IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i7p3164-d1112854.html
   My bibliography  Save this article

Design and Optimization of Linear Permanent Magnet Vernier Generator for Direct Drive Wave Energy Converter

Author

Listed:
  • Mei Zhao

    (School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China)

  • Zhiquan Kong

    (School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China)

  • Pingpeng Tang

    (School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China)

  • Zhentao Zhang

    (State Grid Hangzhou Power Supply Company, Hangzhou 310000, China)

  • Guodong Yu

    (School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China)

  • Huaqiang Zhang

    (School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China)

  • Yongxiang Xu

    (School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China)

  • Jibin Zou

    (School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China)

Abstract

A novel linear permanent magnet vernier generator (LPMVG) for small-power off-grid wave power generation systems is proposed in this paper. Firstly, in order to reduce the cogging force and the inherent edge effect of the linear generator, a staggered tooth modular structure is proposed. Secondly, in order to improve the output power and efficiency of the LPMVG and reduce the fluctuation coefficient of electromagnetic force, the relationship between the parameters of the generator is studied, and a method combining multi-objective optimization and single parameter scanning based on the response surface model and particle swarm optimization algorithm is proposed to obtain the optimal structural parameters of the generator. Thirdly, the output power and efficiency of the optimized generator are calculated and analyzed based on the two-dimensional finite element method, and the effectiveness of the multi-objective optimization design method based on the response surface model and particle swarm optimization algorithm is verified. Finally, a prototype is developed, and the calculated results and the measured results are shown to be in good agreement.

Suggested Citation

  • Mei Zhao & Zhiquan Kong & Pingpeng Tang & Zhentao Zhang & Guodong Yu & Huaqiang Zhang & Yongxiang Xu & Jibin Zou, 2023. "Design and Optimization of Linear Permanent Magnet Vernier Generator for Direct Drive Wave Energy Converter," Energies, MDPI, vol. 16(7), pages 1-18, March.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:7:p:3164-:d:1112854
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/7/3164/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/7/3164/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ghaheri, Aghil & Afjei, Ebrahim & Torkaman, Hossein, 2022. "Design optimization of a novel linear transverse flux switching permanent magnet generator for direct drive wave energy conversion," Renewable Energy, Elsevier, vol. 198(C), pages 851-860.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chunyuan, Liu & Chen, Yi & Dong, Rui & Ye, Bao-Lin, 2023. "Optimization design of Tubular Permanent Magnet Linear Generator based on entropy model for wave energy conversion," Renewable Energy, Elsevier, vol. 216(C).
    2. Ganesh Mayilsamy & Kumarasamy Palanimuthu & Raghul Venkateswaran & Ruban Periyanayagam Antonysamy & Seong Ryong Lee & Dongran Song & Young Hoon Joo, 2023. "A Review of State Estimation Techniques for Grid-Connected PMSG-Based Wind Turbine Systems," Energies, MDPI, vol. 16(2), pages 1-27, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:7:p:3164-:d:1112854. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.