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Improvements of the operational rating system for existing residential buildings

Author

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  • Jeong, Jaewook
  • Hong, Taehoon
  • Ji, Changyoon
  • Kim, Jimin
  • Lee, Minhyun
  • Jeong, Kwangbok
  • Koo, Choongwan

Abstract

The Building Energy Consumption Certification (BECC) evaluating the energy performance of existing buildings has been launched since 2016 to reduce the operational energy consumption in existing buildings in South Korea. However, the current BECC has some potential problems, and these problems should be solved to evaluate the energy performance of existing building more accurately. Thus, this study aims to identify the potential problems in the current BEEC using the hypothesis testing. And then this study proposes the improved BECC using the energy benchmarking process and the modified grading process to solve the potential problems. As a result of the hypothesis testing based on the data of 504 multi-family housing complexes (MFHCs), the potential problems were identified as follows: (i) the current classification criteria caused the irrational judgements, and (ii) the current grading system was lacking in its assessment function (over 94% of MFHCs ranked in the average level as grades “C” and “D”). To solve these problems, this study proposed the improved BECC. The energy benchmarking process provides the reasonable classification criteria, and the modified grading process finds the reasonable number of grades and its range. The result of comparative analysis based on 504 MFHCs indicated that the improved BECC could solve the problems in the current BECC. That is, over 94% of MFHCs were ranked in grades “C” and “D” in the current BECC while they were shown in all five grades (i.e., grades “A”, “B”, “C”, “D”, and “E”) in the improved BECC. The policy-makers can more accurately assess the energy performance of existing MFHCs by using the improved BECC.

Suggested Citation

  • Jeong, Jaewook & Hong, Taehoon & Ji, Changyoon & Kim, Jimin & Lee, Minhyun & Jeong, Kwangbok & Koo, Choongwan, 2017. "Improvements of the operational rating system for existing residential buildings," Applied Energy, Elsevier, vol. 193(C), pages 112-124.
    • Handle: RePEc:eee:appene:v:193:y:2017:i:c:p:112-124
    DOI: 10.1016/j.apenergy.2017.02.036
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    References listed on IDEAS

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    1. Hong, Taehoon & Koo, Choongwan & Kim, Hyunjoong & Seon Park, Hyo, 2014. "Decision support model for establishing the optimal energy retrofit strategy for existing multi-family housing complexes," Energy Policy, Elsevier, vol. 66(C), pages 157-169.
    2. Chung, William & Hui, Y.V. & Lam, Y. Miu, 2006. "Benchmarking the energy efficiency of commercial buildings," Applied Energy, Elsevier, vol. 83(1), pages 1-14, January.
    3. Jeong, Jaewook & Hong, Taehoon & Ji, Changyoon & Kim, Jimin & Lee, Minhyun & Jeong, Kwangbok, 2016. "Development of an integrated energy benchmark for a multi-family housing complex using district heating," Applied Energy, Elsevier, vol. 179(C), pages 1048-1061.
    4. Park, Hyo Seon & Lee, Minhyun & Kang, Hyuna & Hong, Taehoon & Jeong, Jaewook, 2016. "Development of a new energy benchmark for improving the operational rating system of office buildings using various data-mining techniques," Applied Energy, Elsevier, vol. 173(C), pages 225-237.
    5. Koo, Choongwan & Park, Sungki & Hong, Taehoon & Park, Hyo Seon, 2014. "An estimation model for the heating and cooling demand of a residential building with a different envelope design using the finite element method," Applied Energy, Elsevier, vol. 115(C), pages 205-215.
    6. Koo, Choongwan & Hong, Taehoon, 2015. "Development of a dynamic operational rating system in energy performance certificates for existing buildings: Geostatistical approach and data-mining technique," Applied Energy, Elsevier, vol. 154(C), pages 254-270.
    7. Xuchao, Wu & Priyadarsini, Rajagopalan & Siew Eang, Lee, 2010. "Benchmarking energy use and greenhouse gas emissions in Singapore's hotel industry," Energy Policy, Elsevier, vol. 38(8), pages 4520-4527, August.
    8. Koo, Choongwan & Hong, Taehoon & Lee, Minhyun & Seon Park, Hyo, 2014. "Development of a new energy efficiency rating system for existing residential buildings," Energy Policy, Elsevier, vol. 68(C), pages 218-231.
    9. Lee, Wen-Shing, 2010. "Benchmarking the energy performance for cooling purposes in buildings using a novel index-total performance of energy for cooling purposes," Energy, Elsevier, vol. 35(1), pages 50-54.
    10. Lee, Wen-Shing & Lin, Yeong-Chuan, 2011. "Evaluating and ranking energy performance of office buildings using Grey relational analysis," Energy, Elsevier, vol. 36(5), pages 2551-2556.
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    2. Zhou, Yuren & Lork, Clement & Li, Wen-Tai & Yuen, Chau & Keow, Yeong Ming, 2019. "Benchmarking air-conditioning energy performance of residential rooms based on regression and clustering techniques," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    3. Yu, Yanzhe & Cheng, Jie & You, Shijun & Ye, Tianzhen & Zhang, Huan & Fan, Man & Wei, Shen & Liu, Shan, 2019. "Effect of implementing building energy efficiency labeling in China: A case study in Shanghai," Energy Policy, Elsevier, vol. 133(C).
    4. Rastogi, Ankush & Choi, Jun-Ki & Hong, Taehoon & Lee, Minhyun, 2017. "Impact of different LEED versions for green building certification and energy efficiency rating system: A Multifamily Midrise case study," Applied Energy, Elsevier, vol. 205(C), pages 732-740.
    5. Lee, Minhyun & Hong, Taehoon & Jeong, Jaewook & Jeong, Kwangbok, 2018. "Development of a rooftop solar photovoltaic rating system considering the technical and economic suitability criteria at the building level," Energy, Elsevier, vol. 160(C), pages 213-224.
    6. Liu, Jiangyan & Chen, Huanxin & Liu, Jiahui & Li, Zhengfei & Huang, Ronggeng & Xing, Lu & Wang, Jiangyu & Li, Guannan, 2017. "An energy performance evaluation methodology for individual office building with dynamic energy benchmarks using limited information," Applied Energy, Elsevier, vol. 206(C), pages 193-205.

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