The Mean Velocity of the Near-Field of a Lab-Scale Wind Turbine in Tailored Turbulent Shear Flows

Li, Leon; Hearst, R. Jason; Ganapathisubramani, Bharathram

doi:10.1007/978-3-030-22196-6_50

Cited by 1 publication

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“…A new model based on a local acceleration factor and a simulated wind turbine wake velocity calculation was proposed. The above wake model for complex terrain does not take into account the wind shear effect, and the influence of the wind shear effect on the wake distribution cannot be ignored [26][27][28], especially in the vertical wake distribution. In order to solve this problem, Gao et al [29] introduced the Coanda effect into the wake model, considered the effect of wind shear, modified the wind speed distribution in the vertical direction, and proposed a complex terrain wake model suitable for the far wake region.…”

Section: Introductionmentioning

confidence: 99%

Derivation and Verification of Gaussian Terrain Wake Model Based on Wind Field Experiment

et al. 2022

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Aiming at the problem where the current engineering wake model does not describe the wind speed distribution of the wake in the complex terrain wind farm completely, based on the three-dimensional full wake model (3DJGF wake model), this paper proposed a wake model that can predict the three-dimensional wind speed distribution of the entire wake region in the complex wind farm, taking into account the Coanda effect, wind shear effect, and wake subsidence under the Gaussian terrain. Two types of Doppler lidar were used to conduct wind field experiments, and the inflow wind profile and three-dimensional expansion of the wake downstream of the wind turbine on the Gaussian terrain were measured. The experimental results showed that the wake centerline and terrain curve showed similar variation characteristics, and the near wake profile was similar to a super-Gaussian shape (asymmetric super-Gaussian shape) under low-wind-speed conditions, while the near wake profile presented a bimodal shape (asymmetric bimodal shape) under high-wind-speed conditions. The predicted profiles of the Gaussian terrain wake model were compared with the experimental data and the three typical wake models. The comparison results showed that the newly proposed Gaussian terrain wake model fit well with the experimental data in both near wake and far wake regions, and it had better performance in predicting the wake speed of the Gaussian terrain wind farm than the other three wake models. It can effectively predict the three-dimensional velocity distribution in the whole wake region of complex terrain.

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