IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i12p3076-d1676289.html
   My bibliography  Save this article

A Study on the Optimal Configuration of Offshore Substation Transformers

Author

Listed:
  • Byeonghyeon An

    (Department of Electrical Engineering, Mokpo National University, Muan 58554, Republic of Korea)

  • Jeongsik Oh

    (Department of Electrical Engineering, Mokpo National University, Muan 58554, Republic of Korea)

  • Taesik Park

    (Department of Electrical Engineering, Mokpo National University, Muan 58554, Republic of Korea)

Abstract

The growing scale of offshore wind farms and increasing transmission distances has driven the demand for optimized offshore substation (OSS) configurations. This study proposes a comprehensive techno-economic framework to minimize the total lifecycle cost (LCC) of an OSS by determining the optimal number of OSSs and transformers considering wind farm capacity and transmission distance. The methodology incorporates three cost models: capital expenditure (CAPEX), operational expenditure (OPEX), and expected energy not supplied (EENS). CAPEX considers transformer costs, topside structural mass effects, and nonlinear installation costs. OPEX accounts for substation maintenance and vessel operating expenses, and EENS is calculated using transformer failure probability models and redundancy configurations. The optimization is performed through scenario-based simulations and a net present value (NPV)-based comparative analysis to determine the cost-effective configurations. The quantitative analysis demonstrates that for small- to medium-scale wind farms (500–1000 MW), configurations using 1–2 substations and 3–4 transformers achieve minimal LCC regardless of the transmission distance. In contrast, large-scale wind farms (≥1500 MW) require additional substations to mitigate transmission losses and disruption risks, particularly over long distances. These results demonstrate that OSS design should holistically balance initial investment costs, operational reliability, and supply security, providing practical insights for cost-effective planning of next-generation offshore wind projects.

Suggested Citation

  • Byeonghyeon An & Jeongsik Oh & Taesik Park, 2025. "A Study on the Optimal Configuration of Offshore Substation Transformers," Energies, MDPI, vol. 18(12), pages 1-23, June.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:12:p:3076-:d:1676289
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/12/3076/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/18/12/3076/
    Download Restriction: no
    ---><---

    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:18:y:2025:i:12:p:3076-:d:1676289. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.