Articles | Volume 8, issue 3
https://doi.org/10.5194/wes-8-363-2023
© 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-8-363-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Actuator line model using simplified force calculation methods
Gonzalo Pablo Navarro Diaz
CORRESPONDING AUTHOR
Wind Energy Section, Uppsala University, Campus Gotland, Visby, Sweden
Alejandro Daniel Otero
Facultad de Ingeniería, Universidad de Buenos Aires, Buenos Aires, Argentina
Computational Simulation Center (CSC-CONICET), Buenos Aires, Argentina
Henrik Asmuth
Wind Energy Section, Uppsala University, Campus Gotland, Visby, Sweden
Jens Nørkær Sørensen
Department of Wind and Energy Systems, Technical University of Denmark, Lyngby, Denmark
Stefan Ivanell
Wind Energy Section, Uppsala University, Campus Gotland, 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.
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.
Dimas Alejandro Barile, Roberto Sosa, Sandrine Aubrun, and Alejandro Daniel Otero
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-2, https://doi.org/10.5194/wes-2025-2, 2025
Manuscript not accepted for further review
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This work sets out a novel methodology for the CFD simulation of an ABL wind tunnel flow. Initially, the scheme is well validated against experimental measurements, and then it is applied to the study of a floating offshore wind turbine model under surge motion with varying turbulence intensities and motion frequencies. New insights are gained related to wake recovery of a wind turbine under surge motion, as certain frequency cases exhibit a distinctive behaviour regarding coherence structures.
Mohammad Mehdi Mohammadi, Hugo Olivares-Espinosa, Gonzalo Pablo Navarro Diaz, and Stefan Ivanell
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
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.
Jens N. Sørensen
Wind Energ. Sci., 8, 1017–1027, https://doi.org/10.5194/wes-8-1017-2023, https://doi.org/10.5194/wes-8-1017-2023, 2023
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The paper presents a simple analytical model that, with surprisingly good accuracy, represents the loading for virtually any horizontal axis wind turbine, independent of size and operating regime. The aim of the model is to have a simple tool that may represent the loading of any wind turbine without having access to the details regarding the specific geometry and airfoil data, information that is normally kept confidential by the manufacturer of the turbine.
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.
Özge Sinem Özçakmak, Helge Aagaard Madsen, Niels Nørmark Sørensen, and Jens Nørkær Sørensen
Wind Energ. Sci., 5, 1487–1505, https://doi.org/10.5194/wes-5-1487-2020, https://doi.org/10.5194/wes-5-1487-2020, 2020
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Accurate prediction of the laminar-turbulent transition process is critical for design and prediction tools to be used in the industrial design process, particularly for the high Reynolds numbers experienced by modern wind turbines. Laminar-turbulent transition behavior of a wind turbine blade section is investigated in this study by means of field experiments and 3-D computational fluid dynamics (CFD) rotor simulations.
Cited articles
Arthur, R. S., Mirocha, J. D., Marjanovic, N., Hirth, B. D., Schroeder, J. L., Wharton, S., and Chow, F. K.: Multi-scale simulation of wind farm performance during a frontal passage, Atmosphere, 11, 245, https://doi.org/10.3390/atmos11030245, 2020. a
Bossuyt, J., Howland, M. F., Meneveau, C., and Meyers, J.: Wind tunnel study of the power output spectrum in a micro wind farm, J. Phys.: Conf. Ser., 753, 072002, https://doi.org/10.1088/1742-6596/753/7/072002, 2016.
a
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, 9–12 January 2012, Nashville, Tennessee, USA, p. 537, https://doi.org/10.2514/6.2012-537, 2012a. a
Churchfield, M. J., Lee, S., Michalakes, J., and Moriarty, P. J.: A numerical
study of the effects of atmospheric and wake turbulence on wind turbine
dynamics, J. Turbulence, 13, N14, https://doi.org/10.1080/14685248.2012.668191, 2012b. a, b, c
Englberger, A. and Dörnbrack, A.: Impact of the diurnal cycle of the
atmospheric boundary layer on wind-turbine wakes: a numerical modelling study, Bound.-Lay. Meteorol., 166, 423–448, 2018. a
Glauert, H.: Airplane propellers, in: Aerodynamic theory, Springer, 169–360, https://doi.org/10.1007/978-3-642-91487-4_3, 1935. a, b
Howland, M. F., Bossuyt, J., Martínez-Tossas, L. A., Meyers, J., and
Meneveau, C.: Wake structure in actuator disk models of wind turbines in yaw
under uniform inflow conditions, Journal of Renewable and Sustainable Energy,
8, 043301, https://doi.org/10.1063/1.4955091, 2016. a
Jha, P. K. and Schmitz, S.: Actuator curve embedding–an advanced actuator line model, J. Fluid Mech., 834, R2, https://doi.org/10.1017/jfm.2017.793, 2018. a, b
Jonkman, J., Butterfield, S., Musial, W., and Scott, G.: Definition of a 5-MW
reference wind turbine for offshore system development, Technical Report No. NREL/TP-500-38060, National Renewable Energy Laboratory, Golden, CO, https://doi.org/10.2172/947422, 2009. a
Marjanovic, N., Mirocha, J. D., Kosović, B., Lundquist, J. K., and Chow,
F. K.: Implementation of a generalized actuator line model for wind turbine
parameterization in the Weather Research and Forecasting model, J. Renew. Sustain. Energ., 9, 063308, https://doi.org/10.1063/1.4989443, 2017. 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, 9–12 January 2012, Nashville, Tennessee, USA, p. 900, https://doi.org/10.2514/6.2012-900, 2012. a, b, c, d
Munters, W., Meneveau, C., and Meyers, J.: Shifted periodic boundary conditions for simulations of wall-bounded turbulent flows, Phys. Fluids, 28,
025112, https://doi.org/10.1063/1.4941912, 2016. a
Nathan, J., Masson, C., Dufresne, L., and Churchfield, M. J.: Analysis of the
sweeped actuator line method, in: E3S Web of Conferences, vol. 5, National
NREL – Renewable Energy Lab., Golden, CO, USA, https://doi.org/10.1051/e3sconf/20150501001, 2015. a
Nathan, J., Forsting, A. R. M., 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
Nathan, J., Masson, C., and Dufresne, L.: Near-wake analysis of actuator line method immersed in turbulent flow using large-eddy simulations, Wind Energ. Sci., 3, 905–917, https://doi.org/10.5194/wes-3-905-2018, 2018. a
Navarro Diaz, G. P., Saulo, A. C., and Otero, A. D.: Full wind rose wind farm
simulation including wake and terrain effects for energy yield assessment,
Energy, 237, 121642, https://doi.org/10.1016/j.energy.2021.121642, 2021. a
NREL: SOWFA, GitHub [code], https://github.com/NREL/SOWFA/, last access: 21 March 2023. a
Ponta, F. L., Otero, A. D., Lago, L. I., and Rajan, A.: Effects of rotor
deformation in wind-turbine performance: the dynamic rotor deformation blade
element momentum model (DRD–BEM), Renew. Energy, 92, 157–170, 2016. a
Porté-Agel, F., Bastankhah, M., and Shamsoddin, S.: Wind-turbine and
wind-farm flows: a review, Bound.-Lay. Meteorol., 174, 1–59, 2020. a
Sanderse, B., Pijl, S., and Koren, B.: Review of computational fluid dynamics
for wind turbine wake aerodynamics, Wind Energy, 14, 799–819, 2011. 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, b
Sørensen, J. N. and Kock, C. W.: A model for unsteady rotor aerodynamics,
J. Wind Eng. Indust. Aerodynam., 58, 259–275, 1995. a
Sørensen, J. N. and Myken, A.: Unsteady actuator disc model for horizontal
axis wind turbines, J. Wind Eng. Indust. Aerodynam., 39, 139–149, 1992. a
Sørensen, J. N., Mikkelsen, R. F., 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
Stevens, R. J., Martínez-Tossas, L. A., and Meneveau, C.: Comparison of
wind farm large eddy simulations using actuator disk and actuator line models
with wind tunnel experiments, Renew. Energy, 116, 470–478, 2018. a
Stieren, A., Gadde, S. N., and Stevens, R. J.: Modeling dynamic wind direction changes in large eddy simulations of wind farms, Renew. Energy, 170, 1342–1352, 2021. a
van der Laan, M. P., Andersen, S. J., Réthoré, P. E., Baungaard, M., Sørensen, J. N., and Troldborg, N.: Faster wind farm AEP calculations with CFD using a generalized wind turbine model, J. Phys.: Conf.
Ser., 2265, 022030, https://doi.org/10.1088/1742-6596/2265/2/022030, 2022. a
Wang, J., Wang, C., Castañeda, O., Campagnolo, F., and Bottasso, C.:
Large-eddy simulation of scaled floating wind turbines in a boundary layer
wind tunnel, J. Phys.: Conf. Ser., 1037, 072032, https://doi.org/10.1088/1742-6596/1037/7/072032, 2018. a
Yoshizawa, A.: Statistical theory for compressible turbulent shear flows, with the application to subgrid modeling, Phys. Fluids, 29, 2152–2164, 1986. a
Zhong, W., Wang, T. G., Zhu, W. J., and Shen, W. Z.: Evaluation of Tip Loss
Corrections to AD/NS Simulations of Wind Turbine Aerodynamic Performance,
Appl. Sci., 9, 4919, https://doi.org/10.1063/1.865552, 2019. a
Short summary
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.
In this paper, the capacity to simulate transient wind turbine wake interaction problems using...
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