Wind Energy Science
Wind Energy Science
WES
Articles | Volume 8, issue 2
Articles | Volume 8, issue 2
https://doi.org/10.5194/wes-8-141-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-8-141-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 8, issue 2
Brief communication
 | 
08 Feb 2023
Brief communication |  | 08 Feb 2023

Brief communication: A momentum-conserving superposition method applied to the super-Gaussian wind turbine wake model

Frédéric Blondel

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Cited articles

Bastankhah, M., Welch, B. L., Martínez-Tossas, L. A., King, J., and Fleming, P.: Analytical solution for the cumulative wake of wind turbines in wind farms, J. Fluid Mech., 911, A53, https://doi.org/10.1017/jfm.2020.1037, 2021. a, b, c, d, e, f, g, h, i, j, k, l, m, n
Bay, C. J., Fleming, P., Doekemeijer, B., King, J., Churchfield, M., and Mudafort, R.: Addressing deep array effects and impacts to wake steering with the cumulative-curl wake model, Wind Energ. Sci. Discuss. [preprint], https://doi.org/10.5194/wes-2022-17, in review, 2022. a, b, c, d
Blondel, F. and Cathelain, M.: An alternative form of the super-Gaussian wind turbine wake model, Wind Energ. Sci., 5, 1225–1236, https://doi.org/10.5194/wes-5-1225-2020, 2020. a, b, c
Branlard, E. and Meyer Forsting, A. R.: Assessing the blockage effect of wind turbines and wind farms using an analytical vortex model, Wind Energy, 23, 2068–2086, https://doi.org/10.1002/we.2546, 2020. a
Cathelain, M., Blondel, F., Joulin, P., and Bozonnet, P.: Calibration of a super-Gaussian wake model with a focus on near-wake characteristics, J. Phys.: Conf. Ser., 1618, 062008, https://doi.org/10.1088/1742-6596/1618/6/062008, 2020. a, b, c
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Accurate wind farm flow predictions based on analytical wake models are crucial for wind farm design and layout optimization. Wake superposition methods play a key role and remain a substantial source of uncertainty. In the present work, a momentum-conserving superposition method is extended to the superposition of super-Gaussian-type velocity deficit models, allowing the full wake velocity deficit estimation and design of closely packed wind farms.
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