IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i10p6000-d816105.html
   My bibliography  Save this article

Development of Simplified Building Energy Prediction Model to Support Policymaking in South Korea—Case Study for Office Buildings

Author

Listed:
  • Jaewan Joe

    (Department of Architectural Engineering, Inha University, Incheon 22212, Korea)

  • Seunghyeon Min

    (Department of Architectural Engineering, Inha University, Incheon 22212, Korea)

  • Seunghwan Oh

    (Department of Architectural Engineering, Inha University, Incheon 22212, Korea)

  • Byungwoo Jung

    (Department of Architectural Engineering, Inha University, Incheon 22212, Korea)

  • Yu Min Kim

    (Korea Institute of Civil Engineering and Building Technology, Ilsan 10223, Korea)

  • Deuk Woo Kim

    (Korea Institute of Civil Engineering and Building Technology, Ilsan 10223, Korea)

  • Seung Eon Lee

    (Korea Institute of Civil Engineering and Building Technology, Ilsan 10223, Korea)

  • Dong Hyuk Yi

    (Korea Testing Laboratory, Jinju 52852, Korea)

Abstract

This study aims to support building energy policymaking for office buildings in South Korea through regression models by considering the global temperature rise. The key variables representing building energy standards and codes are selected, and their impact on the annual energy consumption is simulated using EnergyPlus reference models. Then, simplified regression models are built on the basis of the annual energy consumption using the selected variables. The prediction performance of the developed model for forecasting the annual energy consumption of each reference building is good, and the prediction error is negligible. An additional global coefficient is estimated to address the impact of increased outdoor air temperature in the future. The final model shows fair prediction performance with global coefficients of 1.27 and 0.9 for cooling and heating, respectively. It is expected that the proposed simplified model can be leveraged by non-expert policymakers to predict building energy consumption and corresponding greenhouse gas emissions for the target year.

Suggested Citation

  • Jaewan Joe & Seunghyeon Min & Seunghwan Oh & Byungwoo Jung & Yu Min Kim & Deuk Woo Kim & Seung Eon Lee & Dong Hyuk Yi, 2022. "Development of Simplified Building Energy Prediction Model to Support Policymaking in South Korea—Case Study for Office Buildings," Sustainability, MDPI, vol. 14(10), pages 1-13, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:10:p:6000-:d:816105
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/10/6000/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/10/6000/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ludovica Maria Campagna & Francesco Fiorito, 2022. "On the Impact of Climate Change on Building Energy Consumptions: A Meta-Analysis," Energies, MDPI, vol. 15(1), pages 1-35, January.
    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. Albina Scioti & Mariella De Fino & Silvia Martiradonna & Fabio Fatiguso, 2022. "Construction Solutions and Materials to Optimize the Energy Performances of EPS-RC Precast Bearing Walls," Sustainability, MDPI, vol. 14(6), pages 1-18, March.
    2. Adel Benhamed & Yousif Osman & Ousama Ben-Salha & Zied Jaidi, 2023. "Unveiling the Spatial Effects of Climate Change on Economic Growth: International Evidence," Sustainability, MDPI, vol. 15(10), pages 1-20, May.
    3. dos Santos Ferreira, Greicili & Martins dos Santos, Deilson & Luciano Avila, Sérgio & Viana Luiz Albani, Vinicius & Cardoso Orsi, Gustavo & Cesar Cordeiro Vieira, Pedro & Nilson Rodrigues, Rafael, 2023. "Short- and long-term forecasting for building energy consumption considering IPMVP recommendations, WEO and COP27 scenarios," Applied Energy, Elsevier, vol. 339(C).
    4. Ehsan Ahmadian & Chris Bingham & Amira Elnokaly & Behzad Sodagar & Ivan Verhaert, 2022. "Impact of Climate Change and Technological Innovation on the Energy Performance and Built form of Future Cities," Energies, MDPI, vol. 15(22), pages 1-22, November.
    5. Anqi Yang & Shudong Yang, 2023. "Negative Sentiment Modeling and Public Legal Liability from Urban Green Space: A Framework for Policy Action in China," Sustainability, MDPI, vol. 15(7), pages 1-15, March.

    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:14:y:2022:i:10:p:6000-:d:816105. 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.