IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i7p3611-d523267.html
   My bibliography  Save this article

Development and Verification of Prototypical Office Buildings Models Using the National Building Energy Consumption Survey in Korea

Author

Listed:
  • Hye-Jin Kim

    (Department of Architectural Engineering, Chungbuk National University, 1 Chungdae-ro, Seowon-gu, Cheongju, Chungbuk 28644, Korea)

  • Do-Young Choi

    (Korea Energy Economics Institute, 405-11, Jongga-ro, Jung-gu, Ulsan 44543, Korea)

  • Donghyun Seo

    (Department of Architectural Engineering, Chungbuk National University, 1 Chungdae-ro, Seowon-gu, Cheongju, Chungbuk 28644, Korea)

Abstract

In the early 2000s, the Korean government mandated the construction of only zero-energy residential buildings by 2025 and for non-residential buildings from 2030. Two decades since the start of building energy policy enforcement, Korean experts believe that it is time to evaluate its impact. However, few studies have systematically and extensively examined the energy consumption characteristics of the non-residential building stock. In this study, a framework development is implemented for defining non-residential prototypical office buildings based on Korea’s first large-scale non-residential building survey result from the Korea Energy Economics Institute (KEEI). Then, a detailed building energy model of the defined prototypical building is constructed to verify the model’s energy estimation against observed energy consumption. As an application of the model, a case study for energy policy evaluation utilizing the constructed prototypical building model is presented. Every researcher and county may have their own circumstances when gathering definition data. However, by using the best available representative data, this suggested framework may result in informed decisions regarding energy policy development and evaluation. In addition, the mitigation of greenhouse gases from buildings may be expedited.

Suggested Citation

  • Hye-Jin Kim & Do-Young Choi & Donghyun Seo, 2021. "Development and Verification of Prototypical Office Buildings Models Using the National Building Energy Consumption Survey in Korea," Sustainability, MDPI, vol. 13(7), pages 1-15, March.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:7:p:3611-:d:523267
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/7/3611/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/7/3611/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Corgnati, Stefano Paolo & Fabrizio, Enrico & Filippi, Marco & Monetti, Valentina, 2013. "Reference buildings for cost optimal analysis: Method of definition and application," Applied Energy, Elsevier, vol. 102(C), pages 983-993.
    2. Im, Piljae & Joe, Jaewan & Bae, Yeonjin & New, Joshua R., 2020. "Empirical validation of building energy modeling for multi-zones commercial buildings in cooling season," Applied Energy, Elsevier, vol. 261(C).
    3. Attia, Shady & Shadmanfar, Niloufar & Ricci, Federico, 2020. "Developing two benchmark models for nearly zero energy schools," Applied Energy, Elsevier, vol. 263(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.
    1. Attia, Shady & Canonge, Théophile & Popineau, Mathieu & Cuchet, Mathilde, 2022. "Developing a benchmark model for renovated, nearly zero-energy, terraced dwellings," Applied Energy, Elsevier, vol. 306(PB).
    2. Baglivo, Cristina & Congedo, Paolo Maria & D'Agostino, Delia & Zacà, Ilaria, 2015. "Cost-optimal analysis and technical comparison between standard and high efficient mono-residential buildings in a warm climate," Energy, Elsevier, vol. 83(C), pages 560-575.
    3. Pikas, Ergo & Thalfeldt, Martin & Kurnitski, Jarek & Liias, Roode, 2015. "Extra cost analyses of two apartment buildings for achieving nearly zero and low energy buildings," Energy, Elsevier, vol. 84(C), pages 623-633.
    4. Shady Attia, 2020. "Spatial and Behavioral Thermal Adaptation in Net Zero Energy Buildings: An Exploratory Investigation," Sustainability, MDPI, vol. 12(19), pages 1-15, September.
    5. Brandão de Vasconcelos, Ana & Pinheiro, Manuel Duarte & Manso, Armando & Cabaço, António, 2015. "A Portuguese approach to define reference buildings for cost-optimal methodologies," Applied Energy, Elsevier, vol. 140(C), pages 316-328.
    6. Younghoon Kwak & Jeonga Kang & Sun-Hye Mun & Young-Sun Jeong & Jung-Ho Huh, 2020. "Development and Application of a Flexible Modeling Approach to Reference Buildings for Energy Analysis," Energies, MDPI, vol. 13(21), pages 1-22, November.
    7. Bienvenido-Huertas, David & Moyano, Juan & Rodríguez-Jiménez, Carlos E. & Marín, David, 2019. "Applying an artificial neural network to assess thermal transmittance in walls by means of the thermometric method," Applied Energy, Elsevier, vol. 233, pages 1-14.
    8. Aste, Niccolò & Adhikari, R.S. & Manfren, Massimiliano, 2013. "Cost optimal analysis of heat pump technology adoption in residential reference buildings," Renewable Energy, Elsevier, vol. 60(C), pages 615-624.
    9. Szalay, Zsuzsa & Zöld, András, 2014. "Definition of nearly zero-energy building requirements based on a large building sample," Energy Policy, Elsevier, vol. 74(C), pages 510-521.
    10. Delmastro, C. & Martinsson, F. & Dulac, J. & Corgnati, S.P., 2017. "Sustainable urban heat strategies: Perspectives from integrated district energy choices and energy conservation in buildings. Case studies in Torino and Stockholm," Energy, Elsevier, vol. 138(C), pages 1209-1220.
    11. Eleftheria Touloupaki & Theodoros Theodosiou, 2017. "Optimization of External Envelope Insulation Thickness: A Parametric Study," Energies, MDPI, vol. 10(3), pages 1-19, February.
    12. Yoon, Y. & Jung, S. & Im, P. & Salonvaara, M. & Bhandari, M. & Kunwar, N., 2023. "Empirical validation of building energy simulation model input parameter for multizone commercial building during the cooling season," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    13. Ascione, Fabrizio & Bianco, Nicola & Mauro, Gerardo Maria & Vanoli, Giuseppe Peter, 2019. "A new comprehensive framework for the multi-objective optimization of building energy design: Harlequin," Applied Energy, Elsevier, vol. 241(C), pages 331-361.
    14. Younghoon Kwak & Jeong-A Kang & Jung-Ho Huh & Tae-Hyoung Kim & Young-Sun Jeong, 2019. "An Analysis of the Effectiveness of Greenhouse Gas Reduction Policy for Office Building Design in South Korea," Sustainability, MDPI, vol. 11(24), pages 1-25, December.
    15. D'Agostino, D. & Parker, D. & Epifani, I. & Crawley, D. & Lawrie, L., 2022. "How will future climate impact the design and performance of nearly zero energy buildings (NZEBs)?," Energy, Elsevier, vol. 240(C).
    16. Hye-Ryeong Nam & Seo-Hoon Kim & Seol-Yee Han & Sung-Jin Lee & Won-Hwa Hong & Jong-Hun Kim, 2020. "Statistical Methodology for the Definition of Standard Model for Energy Analysis of Residential Buildings in Korea," Energies, MDPI, vol. 13(21), pages 1-16, November.
    17. Umberto Berardi & Lamberto Tronchin & Massimiliano Manfren & Benedetto Nastasi, 2018. "On the Effects of Variation of Thermal Conductivity in Buildings in the Italian Construction Sector," Energies, MDPI, vol. 11(4), pages 1-17, April.
    18. Ascione, Fabrizio & Bianco, Nicola & De Stasio, Claudio & Mauro, Gerardo Maria & Vanoli, Giuseppe Peter, 2017. "Artificial neural networks to predict energy performance and retrofit scenarios for any member of a building category: A novel approach," Energy, Elsevier, vol. 118(C), pages 999-1017.
    19. Filogamo, Luana & Peri, Giorgia & Rizzo, Gianfranco & Giaccone, Antonino, 2014. "On the classification of large residential buildings stocks by sample typologies for energy planning purposes," Applied Energy, Elsevier, vol. 135(C), pages 825-835.
    20. Yamaguchi, Yohei & Kim, Bumjoon & Kitamura, Takuya & Akizawa, Kotone & Chen, Hemiao & Shimoda, Yoshiyuki, 2022. "Building stock energy modeling considering building system composition and long-term change for climate change mitigation of commercial building stocks," Applied Energy, Elsevier, vol. 306(PA).

    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:13:y:2021:i:7:p:3611-:d:523267. 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.