Abstract

Increasing wind power generation has been introduced into power systems to meet the renewable energy targets in power generation. The output efficiency and output power stability are of great importance for wind turbines to be integrated into power systems. The wake effect influences the power generation efficiency and stability of wind turbines. However, few studies consider comprehensive corrections in an aerodynamic model and a turbulence model, which challenges the calculation accuracy of the velocity field and turbulence field in the wind turbine wake model, thus affecting wind power integration into power systems. To tackle this challenge, this paper proposes a modified Reynolds-averaged Navier–Stokes (MRANS)-based wind turbine wake model to simulate the wake effects. Our main aim is to add correction modules in a 3D aerodynamic model and a shear-stress transport (SST) k-ω turbulence model, which are converted into a volume source term and a Reynolds stress term for the MRANS-based wake model, respectively. A correction module including blade tip loss, hub loss, and attack angle deviation is considered in the 3D aerodynamic model, which is established by blade element momentum aerodynamic theory and an improved Cauchy fuzzy distribution. Meanwhile, another correction module, including a hold source term, regulating parameters and reducing the dissipation term, is added into the SST k-ω turbulence model. Furthermore, a structured hexahedron mesh with variable size is developed to significantly improve computational efficiency and make results smoother. Simulation results of the velocity field and turbulent field with the proposed approach are consistent with the data of real wind turbines, which verifies the effectiveness of the proposed approach. The variation law of the expansion effect and the double-hump effect are also given.

Highlights

  • In the wake region of a wind turbine, the energy absorption rate of the wind turbine is decreased and the fatigue load is increased due to the decreasing wind speed and increasing intensity of Energies 2020, 13, 4430; doi:10.3390/en13174430 www.mdpi.com/journal/energiesEnergies 2020, 13, x FOR PEER REVIEW turbulence [1,2,3]

  • The accuracy of the turbulence intensity distribution is improved by correcting the closure constant and the dissipation term

  • Simulation results of the velocity field and turbulent field with the proposed approach are consistent with the data of real wind turbines, which verifies the effectiveness of the proposed approach

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Summary

Introduction

In the wake region of a wind turbine, the energy absorption rate of the wind turbine is decreased and the fatigue load is increased due to the decreasing wind speed and increasing intensity of Energies 2020, 13, 4430; doi:10.3390/en13174430 www.mdpi.com/journal/energies. The advantages and disadvantages of research on wind turbine wake models are method [17,18,19]. Concerning LES, a full-scale 3D wind turbine model by using sliding tetrahedron mesh is established to calculate the wakes in the rotor diameter range of 20 times [24]. An improved k-ε turbulence model is presented for the numerical simulation of wind turbine wakes. Motivated by the above discussion, the velocity field and turbulence field of wind turbines are simulated by a modified RANS (MRANS) method in this paper. This paper proposes a modified Reynolds-averaged Navier–Stokes (MRANS)-based wind turbine wake model to simulate the wake effects. The rest of this paper is organized as follows: Section 2 describes the overall proposed wind turbine wake model.

Overall Wind Turbine Wake Model
BEM-Fuzzy 3D Aerodynamic Model
D r nb Vr c
Hub Loss Correction
Attack Angle Correction
L l if l L
SST k-ω Turbulence Model
Hold Source Term
Closure Constant Correction
Correction Factor Addition
Mesh Partition Method
With is imported to the Ansys
Simulation Setup
Simulation
Comparison and Analysis of Velocity Field Results at the Center Axis
Velocity
Correction
Velocity at Different Altitudes
Turbulence Field Result under the Uniform Inflow Condition
Result under under the the Uniform
ComputationAverage
Conclusions
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