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Research Papers: Alternative Energy Sources

Wake Deflection in Long Distance From a Yawed Wind Turbine

[+] Author and Article Information
Yuta Uemura

Graduate School of Mechanical Engineering,
Tokyo University of Science,
6-3-1 Niijuku, Katsushika-ku,
Tokyo 125-8585, Japan
e-mail: yutti930116@gmail.com

Yasutada Tanabe

Japan Aerospace Exploration Agency (JAXA),
6-13-1 Osawa, Mitaka-shi,
Tokyo 181-0015, Japan
e-mail: tan@chofu.jaxa.jp

Hiroya Mamori

Department of Mechanical Engineering,
Tokyo University of Science,
6-3-1 Niijuku, Katsushika-ku,
Tokyo 125-8585, Japan
e-mail: mamori@rs.tus.ac.jp

Naoya Fukushima

Department of Mechanical Engineering,
Tokyo University of Science,
6-3-1 Niijuku, Katsushika-ku,
Tokyo 125-8585, Japan
e-mail: fukushima@rs.tus.ac.jp

Makoto Yamamoto

Department of Mechanical Engineering,
Tokyo University of Science,
6-3-1 Niijuku, Katsushika-ku,
Tokyo 125-8585, Japan
e-mail: yamamoto@rs.kagu.tus.ac.jp

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received October 8, 2016; final manuscript received March 16, 2017; published online May 16, 2017. Assoc. Editor: Ryo Amano.

J. Energy Resour. Technol 139(5), 051212 (May 16, 2017) (9 pages) Paper No: JERT-16-1398; doi: 10.1115/1.4036541 History: Received October 08, 2016; Revised March 16, 2017

Since it is important to prevent the wake produced by upstream wind turbines from interfering with downstream wind turbines, a method of deflecting such wakes is desired. In this paper, we present the coupled analysis results of a computational fluid dynamics (CFD) simulation involving a three-bladed rigid wind turbine with a yaw control system that utilizes rFlow3D CFD code, which was developed by the Japan Aerospace Exploration Agency (JAXA), primarily for rotorcraft use. Herein, a three-dimensional (3D), compressible, and unsteady Reynolds-averaged Navier–Stokes (RANS) equation with a Spalart–Allmaras turbulence model is adopted as the governing equation. In this study, wind turbine computations using various wind turbine yaw angles are performed while focusing on the resulting wake velocity distribution and aerodynamic loads, after which the influences of the yaw angle are discussed. Next, based on the wake velocity distribution results for each yaw angle, we move on to a wake interference avoidance simulation for downstream wind turbines that utilizes two prepared wind turbines. Through this study, the following characteristics were confirmed. The results show wake deflection produced by adding yaw angle can provide a sufficient wake skew angle even in far-wake events. Furthermore, the yaw angle introduction accelerates the progression of vortex dissipation and brings about early velocity recovery in the wake region. Simultaneously, the introduction decreases the power generation amount of the yawed upstream wind turbine and increases the fatigue load of flapwise moment added to the blade root. In this paper, the details of flow field, oscillation, and the yawed wind turbine performance characteristics will also be described.

Copyright © 2017 by ASME
Topics: Wakes , Wind turbines , Yaw , Blades
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References

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Figures

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Fig. 1

Schematic of a wind farm with a staggered arrangement

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Fig. 2

Schematic of overset grids: (a) bird's-eye view and (b) top view

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Fig. 3

Definition of yaw angle θY and wake skew angle θW

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Fig. 4

Schematic for yaw angle selection in first computational step (top view)

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Fig. 5

Power transition with yaw angle increase

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Fig. 6

EFL for each aerodynamic load

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Fig. 7

Difference between vortical structures for each yaw angle: (a) vortical structures and (b) vorticity distribution on the hub height plane

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Fig. 8

Comparison of blade tip vortex positions for each yaw angle

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Fig. 9

Difference between axial velocity distributions on the hub height plane for each yaw angle

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Fig. 10

Difference between axial velocity distributions at X = 3.0R for each yaw angle

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Fig. 11

Selection of yaw angle in second computational step: (a) axial velocity distributions on the hub height plane for each yaw angle, (b) positions of blade tip and root for downstream rotor, and (c) difference between axial velocity distributions at X = 7.0D for each yaw angle

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Fig. 12

Simulation for wake half-interference avoidance: (a) vortical structures and (b) vorticity distribution on the hub height plane

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Fig. 13

Relationship between wake stirring and vortex diffusion: (a) vorticity distribution and (b) Y directional velocity distribution

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Fig. 14

Reproduction of wake interference avoidance

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Fig. 15

Power transition with wake interference avoidance

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Fig. 16

EFLs for each computational step

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