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New engineering wake model for wind farm applications

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  • Lin, Jian Wei
  • Zhu, Wei Jun
  • Shen, Wen Zhong

Abstract

Engineering wake model is widely used in today's wind farm design because of its fast performance. In the literature, there were good developments in the track of engineering wake models. However, its accuracy is still not ideal. In this paper, two novel analytical wake models (one uses a Gaussian shape and the other uses a cosine shape) are developed to predict the wind velocity distribution in the wake region of a wind turbine by applying the momentum and mass conservation laws. Next, the two models are validated using published experimental data and large-eddy simulation (LES) data, and also compared to the analytical wake model of Ishihara and Qian which is considered to be the state-of-the-art engineering wake model in the literature. In all considered cases, the relative errors between the new models and experimental or LES data are much lower than those between the Ishihara and Qian model and experimental or LES data. From the comparisons, it is also seen that the new model with a Gaussian shape is slightly better in far-field wake prediction in most cases while the new model with a cosine shape is slightly better in a few cases. Because of their good performance, these two models are recommended in wind farm design including both wind farm layout optimization and wind farm control.

Suggested Citation

  • Lin, Jian Wei & Zhu, Wei Jun & Shen, Wen Zhong, 2022. "New engineering wake model for wind farm applications," Renewable Energy, Elsevier, vol. 198(C), pages 1354-1363.
    • Handle: RePEc:eee:renene:v:198:y:2022:i:c:p:1354-1363
    DOI: 10.1016/j.renene.2022.08.116
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    References listed on IDEAS

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    Cited by:

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    2. Zhiwen Deng & Chang Xu & Zhihong Huo & Xingxing Han & Feifei Xue, 2023. "Yaw Optimisation for Wind Farm Production Maximisation Based on a Dynamic Wake Model," Energies, MDPI, vol. 16(9), pages 1-20, May.
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