4.7 Article

A new coupled model for the equivalent roughness heights of wind farms

期刊

RENEWABLE ENERGY
卷 171, 期 -, 页码 34-46

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.renene.2021.02.076

关键词

Quasi-infinite wind farms; Equivalent roughness model; Large-eddy simulation; Wake layer

资金

  1. National Key Research and Development Program of China [2019YFE0104800]
  2. National Natural Science Foundation of China [11772128]
  3. Fundamental Research Funds for the Central Universities [2018ZD09]

向作者/读者索取更多资源

Accurate parameterization of wind farms' equivalent roughness heights is crucial for meso-scale climate simulations and wind power predictions. Existing models show sensitivity to sx/sy. Large-eddy simulations reveal differences in wind speed at rotor and hub height, particularly for wind farms with small s(x)/s(y).
Accurate parameterization of wind farms' equivalent roughness heights is critical to meso-scale climate simulations as well as power predictions of wind turbines. A notable inadequacy of the existing models is that the results sensitively depend on sx/sy, where sx and sy are the dimensionless streamwise and spanwise spacing of the turbines. To understand the issue, we conduct large-eddy simulations (LESs) for three types of quasi-infinite wind farms with moderate, large, and small s(x)/s(y). We find that the wind speed at the rotor is different from the horizontally averaged wind speed at the hub height, and this is particularly true for wind farms with small s(x)/s(y). This flow inhomogeneity at the hub height plays an important role in determining wind farms' equivalent roughness height but is often neglected in the existing models. Accounting for the flow inhomogeneity at the hub height, we propose a new coupled top-down/bottom-up model for the equivalent roughness heights of wind farms. Our model is compared with the existing models and our LESs. The results show that the proposed model is able to predict the equivalent roughness height of all types of wind farms irrespective of s(x)/s(y)'s value. (C) 2021 Elsevier Ltd. All rights reserved.

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