Articles | Volume 8, issue 4
https://doi.org/10.5194/wes-8-589-2023
© 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-8-589-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Apr 2023
Research article |
| 26 Apr 2023
| 26 Apr 2023
An investigation of spatial wind direction variability and its consideration in engineering models
Anna von Brandis
Fraunhofer IWES, Küpkersweg 70, 26129 Oldenburg, Germany
Gabriele Centurelli
ForWind – Center for Wind Energy Research, University of Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
Jonas Schmidt
Fraunhofer IWES, Küpkersweg 70, 26129 Oldenburg, Germany
Lukas Vollmer
Fraunhofer IWES, Küpkersweg 70, 26129 Oldenburg, Germany
Bughsin' Djath
Institute of Coastal Systems, Helmholtz-Zentrum Hereon, Max-Planck-Str. 1, 21502 Geesthacht, Germany
Martin Dörenkämper
CORRESPONDING AUTHOR
Fraunhofer IWES, Küpkersweg 70, 26129 Oldenburg, Germany
Related authors
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Balthazar Arnoldus Maria Sengers, Lukas Vollmer, and Martin Dörenkämper
Wind Energ. Sci., 11, 4179–4203, https://doi.org/10.5194/wes-11-4179-2026, https://doi.org/10.5194/wes-11-4179-2026, 2026
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This work compared parameterizations used in mesoscale models to estimate wind energy production against operational data from several offshore sites. Results showed differences of about 5%, with higher resolution reducing generated power due to stronger wakes. One approach best reproduced key aspects of wind farm performance. Overall, results underline known limitations but confirm that these models are useful for estimating wind farm performance.
Niklas Requate, Lukas Vollmer, and René Hofmann
Wind Energ. Sci., 11, 3863–3885, https://doi.org/10.5194/wes-11-3863-2026, https://doi.org/10.5194/wes-11-3863-2026, 2026
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Wind turbines age unevenly within a farm because of site conditions and the influence of surrounding turbines. We present an approach to set lower power under certain winds to reduce fatigue loads while keeping energy high. On a nine‑turbine example farm, this added 2 to 5 years of life with small energy losses of less than 1% and increased net present value. The method is scalable to any wind farm and delivers simple look-up tables for usage in operational planning and control.
Sandra Schwegmann, Tanguy Lunel, Lukas Vollmer, and Martin Dörenkämper
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2026-103, https://doi.org/10.5194/wes-2026-103, 2026
Manuscript not accepted for further review
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This study investigates the feasibility of the Weather Research and Forecasting Model (WRF) to represent turbulence intensity (TI) and quantifies its uncertainties for the North Sea. At mesoscales, using subgrid-scale TKE for TI calculation, a mean absolute percentage error of about 30 % can be achieved. Out of the used PBL schemes, MYNN provides the lowest deviation to observed TI at a resolution of 2 km. Gray-zone simulations with a resolution of up to 111 m do rarely improve TI.
Annika Gaiser, Gerald Steinfeld, Gabriele Centurelli, and Martin Kühn
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2026-140, https://doi.org/10.5194/wes-2026-140, 2026
Revised manuscript under review for WES
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Wind farm wakes can reach far downstream, influencing the power production of other wind farms. In pursuit of improved wake recovery, we investigate how vertically staggered wind farms influence the flow field and wake recovery budget by using large-eddy simulations. Flow circulation forms inside the wind farm for certain setups and at one wake boundary, which influences wake recovery through advection and causes local speed-ups. The wake and power of a second, downstream wind farm is affected.
Nicola Bodini, Patrick Moriarty, Regis Thedin, Paula Doubrawa, Cristina Archer, Myra Blaylock, Carlo Bottasso, Bruno Carmo, Lawrence Cheung, Camille Dubreuil, Rogier Floors, Thomas Herges, Daniel Houck, Ali Kanjari, Colleen M. Kaul, Christopher Kelley, Ru Li, Julie K. Lundquist, Desirae Major, Anh Kiet Nguyen, Mike Optis, Luan R. C. Parada, Alfredo Peña, Julian Quick, David Ricarte, William C. Radünz, Raj K. Rai, Oscar García-Santiago, Jonas Schulte, Knut S. Seim, M. Paul van der Laan, Kisorthman Vimalakanthan, and Adam Wise
Wind Energ. Sci., 11, 3107–3135, https://doi.org/10.5194/wes-11-3107-2026, https://doi.org/10.5194/wes-11-3107-2026, 2026
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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.
Astrid Lampert, Beatriz Cañadillas, Thomas Rausch, Lea Schmitt, Bughsin' Djath, Johannes Schulz-Stellenfleth, Andreas Platis, Kjell zum Berge, Ines Schäfer, Jens Bange, Lukas Gruchot, Thomas Neumann, Martin Dörenkämper, Bernhard Stoevesandt, Julia Gottschall, Lukas Vollmer, Stefan Emeis, Mares Barekzai, Simon Siedersleben, Martin Kühn, Gerald Steinfeld, Detlev Heinemann, Joachim Peinke, Hendrik Heißelmann, Jörge Schneemann, Gabriele Centurelli, Philipp Waldmann, and Konrad Bärfuss
Wind Energ. Sci., 11, 3057–3075, https://doi.org/10.5194/wes-11-3057-2026, https://doi.org/10.5194/wes-11-3057-2026, 2026
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Two major aircraft measurement campaigns above the North Sea provide insights into modifications of the wind field and sea surface induced by wind farms. The aircraft performed transects at hub height upstream and downstream of wind farm clusters and identified different effects, e.g. how long it takes for the wind speed to recover after the wind farm, how changes across the coastline interact with wind energy, and if wind farms are well represented in numerical simulations.
Johanna Borowski, Kerstin Avila, and Martin Dörenkämper
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2026-129, https://doi.org/10.5194/wes-2026-129, 2026
Preprint under review for WES
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This study introduces a methodology that integrates climate model ensembles into the measure-correlate-predict framework for site-specific wind resource assessments. Using ERA5 reanalysis data and tall tower measurements from European sites, the approach bias-corrects climate model data to local conditions and reproduces historical wind climates. Results indicate decreases in summer wind speeds (typically 0.1–0.4 m s−¹) and slight winter increases but with greater ensemble spread in this season.
Johannes Schulz-Stellenfleth and Bughsin Djath
Wind Energ. Sci., 11, 2323–2344, https://doi.org/10.5194/wes-11-2323-2026, https://doi.org/10.5194/wes-11-2323-2026, 2026
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Data acquired by the European Sentinel-1A/Sentinel-B satellites are combined with a semi-empirical model to enable the easy inclusion of atmospheric offshore wind farm wakes in existing atmospheric model datasets. The model improves the agreement of data from an operational forecast centre with in situ measurements in the German Bight significantly.
Johanna Borowski, Sandra Schwegmann, Kerstin Avila, and Martin Dörenkämper
Wind Energ. Sci., 11, 661–677, https://doi.org/10.5194/wes-11-661-2026, https://doi.org/10.5194/wes-11-661-2026, 2026
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Assessing wind resources and mitigating the associated uncertainties are crucial to wind farm profitability. The study quantifies the uncertainty due to inter-annual variability, averaging 6.5 % and ranging from 1 % to 14 %, using long-term, quality-controlled wind measurements from tall met masts in terrain of varying complexity. Further, the results indicate that machine learning models are beneficial in mitigating the impact of inter-annual variability in heterogeneous and complex terrain.
Johannes Paulsen, Gerald Steinfeld, Martin Kühn, and Martin Dörenkämper
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2026-23, https://doi.org/10.5194/wes-2026-23, 2026
Revised manuscript accepted for WES
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We investigated the potential benefits in wake development and power production of a new turbine concept with a low specific rating and low induction and compared it to a reference design with same rated power. Our results show that the design can strongly increase the AEP and shows especially strong benefits during doldrum events and in strongly cluster wake affected areas. While the inner farm wake wakes are strongly decreased by the new concept, the outer farm wakes are slightly stronger.
Bjarke T. E. Olsen, Andrea N. Hahmann, Nicolas G. Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
Geosci. Model Dev., 18, 4499–4533, https://doi.org/10.5194/gmd-18-4499-2025, https://doi.org/10.5194/gmd-18-4499-2025, 2025
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Low-level jets (LLJs) are strong winds in the lower atmosphere that are important for wind energy as turbines get taller. This study compares a weather model (WRF) with real data across five North and Baltic Sea sites. Adjusting the model improved accuracy over the widely used ERA5. In key offshore regions, LLJs occur 10–15 % of the time and significantly boost wind power, especially in spring and summer, contributing up to 30 % of total capacity in some areas.
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.
Lukas Vollmer, Balthazar Arnoldus Maria Sengers, and Martin Dörenkämper
Wind Energ. Sci., 9, 1689–1693, https://doi.org/10.5194/wes-9-1689-2024, https://doi.org/10.5194/wes-9-1689-2024, 2024
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This study proposes a modification to a well-established wind farm parameterization used in mesoscale models. The wind speed at the location of the turbine, which is used to calculate power and thrust, is corrected to approximate the free wind speed. Results show that the modified parameterization produces more accurate estimates of the turbine’s power curve.
Markus Sommerfeld, Martin Dörenkämper, Jochem De Schutter, and Curran Crawford
Wind Energ. Sci., 8, 1153–1178, https://doi.org/10.5194/wes-8-1153-2023, https://doi.org/10.5194/wes-8-1153-2023, 2023
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This study investigates the performance of pumping-mode ground-generation airborne wind energy systems by determining power-optimal flight trajectories based on realistic, k-means clustered, vertical wind velocity profiles. These profiles, derived from mesoscale weather simulations at an offshore and an onshore site in Europe, are incorporated into an optimal control model that maximizes average cycle power by optimizing the kite's trajectory.
Markus Sommerfeld, Martin Dörenkämper, Jochem De Schutter, and Curran Crawford
Wind Energ. Sci., 7, 1847–1868, https://doi.org/10.5194/wes-7-1847-2022, https://doi.org/10.5194/wes-7-1847-2022, 2022
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This research explores the ground-generation airborne wind energy system (AWES) design space and investigates scaling effects by varying design parameters such as aircraft wing size, aerodynamic efficiency and mass. Therefore, representative simulated onshore and offshore wind data are implemented into an AWES trajectory optimization model. We estimate optimal annual energy production and capacity factors as well as a minimal operational lift-to-weight ratio.
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.
Beatriz Cañadillas, Maximilian Beckenbauer, Juan J. Trujillo, Martin Dörenkämper, Richard Foreman, Thomas Neumann, and Astrid Lampert
Wind Energ. Sci., 7, 1241–1262, https://doi.org/10.5194/wes-7-1241-2022, https://doi.org/10.5194/wes-7-1241-2022, 2022
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Scanning lidar measurements combined with meteorological sensors and mesoscale simulations reveal the strong directional and stability dependence of the wake strength in the direct vicinity of wind farm clusters.
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Short summary
We propose that considering large-scale wind direction changes in the computation of wind farm cluster wakes is of high relevance. Consequently, we present a new solution for engineering modeling tools that accounts for the effect of such changes in the propagation of wakes. The new model is evaluated with satellite data in the German Bight area. It has the potential to reduce uncertainty in applications such as site assessment and short-term power forecasting.
We propose that considering large-scale wind direction changes in the computation of wind farm...
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