Three-dimensional non-uniform full wake characteristics for yawed wind turbine with LiDAR-based experimental verification

Xiao-hong, Zhu; Chen, Yao; Xu, Shinai; Zhang, Shaohai; Gao, Xiaoxia; Sun, Haiying; Wang, Yu; Zhao, Fu; Lv, Tiancheng

doi:10.1016/j.energy.2023.126907

Cited by 9 publications

(4 citation statements)

References 44 publications

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“…The flow field environment of the field measurements is real and more credible, but the accuracy may be significantly affected by factors such as unstable wind field and poor monitoring environment, etc. Zhu Xiaoxun et al [23] conducted a field experiment based on Doppler radars at a wind farm in northern China. They analyzed the wake characteristics of the wind field combined with the SCADA data and investigated the velocity deficit at different distances.…”

Section: Introductionmentioning

confidence: 99%

Research on Evaluation Method of Wind Farm Wake Energy Efficiency Loss Based on SCADA Data Analysis

Ma,

Zhang,

Gao

et al. 2024

Sustainability

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The large size of wind turbines and wind farm clustering aggravate the effect of wake on output power, resulting in a reduction in the economic benefits of wind farms. This paper took the actual operating turbines of an onshore wind farm in China as the research object and analyzed the influence of wake on energy efficiency loss by combining SCADA data. The research established a complete loss assessment method and proposed the corresponding evaluation criteria. The results showed that typical wind turbines seriously affected by wake accounted for 32.8% of the wind farm. The actual output power was only 84.2% of the theoretical output power at the lowest month, and the wake loss of the wind farm is serious. The economic efficiency of the wind farm is lower in the summer months (June–August). The study can provide a theoretical basis for the arrangement of wind farms and the development of an operation control strategy.

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Section: Introductionmentioning

confidence: 99%

Research on Evaluation Method of Wind Farm Wake Energy Efficiency Loss Based on SCADA Data Analysis

Ma,

Zhang,

Gao

et al. 2024

Sustainability

Self Cite

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“…The model gives a specific expression for the wake expansion rate without the need for extensive experimental calculations to determine some empirical parameters. Subsequently, the 3DJG model was improved by Gao et al [25][26][27] considering the velocity distribution characteristics of the near wake, topographic effects, and yawing. Xu et al 28 combined the 3DJG model and OpenFAST to investigate the effect of upstream wind turbine location on the aerodynamic performance of downstream wind turbines.…”

Section: Introductionmentioning

confidence: 99%

“…Xu et al 28 combined the 3DJG model and OpenFAST to investigate the effect of upstream wind turbine location on the aerodynamic performance of downstream wind turbines. In addition, by correcting for the effect of wind shear using the same method as Gao et al, [24][25][26][27] we 29 propose a 3D polynomial-shaped wake model by considering the anisotropic expansion of the wake boundary.…”

Section: Introductionmentioning

confidence: 99%

A three‐dimensional analytical model based on Gaussian distribution for wind‐turbine wakes

Ling,

Zhao,

Liu

et al. 2023

Env Prog and Sustain Energy

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A Gaussian‐shaped, three‐dimensional (3DG‐k) wake model is proposed considering the shear wind effect. The model defines the wake radius rw to be equal to twice the Gaussian standard deviation σ and establishes a link with the expansion coefficient k of the physical wake boundary to describe the wake boundary. Garrad Hassan (GH) wind tunnel test data, Shiren wind farm measurement data, Nibe wind farm measurement data, and Vestas V80‐2MW wind turbine computational data by large eddy simulation method are used to validate the accuracy of the 3DG‐k, Jensen, 3D Gaussian (3DG), and 3D cosine (3D‐C) models. Results show that the 3DG‐k model exhibits higher accuracy for the four cases compared to other models. Due to its simplicity and universality, the model can be used for layout optimization and wake control of wind farms.

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“…The deflection of wake was described by a semiempirical formula. Zhu et al [37] conducted a field wake measurement using LiDAR and established a three-dimensional non-uniform wake model. Its results show that the model agrees well with experimental data.…”

Section: Introductionmentioning

confidence: 99%

Study on Complex Wake Characteristics of Yawed Wind Turbine Using Actuator Line Method

Wang

Zhou

Cai

et al. 2023

JMSE

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In modern large-scale wind farms, power loss caused by the wake effect is more than 30%, and active yaw control can greatly reduce the influence of the wake effect by deflecting the wind turbine’s wake. The yawed wind turbine’s wake characteristics are complex, and a deep comprehension of a yawed turbine’s wake is necessary. The actuator line method combined with URANS (unsteady Reynold-averaged Navier–Stokes equations) is used to study the yawed wind turbine’s wake characteristics in this paper. Compared with an un-yawed wind turbine, a yawed one has two main characteristics, deflection and deformation. With an increasing yaw angle, turbine wake shows an increasing deflection. The results indicated that deflection at different height was different, the wake profile showed the biggest deflection at about the hub height, while the smallest deflection existed at the top and bottom of the yawed turbine’s wake. This can be visually demonstrated by the evolution of a kidney-shape velocity distribution at the vertical cross-section. Two-dimensional and three-dimensional presentations of velocity deficit distributions are presented in this paper. The evolution of an irregular kidney-shape distribution is discussed in this paper. It is formed by the momentum exchange caused by the counter-rotating vortex pair. The results indicated that the counter-rotating vortex pair was composed of the streamwise vortex flux brought by the tip vortex. Furthermore, when the wind turbine rotated clockwise and yawed clockwise, the negative vorticity of counter-rotating vortex first appeared in the upper left position.

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Three-dimensional non-uniform full wake characteristics for yawed wind turbine with LiDAR-based experimental verification

Cited by 9 publications

References 44 publications

Research on Evaluation Method of Wind Farm Wake Energy Efficiency Loss Based on SCADA Data Analysis

Research on Evaluation Method of Wind Farm Wake Energy Efficiency Loss Based on SCADA Data Analysis

A three‐dimensional analytical model based on Gaussian distribution for wind‐turbine wakes

Study on Complex Wake Characteristics of Yawed Wind Turbine Using Actuator Line Method

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