IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i4p1702-d1593968.html
   My bibliography  Save this article

Adaptive Grey-Box Modelling for Energy-Efficient Building Retrofits: Case Studies in Denmark

Author

Listed:
  • Yujie Yang

    (Center for Energy Informatics, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark)

  • Muhyiddine Jradi

    (Center for Energy Informatics, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark)

Abstract

Optimizing energy efficiency in existing buildings can yield substantial savings, though collecting the necessary data for energy modelling often poses challenges. This study developed a flexible, room-level framework for evaluating retrofit strategies using simplified energy models. The approach, based on the RC model, estimated parameters from readily available data such as solar radiation, indoor and outdoor temperatures, and heating system characteristics. The model was validated through case studies of an office and a daycare room in Denmark, guiding energy retrofit decisions. Results showed that adding roof insulation provided greater energy savings compared to wall insulation. A multi-objective optimization was employed to balance energy efficiency and thermal comfort, achieving a 6.58% reduction in energy demand during January while maintaining occupant comfort for 744 h. This framework not only facilitates building–energy retrofitting but also supports the development of digital twins and operational optimization, improving both energy performance and indoor environmental quality.

Suggested Citation

  • Yujie Yang & Muhyiddine Jradi, 2025. "Adaptive Grey-Box Modelling for Energy-Efficient Building Retrofits: Case Studies in Denmark," Sustainability, MDPI, vol. 17(4), pages 1-26, February.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:4:p:1702-:d:1593968
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/4/1702/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/4/1702/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Huang, Tao & Bacher, Peder & Møller, Jan Kloppenborg & D’Ettorre, Francesco & Markussen, Wiebke Brix, 2023. "A step towards digital operations—A novel grey-box approach for modelling the heat dynamics of ultra-low temperature freezing chambers," Applied Energy, Elsevier, vol. 349(C).
    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.

      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:jsusta:v:17:y:2025:i:4:p:1702-:d:1593968. 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.