IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i16p5986-d891673.html
   My bibliography  Save this article

Cooling Techniques in Direct-Drive Generators for Wind Power Application

Author

Listed:
  • Petrica Taras

    (Department of Electronic and Electrical Engineering, The University of Sheffield, Sheffield S1 3JD, UK)

  • Reza Nilifard

    (Siemens Gamesa Renewable Energy A/S, P.O. Box 7330 Brande, Denmark)

  • Zi-Qiang Zhu

    (Department of Electronic and Electrical Engineering, The University of Sheffield, Sheffield S1 3JD, UK
    Sheffield Siemens Gamesa Renewable Energy Research Centre, Sheffield S3 7HQ, UK)

  • Ziad Azar

    (Sheffield Siemens Gamesa Renewable Energy Research Centre, Sheffield S3 7HQ, UK)

Abstract

Direct-drive generators are an attractive candidate for wind power application since they do not need a gearbox, thus increasing operational reliability and reducing power losses. However, this is achieved at the cost of an increased generator size, larger inverter and decreased thermal performance. The associated cooling system is therefore crucial to keep the generator and inverter sizes down and to operate within the safe thermal limits. Various cooling techniques suitable for generators are therefore reviewed and analyzed in this paper. The performance and maintenance requirements are unavoidable compromises that need to be investigated together, especially for large generators. The location of the wind turbine is also important and dictates critical issues such as accessibility and maximum size. The key novelty in this paper is the assessment of the cooling methods based on generator size, reliability and maintenance requirements.

Suggested Citation

  • Petrica Taras & Reza Nilifard & Zi-Qiang Zhu & Ziad Azar, 2022. "Cooling Techniques in Direct-Drive Generators for Wind Power Application," Energies, MDPI, vol. 15(16), pages 1-29, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:16:p:5986-:d:891673
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/16/5986/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/16/5986/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nerg, Janne & Ruuskanen, Vesa, 2013. "Lumped-parameter-based thermal analysis of a doubly radial forced-air-cooled direct-driven permanent magnet wind generator," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 90(C), pages 218-229.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zi-Qiang Zhu & Dawei Liang, 2022. "Perspective of Thermal Analysis and Management for Permanent Magnet Machines, with Particular Reference to Hotspot Temperatures," Energies, MDPI, vol. 15(21), pages 1-51, November.
    2. Farid Khazaeli Moghadam & Nils Desch, 2023. "Life Cycle Assessment of Various PMSG-Based Drivetrain Concepts for 15 MW Offshore Wind Turbines Applications," Energies, MDPI, vol. 16(3), pages 1-26, February.
    3. Dongmyoung Kim & Taesu Jeon & Insu Paek & Wirachai Roynarin & Boonyang Plangklang & Bayasgalan Dugarjav, 2023. "A Study on the Improved Power Control Algorithm for a 100 kW Wind Turbine," Energies, MDPI, vol. 16(2), pages 1-15, January.
    4. Małgorzata Jastrzębska, 2022. "Installation’s Conception in the Field of Renewable Energy Sources for the Needs of the Silesian Botanical Garden," Energies, MDPI, vol. 15(18), pages 1-28, September.

    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. Ouagued, Sofiane & Amara, Yacine & Barakat, Georges, 2016. "Comparison of hybrid analytical modelling and reluctance network modelling for pre-design purposes," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 130(C), pages 3-21.
    2. Hoang, Trung-Kien & Vido, Lionel & Gillon, Frederic & Gabsi, Mohamed, 2019. "Structural optimization to maximize the flux control range of a double excitation synchronous machine," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 158(C), pages 235-247.
    3. Ping Jiang & Tianyi Zhang & Jinpeng Geng & Peiguang Wang & Lei Fu, 2023. "An MPPT Strategy for Wind Turbines Combining Feedback Linearization and Model Predictive Control," Energies, MDPI, vol. 16(10), pages 1-16, May.
    4. Payam Shams Ghahfarokhi & Andrejs Podgornovs & Ants Kallaste & Antonio J. Marques Cardoso & Anouar Belahcen & Toomas Vaimann & Oleg Kudrjavtsev & Bilal Asad & Muhammad Naveed Iqbal, 2022. "Steady-State Thermal Modeling of Salient Pole Synchronous Generator," Energies, MDPI, vol. 15(24), pages 1-15, December.

    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:15:y:2022:i:16:p:5986-:d:891673. 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.