverage. The approach involves the deployment of a ship-based lidar system consisting of two co-located lidars on a vessel. This strategy is designed to enable a detailed assessment of vertical wind velocity within and around offshore wind farms.
Abdul Haseeb Syed, Jakob Mann, and Mohammadreza Manami
EGUsphere, https://doi.org/10.5194/egusphere-2025-5214, https://doi.org/10.5194/egusphere-2025-5214, 2025
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We present a new structure function model to estimate the turbulence energy dissipation rate using lidar velocities. The model corrects for turbulence filtering due to the lidar probe volume by applying a Gaussian weighting function. By utilizing the high 3 m range-gate resolution of the BEAM 6x pulsed lidar, we achieve excellent agreement between turbulence energy dissipation rate values derived from lidar and sonic anemometer at three heights, with correlation coefficients exceeding 0.9.
Isadora L. Coimbra, Jakob Mann, José M. L. M. Palma, and Vasco T. P. Batista
Atmos. Meas. Tech., 18, 287–303, https://doi.org/10.5194/amt-18-287-2025, https://doi.org/10.5194/amt-18-287-2025, 2025
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Dual-lidar measurements are explored here as a cost-effective alternative for measuring the wind at great heights. From measurements at a mountainous site, we showed that this methodology can accurately capture mean wind speeds and turbulence under different flow conditions, and we recommended optimal lidar placement and sampling rates. This methodology allows the construction of vertical wind profiles up to 430 m, surpassing traditional meteorological mast heights and single-lidar capabilities.
Abdul Haseeb Syed and Jakob Mann
Wind Energ. Sci., 9, 1381–1391, https://doi.org/10.5194/wes-9-1381-2024, https://doi.org/10.5194/wes-9-1381-2024, 2024
Short summary
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Wind flow consists of swirling patterns of air called eddies, some as big as many kilometers across, while others are as small as just a few meters. This paper introduces a method to simulate these large swirling patterns on a flat grid. Using these simulations we can better figure out how these large eddies affect big wind turbines in terms of loads and forces.
Liqin Jin, Mauro Ghirardelli, Jakob Mann, Mikael Sjöholm, Stephan Thomas Kral, and Joachim Reuder
Atmos. Meas. Tech., 17, 2721–2737, https://doi.org/10.5194/amt-17-2721-2024, https://doi.org/10.5194/amt-17-2721-2024, 2024
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Three-dimensional wind fields can be accurately measured by sonic anemometers. However, the traditional mast-mounted sonic anemometers are not flexible in various applications, which can be potentially overcome by drones. Therefore, we conducted a proof-of-concept study by applying three continuous-wave Doppler lidars to characterize the complex flow around a drone to validate the results obtained by CFD simulations. Both methods show good agreement, with a velocity difference of 0.1 m s-1.
Liqin Jin, Jakob Mann, Nikolas Angelou, and Mikael Sjöholm
Atmos. Meas. Tech., 16, 6007–6023, https://doi.org/10.5194/amt-16-6007-2023, https://doi.org/10.5194/amt-16-6007-2023, 2023
Short summary
Short summary
By sampling the spectra from continuous-wave Doppler lidars very fast, the rain-induced Doppler signal can be suppressed and the bias in the wind velocity estimation can be reduced. The method normalizes 3 kHz spectra by their peak values before averaging them down to 50 Hz. Over 3 h, we observe a significant reduction in the bias of the lidar data relative to the reference sonic data when the largest lidar focus distance is used. The more it rains, the more the bias is reduced.
Maarten Paul van der Laan, Oscar García-Santiago, Mark Kelly, Alexander Meyer Forsting, Camille Dubreuil-Boisclair, Knut Sponheim Seim, Marc Imberger, Alfredo Peña, Niels Nørmark Sørensen, and Pierre-Elouan Réthoré
Wind Energ. Sci., 8, 819–848, https://doi.org/10.5194/wes-8-819-2023, https://doi.org/10.5194/wes-8-819-2023, 2023
Short summary
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Offshore wind farms are more commonly installed in wind farm clusters, where wind farm interaction can lead to energy losses. In this work, an efficient numerical method is presented that can be used to estimate these energy losses. The novel method is verified with higher-fidelity numerical models and validated with measurements of an existing wind farm cluster.
Wei Fu, Alessandro Sebastiani, Alfredo Peña, and Jakob Mann
Wind Energ. Sci., 8, 677–690, https://doi.org/10.5194/wes-8-677-2023, https://doi.org/10.5194/wes-8-677-2023, 2023
Short summary
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Nacelle lidars with different beam scanning locations and two types of systems are considered for inflow turbulence estimations using both numerical simulations and field measurements. The turbulence estimates from a sonic anemometer at the hub height of a Vestas V52 turbine are used as references. The turbulence parameters are retrieved using the radial variances and a least-squares procedure. The findings from numerical simulations have been verified by the analysis of the field measurements.
Abdul Haseeb Syed, Jakob Mann, Andreas Platis, and Jens Bange
Wind Energ. Sci., 8, 125–139, https://doi.org/10.5194/wes-8-125-2023, https://doi.org/10.5194/wes-8-125-2023, 2023
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Wind turbines extract energy from the incoming wind flow, which needs to be recovered. In very large offshore wind farms, the energy is recovered mostly from above the wind farm in a process called entrainment. In this study, we analyzed the effect of atmospheric stability on the entrainment process in large offshore wind farms using measurements recorded by a research aircraft. This is the first time that in situ measurements are used to study the energy recovery process above wind farms.
Felix Kelberlau and Jakob Mann
Atmos. Meas. Tech., 15, 5323–5341, https://doi.org/10.5194/amt-15-5323-2022, https://doi.org/10.5194/amt-15-5323-2022, 2022
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Floating lidar systems are used for measuring wind speeds offshore, and their motion influences the measurements. This study describes the motion-induced bias on mean wind speed estimates by simulating the lidar sampling pattern of a moving lidar. An analytic model is used to validate the simulations. The bias is low and depends on amplitude and frequency of motion as well as on wind shear. It has been estimated for the example of the Fugro SEAWATCH wind lidar buoy carrying a ZX 300M lidar.
Wei Fu, Alfredo Peña, and Jakob Mann
Wind Energ. Sci., 7, 831–848, https://doi.org/10.5194/wes-7-831-2022, https://doi.org/10.5194/wes-7-831-2022, 2022
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Measuring the variability of the wind is essential to operate the wind turbines safely. Lidars of different configurations have been placed on the turbines’ nacelle to measure the inflow remotely. This work found that the multiple-beam lidar is the only one out of the three employed nacelle lidars that can give detailed information about the inflow variability. The other two commercial lidars, which have two and four beams, respectively, measure only the fluctuation in the along-wind direction.
Nikolas Angelou, Jakob Mann, and Ebba Dellwik
Atmos. Chem. Phys., 22, 2255–2268, https://doi.org/10.5194/acp-22-2255-2022, https://doi.org/10.5194/acp-22-2255-2022, 2022
Short summary
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In this study we use state-of-the-art scanning wind lidars to investigate the wind field in the near-wake region of a mature, open-grown tree. Our measurements provide for the first time a picture of the mean and the turbulent spatial fluctuations in the flow in the wake of a tree in its natural environment. Our observations support the hypothesis that even simple models can realistically simulate the turbulent fluctuations in the wake and thus predict the effect of trees in flow models.
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Short summary
This study presents the first experimental investigation using two nacelle-mounted wind lidars that reveal the upwind and downwind conditions relative to a full-scale floating wind turbine. We find that in the case of floating wind turbines with small pitch and roll oscillating motions (< 1°), the ambient turbulence is the main driving factor that determines the propagation of the wake characteristics.
This study presents the first experimental investigation using two nacelle-mounted wind lidars...
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