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Semi-Empirical Model Based on the Influence of Turbulence Intensity on the Wake of Vertical Axis Turbines

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  • Ziyao Wang

    (National Ocean Technology Center, Tianjin 300110, China)

  • Erhu Hou

    (National Ocean Technology Center, Tianjin 300110, China)

  • He Wu

    (National Ocean Technology Center, Tianjin 300110, China)

Abstract

In the context of energy shortages and the development of new energy sources, tidal current energy has emerged as a promising alternative. It is typically harnessed by deploying arrays of multiple water turbines offshore. Vertical axis water turbines (VAWTs), as key units in these arrays, have wake effects that influence array spacing and energy efficiency. However, existing studies on wake velocity distribution models for VAWTs are limited in number, accuracy, and consideration of influencing factors. A precise theoretical model (Lam’s formula) for wake lateral velocity can better predict wake decay, aiding in the optimization of tidal current energy array designs. Turbulence in the ocean, serving as a medium for energy exchange between high-energy and low-energy water flows, significantly impacts the wake recovery of water turbines. To simplify the problem, this study uses software ANSYS Fluent 2020 R2 for two-dimensional simulations of VAWT wake decay under different turbulence intensities, confirming the critical role of turbulence intensity in wake velocity decay. Based on the obtained data, a new mathematical approach was employed to incorporate turbulence intensity into Lam’s wake formula for VAWTs, improving its predictive accuracy with a minimum error of 1%, and refining some parameter calculations. The results show that this model effectively reflects the impact of turbulence on VAWT wake recovery and can be used to predict wake decay under various turbulence conditions, providing a theoretical basis for VAWT design, optimization, and array layout.

Suggested Citation

  • Ziyao Wang & Erhu Hou & He Wu, 2024. "Semi-Empirical Model Based on the Influence of Turbulence Intensity on the Wake of Vertical Axis Turbines," Energies, MDPI, vol. 17(18), pages 1-17, September.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:18:p:4535-:d:1474792
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    References listed on IDEAS

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    1. Lo Brutto, Ottavio A. & Nguyen, Van Thinh & Guillou, Sylvain S. & Thiébot, Jérôme & Gualous, Hamid, 2016. "Tidal farm analysis using an analytical model for the flow velocity prediction in the wake of a tidal turbine with small diameter to depth ratio," Renewable Energy, Elsevier, vol. 99(C), pages 347-359.
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