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Study on the Improvement of Expected Energy Savings and Actual Energy Savings in Apartments

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  • Won-Jun Park

    (Department of Architectural Engineering, Kangwon National University, Jungang-ro, Samcheok-si, Kangwon-do 24341, Korea)

  • Hye-Mi Kim

    (Department of Architectural Engineering, Kangwon National University, Jungang-ro, Samcheok-si, Kangwon-do 24341, Korea)

Abstract

Regulating energy consumption can reduce both greenhouse gas emissions and expenditures. In order to maximize efficiency, appropriate energy protocols for buildings must be devised and implemented. This study examines predicted and real energy savings, the differences between them, and the methods which might reduce these discrepancies. Analyses for 195 high-efficiency apartment units (certified based on the energy efficiency rating system in use in Korea) indicated an average difference of 23% between predicted and real energy savings. This was found to be due to the fact that predictions failed to take variables such as Heating Type, Corridor Type, and Climate into account. By accounting for these factors, an appropriate calculation formula may be established. Using the revised calculation formula to reevaluate the predicted energy savings of 13 apartment units resulted in a reduction of 7% in the aforementioned discrepancy between predicted and real energy savings. Using the proposed formula to predict energy savings in buildings could improve accuracy, thus facilitating the setting of appropriate standards for restrictions on greenhouse gas emissions of buildings.

Suggested Citation

  • Won-Jun Park & Hye-Mi Kim, 2018. "Study on the Improvement of Expected Energy Savings and Actual Energy Savings in Apartments," Sustainability, MDPI, vol. 10(4), pages 1-15, April.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:4:p:1089-:d:139752
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    References listed on IDEAS

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    1. Kontokosta, Constantine E. & Tull, Christopher, 2017. "A data-driven predictive model of city-scale energy use in buildings," Applied Energy, Elsevier, vol. 197(C), pages 303-317.
    2. Giacomo Salvadori & Fabio Fantozzi & Michele Rocca & Francesco Leccese, 2016. "The Energy Audit Activity Focused on the Lighting Systems in Historical Buildings," Energies, MDPI, vol. 9(12), pages 1-13, November.
    3. Francesca Pagliaro & Lucia Cellucci & Chiara Burattini & Fabio Bisegna & Franco Gugliermetti & Andrea De Lieto Vollaro & Ferdinando Salata & Iacopo Golasi, 2015. "A Methodological Comparison between Energy and Environmental Performance Evaluation," Sustainability, MDPI, vol. 7(8), pages 1-19, July.
    4. Abu Bakar, Nur Najihah & Hassan, Mohammad Yusri & Abdullah, Hayati & Rahman, Hasimah Abdul & Abdullah, Md Pauzi & Hussin, Faridah & Bandi, Masilah, 2015. "Energy efficiency index as an indicator for measuring building energy performance: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 1-11.
    5. Lin, Jianyi & Cao, Bin & Cui, Shenghui & Wang, Wei & Bai, Xuemei, 2010. "Evaluating the effectiveness of urban energy conservation and GHG mitigation measures: The case of Xiamen city, China," Energy Policy, Elsevier, vol. 38(9), pages 5123-5132, September.
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    Cited by:

    1. Fabrizio Maria Amoruso & Udo Dietrich & Thorsten Schuetze, 2018. "Development of a Building Information Modeling-Parametric Workflow Based Renovation Strategy for an Exemplary Apartment Building in Seoul, Korea," Sustainability, MDPI, vol. 10(12), pages 1-30, November.

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