Articles | Volume 11, issue 3
https://doi.org/10.5194/wes-11-983-2026
© 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-11-983-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article
| 
26 Mar 2026
Review article |
| 26 Mar 2026
| 26 Mar 2026
The lattice Boltzmann method for wind farm simulations: a review
Wind Energy Division, Department of Earth Sciences, Uppsala University – Campus Gotland, Cramérgatan 3, 62167 Visby, Sweden
Jean Bastin
Wind Energy Division, Department of Earth Sciences, Uppsala University – Campus Gotland, Cramérgatan 3, 62167 Visby, Sweden
Henrik Asmuth
Wind Energy Division, Department of Earth Sciences, Uppsala University – Campus Gotland, Cramérgatan 3, 62167 Visby, Sweden
Stefan Ivanell
Wind Energy Division, Department of Earth Sciences, Uppsala University – Campus Gotland, Cramérgatan 3, 62167 Visby, Sweden
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This study presents a new way to simulate the wind in the lower atmosphere while taking into account the changes in temperature. The model is much faster than previous models while having the same level of accuracy. This study is a step in making highly accurate software to predict the output of wind farms fast enough for use in the wind industry, ultimately reducing making electricity from wind energy cheaper and more reliable.
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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.
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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.
Henry Korb, Henrik Asmuth, Martin Schönherr, Martin Geier, and Stefan Ivanell
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Preprint under review for WES
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This study presents a new way to simulate the wind in the lower atmosphere while taking into account the changes in temperature. The model is much faster than previous models while having the same level of accuracy. This study is a step in making highly accurate software to predict the output of wind farms fast enough for use in the wind industry, ultimately reducing making electricity from wind energy cheaper and more reliable.
Øyvind Waage Hanssen-Bauer, Paula Doubrawa, Helge Aa. Madsen, Henrik Asmuth, Jason Jonkman, Gunner C. Larsen, Stefan Ivanell, and Roy Stenbro
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We studied how different industry-oriented computer models predict the behavior of winds behind turbines in a wind farm. These "wakes" reduce energy output and can affect turbines further down the row. By comparing these three models with more detailed simulations, we found they agree well on overall power but differ in how they capture turbulence and wear on machines. Our results show where the models need improvement to make wind farm computer models more accurate and reliable in the future.
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Wind Energ. Sci., 9, 1305–1321, https://doi.org/10.5194/wes-9-1305-2024, https://doi.org/10.5194/wes-9-1305-2024, 2024
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This paper has put forward a set of recommendations regarding the actuator sector model implementation details to improve the capability of the model to reproduce similar results compared to those obtained by an actuator line model, which is one of the most common ways used for numerical simulations of wind farms, while providing significant computational savings. This includes among others the velocity sampling method and a correction of the sampled velocities to calculate the blade forces.
Christoffer Hallgren, Jeanie A. Aird, Stefan Ivanell, Heiner Körnich, Ville Vakkari, Rebecca J. Barthelmie, Sara C. Pryor, and Erik Sahlée
Wind Energ. Sci., 9, 821–840, https://doi.org/10.5194/wes-9-821-2024, https://doi.org/10.5194/wes-9-821-2024, 2024
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Knowing the wind speed across the rotor of a wind turbine is key in making good predictions of the power production. However, models struggle to capture both the speed and the shape of the wind profile. Using machine learning methods based on the model data, we show that the predictions can be improved drastically. The work focuses on three coastal sites, spread over the Northern Hemisphere (the Baltic Sea, the North Sea, and the US Atlantic coast) with similar results for all sites.
Christoffer Hallgren, Jeanie A. Aird, Stefan Ivanell, Heiner Körnich, Rebecca J. Barthelmie, Sara C. Pryor, and Erik Sahlée
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Low-level jets (LLJs) are special types of non-ideal wind profiles affecting both wind energy production and loads on a wind turbine. However, among LLJ researchers, there is no consensus regarding which definition to use to identify these profiles. In this work, we compare two different ways of identifying the LLJ – the falloff definition and the shear definition – and argue why the shear definition is better suited to wind energy applications.
Christoffer Hallgren, Heiner Körnich, Stefan Ivanell, Ville Vakkari, and Erik Sahlée
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2023-129, https://doi.org/10.5194/wes-2023-129, 2023
Preprint withdrawn
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Sometimes, the wind changes direction between the bottom and top part of a wind turbine. This affects both the power production and the loads on the turbine. In this study, a climatology of pronounced changes in wind direction across the rotor is created, focusing on Scandinavia. The weather conditions responsible for these changes in wind direction are investigated and the climatology is compared to measurements from two coastal sites, indicating an underestimation by the climatology.
Gonzalo Pablo Navarro Diaz, Alejandro Daniel Otero, Henrik Asmuth, Jens Nørkær Sørensen, and Stefan Ivanell
Wind Energ. Sci., 8, 363–382, https://doi.org/10.5194/wes-8-363-2023, https://doi.org/10.5194/wes-8-363-2023, 2023
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In this paper, the capacity to simulate transient wind turbine wake interaction problems using limited wind turbine data has been extended. The key novelty is the creation of two new variants of the actuator line technique in which the rotor blade forces are computed locally using generic load data. The analysis covers a partial wake interaction case between two wind turbines for a uniform laminar inflow and for a turbulent neutral atmospheric boundary layer inflow.
Christoffer Hallgren, Johan Arnqvist, Erik Nilsson, Stefan Ivanell, Metodija Shapkalijevski, August Thomasson, Heidi Pettersson, and Erik Sahlée
Wind Energ. Sci., 7, 1183–1207, https://doi.org/10.5194/wes-7-1183-2022, https://doi.org/10.5194/wes-7-1183-2022, 2022
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Non-idealized wind profiles with negative shear in part of the profile (e.g., low-level jets) frequently occur in coastal environments and are important to take into consideration for offshore wind power. Using observations from a coastal site in the Baltic Sea, we analyze in which meteorological and sea state conditions these profiles occur and study how they alter the turbulence structure of the boundary layer compared to idealized profiles.
Christoffer Hallgren, Stefan Ivanell, Heiner Körnich, Ville Vakkari, and Erik Sahlée
Wind Energ. Sci., 6, 1205–1226, https://doi.org/10.5194/wes-6-1205-2021, https://doi.org/10.5194/wes-6-1205-2021, 2021
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As wind power becomes more popular, there is a growing demand for accurate power production forecasts. In this paper we investigated different methods to improve wind power forecasts for an offshore location in the Baltic Sea, using both simple and more advanced techniques. The performance of the methods is evaluated for different weather conditions. Smoothing the forecast was found to be the best method in general, but we recommend selecting which method to use based on the forecasted weather.
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Short summary
The lattice Boltzmann method (LBM) is a new method for very fast and accurate wind farm flow simulations. However, information on this method is scattered, and recent developments are unknown among the wind energy community. This review structures the different aspects of the method and answers common questions about it for wind energy researchers. We find that many of the building blocks for a wind farm simulation tool are present and that the LBM is accurate and efficient.
The lattice Boltzmann method (LBM) is a new method for very fast and accurate wind farm flow...
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