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Numerical Analysis of the Dynamic Interaction between Two Closely Spaced Vertical-Axis Wind Turbines

Author

Listed:
  • Yutaka Hara

    (Faculty of Engineering, Tottori University, 4-101 Koyama-Minami, Tottori 680-8552, Japan)

  • Yoshifumi Jodai

    (Department of Mechanical Engineering, Kagawa National Institute of Technology (KOSEN), Kagawa College, 355 Chokushi, Takamatsu 761-8058, Japan)

  • Tomoyuki Okinaga

    (Graduate School of Engineering, Tottori University, 4-101 Koyama-Minami, Tottori 680-8552, Japan)

  • Masaru Furukawa

    (Faculty of Engineering, Tottori University, 4-101 Koyama-Minami, Tottori 680-8552, Japan)

Abstract

To investigate the optimum layouts of small vertical-axis wind turbines, a two-dimensional analysis of dynamic fluid body interaction is performed via computational fluid dynamics for a rotor pair in various configurations. The rotational speed of each turbine rotor (diameter: D = 50 mm) varies based on the equation of motion. First, the dependence of rotor performance on the gap distance ( gap ) between two rotors is investigated. For parallel layouts, counter-down (CD) layouts with blades moving downwind in the gap region yield a higher mean power than counter-up (CU) layouts with blades moving upwind in the gap region. CD layouts with gap / D = 0.5–1.0 yield a maximum average power that is 23% higher than that of an isolated single rotor. Assuming isotropic bidirectional wind speed, co-rotating (CO) layouts with the same rotational direction are superior to the combination of CD and CU layouts regardless of the gap distance. For tandem layouts, the inverse-rotation (IR) configuration shows an earlier wake recovery than the CO configuration. For 16-wind-direction layouts, both the IR and CO configurations indicate similar power distribution at gap / D = 2.0. For the first time, this study demonstrates the phase synchronization of two rotors via numerical simulation.

Suggested Citation

  • Yutaka Hara & Yoshifumi Jodai & Tomoyuki Okinaga & Masaru Furukawa, 2021. "Numerical Analysis of the Dynamic Interaction between Two Closely Spaced Vertical-Axis Wind Turbines," Energies, MDPI, vol. 14(8), pages 1-23, April.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:8:p:2286-:d:538862
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    References listed on IDEAS

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    1. Zanforlin, Stefania & Nishino, Takafumi, 2016. "Fluid dynamic mechanisms of enhanced power generation by closely spaced vertical axis wind turbines," Renewable Energy, Elsevier, vol. 99(C), pages 1213-1226.
    2. Chen, Wei-Hsin & Chen, Ching-Ying & Huang, Chun-Yen & Hwang, Chii-Jong, 2017. "Power output analysis and optimization of two straight-bladed vertical-axis wind turbines," Applied Energy, Elsevier, vol. 185(P1), pages 223-232.
    3. Göçmen, Tuhfe & Laan, Paul van der & Réthoré, Pierre-Elouan & Diaz, Alfredo Peña & Larsen, Gunner Chr. & Ott, Søren, 2016. "Wind turbine wake models developed at the technical university of Denmark: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 752-769.
    4. Zhenzhou Shao & Ying Wu & Li Li & Shuang Han & Yongqian Liu, 2019. "Multiple Wind Turbine Wakes Modeling Considering the Faster Wake Recovery in Overlapped Wakes," Energies, MDPI, vol. 12(4), pages 1-14, February.
    5. Poguluri, Sunny Kumar & Lee, Hyebin & Bae, Yoon Hyeok, 2021. "An investigation on the aerodynamic performance of a co-axial contra-rotating vertical-axis wind turbine," Energy, Elsevier, vol. 219(C).
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    Cited by:

    1. Yoshifumi Jodai & Yutaka Hara, 2021. "Wind Tunnel Experiments on Interaction between Two Closely Spaced Vertical-Axis Wind Turbines in Side-by-Side Arrangement," Energies, MDPI, vol. 14(23), pages 1-19, November.
    2. Lin Pan & Ze Zhu & Haodong Xiao & Leichong Wang, 2021. "Numerical Analysis and Parameter Optimization of J-Shaped Blade on Offshore Vertical Axis Wind Turbine," Energies, MDPI, vol. 14(19), pages 1-29, October.
    3. Masaru Furukawa & Yutaka Hara & Yoshifumi Jodai, 2022. "Analytical Model for Phase Synchronization of a Pair of Vertical-Axis Wind Turbines," Energies, MDPI, vol. 15(11), pages 1-19, June.
    4. Jirarote Buranarote & Yutaka Hara & Masaru Furukawa & Yoshifumi Jodai, 2022. "Method to Predict Outputs of Two-Dimensional VAWT Rotors by Using Wake Model Mimicking the CFD-Created Flow Field," Energies, MDPI, vol. 15(14), pages 1-29, July.
    5. Yoshifumi Jodai & Yutaka Hara, 2023. "Wind-Tunnel Experiments on the Interactions among a Pair/Trio of Closely Spaced Vertical-Axis Wind Turbines," Energies, MDPI, vol. 16(3), pages 1-27, January.
    6. Chloë Dorge & Eric Louis Bibeau, 2023. "Deep Learning-Based Prediction of Unsteady Reynolds-Averaged Navier-Stokes Solutions for Vertical-Axis Turbines," Energies, MDPI, vol. 16(3), pages 1-33, January.
    7. Ji Hao Zhang & Fue-Sang Lien & Eugene Yee, 2022. "Investigations of Vertical-Axis Wind-Turbine Group Synergy Using an Actuator Line Model," Energies, MDPI, vol. 15(17), pages 1-22, August.

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