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Numerical Simulations of a VAWT in the Wake of a Moving Car

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  • Wenlong Tian

    (School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, 710072, China
    Key Laboratory for Unmanned Underwater Vehicle, Northwestern Polytechnical University, Xi’an, 710072, China)

  • Zhaoyong Mao

    (School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, 710072, China
    Key Laboratory for Unmanned Underwater Vehicle, Northwestern Polytechnical University, Xi’an, 710072, China)

  • Yukai Li

    (School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, 710072, China)

Abstract

Wind energy generated from the wake of moving cars has a large energy potential that has not yet been utilized. In this study, a vertical axis wind turbine (VAWT) was used to recover energy from the wakes of moving cars. The turbine was designed to be planted by the side of the car lane and driven by the wake produced by the car. Transient computational fluid dynamics (CFD) simulations were performed to evaluate the performance of the VAWT. The influence of two main factors on the performance of the VAWT, the velocity of the car and the gap between the car and the rotor, were studied. The simulations confirmed the feasibility of this plan, and in the tested cases, the VAWT was able to generate a maximum energy output of 100.49 J from the wake of a car. The results also showed that the performance of the VAWT decreased with the velocity of the car, and the increased gap between the car and the VAWT.

Suggested Citation

  • Wenlong Tian & Zhaoyong Mao & Yukai Li, 2017. "Numerical Simulations of a VAWT in the Wake of a Moving Car," Energies, MDPI, vol. 10(4), pages 1-14, April.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:4:p:478-:d:94862
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    References listed on IDEAS

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    6. Wenlong Tian & Baowei Song & James H. VanZwieten & Parakram Pyakurel, 2015. "Computational Fluid Dynamics Prediction of a Modified Savonius Wind Turbine with Novel Blade Shapes," Energies, MDPI, vol. 8(8), pages 1-15, July.
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    Cited by:

    1. Wenlong Tian & Zhaoyong Mao & Fuliang Zhao & Zhicao Zhao, 2017. "Layout Optimization of Two Autonomous Underwater Vehicles for Drag Reduction with a Combined CFD and Neural Network Method," Complexity, Hindawi, vol. 2017, pages 1-15, December.
    2. Guo, Fen & Song, Baowei & Mao, Zhaoyong & Tian, Wenlong, 2020. "Experimental and numerical validation of the influence on Savonius turbine caused by rear deflector," Energy, Elsevier, vol. 196(C).
    3. Zahra Sefidgar & Amir Ahmadi Joneidi & Ahmad Arabkoohsar, 2023. "A Comprehensive Review on Development and Applications of Cross-Flow Wind Turbines," Sustainability, MDPI, vol. 15(5), pages 1-39, March.

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