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Research on Size Optimization of Wave Energy Converters Based on a Floating Wind-Wave Combined Power Generation Platform

Author

Listed:
  • Xianxiong Zhang

    (Department of Engineering, Poly Changda Engineering Co., Ltd., Guangzhou 510620, China)

  • Bin Li

    (Department of Engineering, Poly Changda Engineering Co., Ltd., Guangzhou 510620, China)

  • Zhenwei Hu

    (Department of Engineering, Poly Changda Engineering Co., Ltd., Guangzhou 510620, China)

  • Jiang Deng

    (School of Naval Architecture, Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan 430063, China)

  • Panpan Xiao

    (School of Naval Architecture, Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan 430063, China)

  • Mingsheng Chen

    (School of Naval Architecture, Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan 430063, China
    Sanya Science and Education Innovation Park of Wuhan University of Technology, Sanya 572025, China)

Abstract

Wind energy and wave energy often co-exist in offshore waters, which have the potential and development advantages of combined utilization. Therefore, the combined utilization of wind and waves has become a research hotspot in the field of marine renewable energy. Against this background, this study analyses a novel integrated wind-wave power generation platform combining a semi-submersible floating wind turbine foundation and a point absorber wave energy converter (WEC), with emphasis on the size optimization of the WEC. Based on the engineering toolset software ANSYS-AQWA, numerical simulation is carried out to study the influence of different point absorber sizes on the hydrodynamic characteristics and wave energy conversion efficiency of the integrated power generation platform. The well-proven CFD software STAR CCM+ is used to modify the heaving viscosity damping of the point absorber to study the influence of fluid viscosity on the response of the point absorber. Based on this, the multi-body coupled time-domain model of the integrated power generation platform is established, and the performance of the integrated power generation platform is evaluated from two aspects, including the motion characteristics and wave energy conversion efficiency, which provides an important reference for the design and optimization of the floating wind-wave power generation platform.

Suggested Citation

  • Xianxiong Zhang & Bin Li & Zhenwei Hu & Jiang Deng & Panpan Xiao & Mingsheng Chen, 2022. "Research on Size Optimization of Wave Energy Converters Based on a Floating Wind-Wave Combined Power Generation Platform," Energies, MDPI, vol. 15(22), pages 1-16, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:22:p:8681-:d:977545
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    References listed on IDEAS

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    1. Gaspar, J.F. & Kamarlouei, M. & Thiebaut, F. & Guedes Soares, C., 2021. "Compensation of a hybrid platform dynamics using wave energy converters in different sea state conditions," Renewable Energy, Elsevier, vol. 177(C), pages 871-883.
    2. Hyebin Lee & Sunny Kumar Poguluri & Yoon Hyeok Bae, 2018. "Performance Analysis of Multiple Wave Energy Converters Placed on a Floating Platform in the Frequency Domain," Energies, MDPI, vol. 11(2), pages 1-14, February.
    3. Hu, Jianjian & Zhou, Binzhen & Vogel, Christopher & Liu, Pin & Willden, Richard & Sun, Ke & Zang, Jun & Geng, Jing & Jin, Peng & Cui, Lin & Jiang, Bo & Collu, Maurizio, 2020. "Optimal design and performance analysis of a hybrid system combing a floating wind platform and wave energy converters," Applied Energy, Elsevier, vol. 269(C).
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    Cited by:

    1. Yang, Yang & Shi, Zhaobin & Fu, Jianbin & Ma, Lu & Yu, Jie & Fang, Fang & Li, Chun & Chen, Shunhua & Yang, Wenxian, 2023. "Effects of tidal turbine number on the performance of a 10 MW-class semi-submersible integrated floating wind-current system," Energy, Elsevier, vol. 285(C).
    2. Neshat, Mehdi & Sergiienko, Nataliia Y. & Nezhad, Meysam Majidi & da Silva, Leandro S.P. & Amini, Erfan & Marsooli, Reza & Astiaso Garcia, Davide & Mirjalili, Seyedali, 2024. "Enhancing the performance of hybrid wave-wind energy systems through a fast and adaptive chaotic multi-objective swarm optimisation method," Applied Energy, Elsevier, vol. 362(C).

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