대한건축학회논문집 (Journal of the Architectural Institute of Korea)

  • 제38권11호
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  • Pages.289-296
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  • 2022
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  • 2733-6239(pISSN)
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  • 2733-6247(eISSN)
대한건축학회 (Architectural Institute of Korea)
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에너지 성능 지표 (EPI)의 문제와 개선 - ECO2 vs. EnergyPlus와의 상관성 분석을 중심으로 -

Limitations and Improvement of Energy Performance Index - Focusing on Comparison between ECO2 and EnergyPlus -

  • 이승주 (서울대 건축학과) ;
  • 유영서 (서울대 건축학과) ;
  • 박철홍 (서울대 건축학과) ;
  • 박철수 (서울대 건축학과.공학연구원.건설환경종합연구소)
  • Lee, Seung-Ju (Dept. of Architecture & Architectural Engineering, Seoul National University) ;
  • Yoo, Young-Seo (Dept. of Architecture & Architectural Engineering, Seoul National University) ;
  • Park, Chul-Hong (Dept. of Architecture & Architectural Engineering, Seoul National University) ;
  • Park, Cheol-Soo (Dept. of Architecture and Architectural Engineering.Institute of Engineering Research.Institute of Construction and Environmental Engineering, Seoul National University)
  • 투고 : 2022.08.30
  • 심사 : 2022.10.12
  • 발행 : 2022.11.30
⟨ 이전 논문 다음 논문 ⟩

초록

The issues and limitations of the current prescriptive domestic building energy code compliance, or EPI was addressed. In order to convert it into being performance-based, a global sensitivity analysis, Sobol was used. For this purpose, a medium office building developed by US DOE was selected. The Sobol sensitivity indices per design variables were substituted for weights (a) and (b) to calculate a new EPI. Based on the comparison between the new EPI, ECO2 calculation and EnergyPlus simulation results, it was found that the new EPI becomes more proportional to Energy Use Intensity (EUI) calculated from EnergyPlus (R2 = 89.3%).

키워드

과제정보

해당 과제는 한국에너지공단의 연구비를 지원받아 수행되었습니다.

참고문헌

  1. Amiri, A., Ottelin, J., & Sorvari, J. (2019). Are LEED-certified buildings energy-efficient in practice?. Sustainability, 11(6), 1672. https://doi.org/10.3390/su11061672
  2. Bloem, H. (2013). Evaluating and modelling nearly-zero energy buildings; are we ready for 2018, IBPSA World conference 2013 (discussion in a keynote speech)
  3. de Wilde, P. (2014). The gap between predicted and measured energy performance of buildings: A framework for investigation. Automation in Construction, 41, 40-49. https://doi.org/10.1016/j.autcon.2014.02.009
  4. Hopfe, C. J. (2009). Uncertainty and Sensitivity Analysis in Building Performance Simulation for Decision Support and Design Optimization. Ph.D. Dissertation, Eindhoven University of Technology.
  5. Jo, J. (2017). A study on evaluation criteria and evaluation tool for Energy Performance of internal and external building. Special projectII-Zero Energy Building Policies and Trends of Internal and External Building, SSangyong, 74, 16-23.
  6. KEA. (2016). Building Energy Efficiency Certification, Korea Energy Agency.
  7. KEA. (n.d) Building energy code compliance, Korea Energy Agency, Retrieved July 18, 2022 from https://dco.energy.or.kr/renew_eng/energy/buildings/worksheet.aspx
  8. Kim, S. H., Kwak, Y. H., & Kim, C. S. (2018). The analysis on energy performance of collective housing using ECO2 and DesignBuilder softwares. Korea Inst. Ecol. Archit. Environ. J.(KIEAE J.), 18, 47-54.
  9. Kim, Y. A., Jang, H. I., Park, C. Y., Jang, D. H., & Lee, K. H. (2016). Comparison of cooling and heating load analysis characteristics of the energy performance assessment tools for green remodeling. Journal of Korean Institute of Architectural Sustainable Environment and Building System, 10(6), 449-455.
  10. Kim, Y. J., & Park, C. S. (2008). Uncertainty analysis of ventilation strategies in residential apartment buildings. Journal of the Architectural Institute of Korea, Planning and Design section, 24(8), 311-320.
  11. Korea Institute of Construction Technology. (2017). Construction report/Published data. Codil. Retrieved Oct 4, 2022 from https://scienceon.kisti.re.kr/srch/selectPORSrchReport.do?cn=TRKO201700004332
  12. Malkawi, A., & Augenbroe, G. (2004). Advanced Building Simulation. 1st ed., Routledge, 5.
  13. Ostertagova, E. (2012). Modelling using polynomial regression. Procedia Engineering, 48, 500-506. https://doi.org/10.1016/j.proeng.2012.09.545
  14. Park, C. S. (2006). Normative assessment of technical building performance. Journal of Architecture Institute (Planning), 22(11), 337-344.
  15. Saltelli, A., Ratto, M., Tarantola, S., & Campolongo, F. (2006). Sensitivity analysis practices: Strategies for model-based inference. Reliability Engineering & System Safety, 91(10-11), 1109-1125. https://doi.org/10.1016/j.ress.2005.11.014
  16. Saltelli, A., Tarantola, S., Campolongo, F., & Ratto, M. (2004). Sensitivity analysis in practice: a guide to assessing scientific models. Chichester, England.
  17. Tian, W. (2013). A review of sensitivity analysis methods in building energy analysis. Renewable and Sustainable Energy Reviews, 20, 411-419. https://doi.org/10.1016/j.rser.2012.12.014
  18. Yoo, Y. S., Yi, D. H., Kim, S. S., & Park, C. S. (2020). Rational building energy assessment using global sensitivity analysis. Journal of the Architectural Institute of Korea Structure & Construction, 36(5), 177-185.