Energies (Oct 2022)

Applicability of Wake Models to Predictions of Turbine-Induced Velocity Deficit and Wind Farm Power Generation

  • Dongqin Zhang,
  • Yang Liang,
  • Chao Li,
  • Yiqing Xiao,
  • Gang Hu

DOI
https://doi.org/10.3390/en15197431
Journal volume & issue
Vol. 15, no. 19
p. 7431

Abstract

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Turbine-induced velocity deficit is the main reason to reduce wind farm power generation and increase the fatigue loadings. It is meaningful to investigate turbine-induced wake structures by a simple and accurate method. In this study, a series of single turbine wake models are proposed by combining different spanwise distributions and wake boundary expansion models. It is found that several combined wake models with high hit rates are more accurate and universal. Subsequently, the wake models for multiple wind turbines are also investigated by considering the combined wake models for single turbine and proper superposition approaches. Several excellent plans are provided where the velocity, turbulence intensity, and wind power generation for multiple wind turbines can be accurately evaluated. Finally, effects of thrust coefficient and ambient turbulence intensity are studied. In summary, the combined wake models for both single and multiple wind turbines are proposed and validated, enhancing the precision of wind farm layout optimization will be helped by using these wake models.

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