Articles | Volume 9, issue 6
https://doi.org/10.5194/wes-9-1305-2024
© Author(s) 2024. 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-9-1305-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
An actuator sector model for wind power applications: a parametric study
Mohammad Mehdi Mohammadi
CORRESPONDING AUTHOR
Department of Earth Sciences, Wind Energy Section, Uppsala University, Cramérgatan 3, 621 67 Visby, Sweden
Hugo Olivares-Espinosa
Department of Earth Sciences, Wind Energy Section, Uppsala University, Cramérgatan 3, 621 67 Visby, Sweden
Gonzalo Pablo Navarro Diaz
Department of Earth Sciences, Wind Energy Section, Uppsala University, Cramérgatan 3, 621 67 Visby, Sweden
Stefan Ivanell
Department of Earth Sciences, Wind Energy Section, Uppsala University, Cramérgatan 3, 621 67 Visby, Sweden
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Henry Korb, Jean Bastin, Henrik Asmuth, and Stefan Ivanell
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-166, https://doi.org/10.5194/wes-2025-166, 2025
Preprint under review for WES
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The Lattice Boltzmann Method 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 amongst 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.
Øyvind Waage Hanssen-Bauer, Paula Doubrawa, Helge Aa. Madsen, Henrik Asmuth, Jason Jonkman, Gunner C. Larsen, Stefan Ivanell, and Roy Stenbro
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-163, https://doi.org/10.5194/wes-2025-163, 2025
Preprint under review for WES
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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.
Hugo Olivares-Espinosa and Johan Arnqvist
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-114, https://doi.org/10.5194/wes-2025-114, 2025
Preprint under review for WES
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This work presents an investigation into varying modelling choices for large eddy simulation over realistic forests. The focus is on how to represent the impact of upstream forest cover on the wind statistics. The work clearly demonstrates the advantage of using an explicit drag formulation together with forest density maps from airborne laser scans over using roughness length and displacement height, mainly because it leverages observable quantities and minimizes the impact uncertain choices.
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. Discuss., https://doi.org/10.5194/wes-2025-88, https://doi.org/10.5194/wes-2025-88, 2025
Preprint under review for WES
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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, the 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.
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
Wind Energ. Sci., 8, 1651–1658, https://doi.org/10.5194/wes-8-1651-2023, https://doi.org/10.5194/wes-8-1651-2023, 2023
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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.
Søren Juhl Andersen, Simon-Philippe Breton, Björn Witha, Stefan Ivanell, and Jens Nørkær Sørensen
Wind Energ. Sci., 5, 1689–1703, https://doi.org/10.5194/wes-5-1689-2020, https://doi.org/10.5194/wes-5-1689-2020, 2020
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The complexity of wind farm operation increases as the wind farms get larger and larger. Therefore, researchers from three universities have simulated numerous different large wind farms as part of an international benchmark. The study shows how simple engineering models can capture the general trends, but high-fidelity simulations are required in order to quantify the variability and uncertainty associated with power production of the wind farms and hence the potential profitability and risks.
Cited articles
Asmuth, H., Navarro Diaz, G. P., Madsen, H. A., Branlard, E., Meyer Forsting, A. R., Nilsson, K., Jonkman, J., and Ivanell, S.: Wind Turbine Response in Waked Inflow: A Modelling Benchmark Against Full-Scale Measurements, SSRN Electron. J., 191, 868–887, https://doi.org/10.2139/ssrn.3940154, 2021. a, b
Churchfield, M., Lee, S., Moriarty, P., Martinez, L., Leonardi, S., Vijayakumar, G., and Brasseur, J.: A Large-Eddy Simulation of Wind-Plant Aerodynamics, in: 50th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, American Institute of Aeronautics and Astronautics, Nashville, Tennessee, ISBN 9781600869365, https://doi.org/10.2514/6.2012-537, 2012. a, b
Churchfield, M. J., Schreck, S. J., Martinez, L. A., Meneveau, C., and Spalart, P. R.: An Advanced Actuator Line Method for Wind Energy Applications and Beyond, in: 35th Wind Energy Symposium, American Institute of Aeronautics and Astronautics, Grapevine, Texas, ISBN 9781624104565, https://doi.org/10.2514/6.2017-1998, 2017. a
Dağ, K. O. and Sørensen, J. N.: A new tip correction for actuator line computations, Wind Energy, 23, 148–160, https://doi.org/10.1002/we.2419, 2020. a
Fleming, P., Gebraad, P. M., Lee, S., Van Wingerden, J.-W., Johnson, K., Churchfield, M., Michalakes, J., Spalart, P., and Moriarty, P.: Simulation comparison of wake mitigation control strategies for a two-turbine case: Simulation comparison of wake mitigation control strategies for a two-turbine case, Wind Energy, 18, 2135–2143, https://doi.org/10.1002/we.1810, 2015. a
Hansen, M. O. L.: Aerodynamics of wind turbines, in: 2nd Edn., Earthscan, London, Sterling, VA, ISBN 9781844074389, 2008. a
Ivanell, S., Mikkelsen, R., Sørensen, J. N., and Henningson, D.: Stability analysis of the tip vortices of a wind turbine, Wind Energy, 13, 705–715, https://doi.org/10.1002/we.391, 2010. a
Jonkman, J., Butterfield, S., Musial, W., and Scott, G.: Definition of a 5-MW Reference Wind Turbine for Offshore System Development, Tech. rep., National Renewable Energy Laboratory, https://doi.org/10.2172/947422, 2009. a
Krüger, S., Steinfeld, G., Kraft, M., and Lukassen, L. J.: Validation of a coupled atmospheric–aeroelastic model system for wind turbine power and load calculations, Wind Energ. Sci., 7, 323–344, https://doi.org/10.5194/wes-7-323-2022, 2022. a
Madsen, H. A., Riziotis, V., Zahle, F., Hansen, M., Snel, H., Grasso, F., Larsen, T., Politis, E., and Rasmussen, F.: Blade element momentum modeling of inflow with shear in comparison with advanced model results: BEM modeling of inflow with shear, Wind Energy, 15, 63–81, https://doi.org/10.1002/we.493, 2012. a
Martinez, L., Leonardi, S., Churchfield, M., and Moriarty, P.: A Comparison of Actuator Disk and Actuator Line Wind Turbine Models and Best Practices for Their Use, in: 50th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, American Institute of Aeronautics and Astronautics, Nashville, Tennessee, ISBN 9781600869365, https://doi.org/10.2514/6.2012-900, 2012. a, b, c
Martínez-Tossas, L. A., Churchfield, M. J., and Leonardi, S.: Large eddy simulations of the flow past wind turbines: actuator line and disk modeling: LES of the flow past wind turbines: actuator line and disk modeling, Wind Energy, 18, 1047–1060, https://doi.org/10.1002/we.1747, 2015. a, b
Martínez‐Tossas, L. A., Churchfield, M. J., and Meneveau, C.: Optimal smoothing length scale for actuator line models of wind turbine blades based on Gaussian body force distribution, Wind Energy, 20, 1083–1096, https://doi.org/10.1002/we.2081, 2017. a
Martínez-Tossas, L. A., Churchfield, M. J., Yilmaz, A. E., Sarlak, H., Johnson, P. L., Sørensen, J. N., Meyers, J., and Meneveau, C.: Comparison of four large-eddy simulation research codes and effects of model coefficient and inflow turbulence in actuator-line-based wind turbine modeling, J. Renew. Sustain. Energ., 10, 033301, https://doi.org/10.1063/1.5004710, 2018. a
Mason, P. J. and Thomson, D. J.: Stochastic backscatter in large-eddy simulations of boundary layers, J. Fluid Mech., 242, 51–78, https://doi.org/10.1017/S0022112092002271, 1992. a
Meyer Forsting, A. R., Pirrung, G. R., and Ramos-García, N.: A vortex-based tip/smearing correction for the actuator line, Wind Energ. Sci., 4, 369–383, https://doi.org/10.5194/wes-4-369-2019, 2019. a, b, c
Meyer Forsting, A. R., Pirrung, G. R., and Ramos-García, N.: Brief communication: A fast vortex-based smearing correction for the actuator line, Wind Energ. Sci., 5, 349–353, https://doi.org/10.5194/wes-5-349-2020, 2020. a, b, c
Mittal, A., Sreenivas, K., Taylor, L. K., and Hereth, L.: Improvements to the Actuator Line Modeling for Wind Turbines, in: 33rd Wind Energy Symposium, American Institute of Aeronautics and Astronautics, Kissimmee, Florida, ISBN 9781624103445, https://doi.org/10.2514/6.2015-0216, 2015. a, b
Nathan, J., Masson, C., Dufresne, L., and Churchfield, M.: Analysis of the sweeped actuator line method, E3S Web Conf., 5, 01001, https://doi.org/10.1051/e3sconf/20150501001, 2015. a, b, c
Nathan, J., Meyer Forsting, A. R., Troldborg, N., and Masson, C.: Comparison of OpenFOAM and EllipSys3D actuator line methods with (NEW) MEXICO results, J. Phys.: Conf. Ser., 854, 012033, https://doi.org/10.1088/1742-6596/854/1/012033, 2017. a, b
Prandtl, L. and Betz, A.: Vier Abhandlungen zur Hydrodynamik und Aerodynamik, in: vol. 003 of Göttinger Klassiker der Strömungsmechanik, Universitätsverlag Göttingen, Göttingen, 88–92, https://doi.org/10.17875/gup2010-106, 2010. a
Sørensen, J. N. and Andersen, S. J.: Validation of analytical body force model for actuator disc computations, J. Phys.: Conf. Ser., 1618, 052051, https://doi.org/10.1088/1742-6596/1618/5/052051, 2020. a
Sørensen, J. N. and Myken, A.: Unsteady actuator disc model for horizontal axis wind turbines, J. Wind Eng. Indust. Aerodynam., 39, 139–149, https://doi.org/10.1016/0167-6105(92)90540-Q, 1992. a
Sørensen, J. N. and Shen, W. Z.: Numerical Modeling of Wind Turbine Wakes, J. Fluids Eng., 124, 393–399, https://doi.org/10.1115/1.1471361, 2002. a
Sørensen, J. N., Mikkelsen, R., Henningson, D. S., Ivanell, S., Sarmast, S., and Andersen, S. J.: Simulation of wind turbine wakes using the actuator line technique, Philos. T. Roy. Soc. A, 373, 20140071, https://doi.org/10.1098/rsta.2014.0071, 2015. a
Storey, R. C., Norris, S. E., and Cater, J. E.: An actuator sector method for efficient transient wind turbine simulation: An actuator sector method for wind turbine simulation, Wind Energy, 18, 699–711, https://doi.org/10.1002/we.1722, 2015. a, b
Troldborg, N., Zahle, F., Réthoré, P.-E., and Sorensen, N.: Comparison of the wake of different types of wind turbine CFD models, in: 50th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, American Institute of Aeronautics and Astronautics, Nashville, Tennessee, ISBN 9781600869365, https://doi.org/10.2514/6.2012-237, 2012. a
Vitsas, A. and Meyers, J.: Multiscale aeroelastic simulations of large wind farms in the atmospheric boundary layer, J. Phys.: Conf. Ser., 753, 082020, https://doi.org/10.1088/1742-6596/753/8/082020, 2016. a
Weller, H. G., Tabor, G., Jasak, H., and Fureby, C.: A tensorial approach to computational continuum mechanics using object-oriented techniques, Comput. Phys., 12, 620–631, https://doi.org/10.1063/1.168744, 1998. a
Xie, S.: An actuator‐line model with Lagrangian‐averaged velocity sampling and piecewise projection for wind turbine simulations, Wind Energy, 24, 1095–1106, https://doi.org/10.1002/we.2619, 2021. a
Short summary
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.
This paper has put forward a set of recommendations regarding the actuator sector model...
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