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Development of an End-use Analysis Tool for Existing Buildings Based on Energy Billing Data

고지데이터 기반 기존 건축물의 용도별 에너지사용 현황분석 툴 개발

  • Kong, Dong-Seok (Department of Architectural Engineering, University of Seoul) ;
  • Park, Jung-Min (Department of Architectural Engineering, University of Seoul) ;
  • Jang, Yong-Sung (GS E&C Building Science Research Team) ;
  • Lee, Keon-Ho (Korea Instiute of Construction Technology) ;
  • Huh, Jung-Ho (Department of Architectural Engineering, University of Seoul)
  • 공동석 (서울시립대학교 건축공학과) ;
  • 박정민 (서울시립대학교 건축공학과) ;
  • 장용성 (GS건설기술연구소) ;
  • 이건호 (한국건설기술연구원) ;
  • 허정호 (서울시립대학교 건축공학과)
  • Received : 2014.11.04
  • Accepted : 2015.01.08
  • Published : 2015.03.10

Abstract

Reducing the building energy consumption has become one of the most important issues. However, the current engineering and technological involvement in energy analysis has been relatively low in the existing buildings. In the existing buildings, end-use analysis must be accompanied to calculate the exact amount in energy savings and such analysis should be conducted based on the energy billing data or measurement data by calibration process. Mostly, detailed energy simulation programs have been proposed for the analysis but, it is difficult to utilize them due to realistic problems. In this paper, we developed an end-use analysis tool that have input function for energy audit data and two case studies were conducted in the real-life office buildings located in Seoul, Korea. Mean Bias Error (MBE) and Coefficient of Variation of Root-Mean- Squreaed-Error (CV(RMSE)) are used for the criteria of comparison. Each index was calculated by using monthly utility bills of electricity and gas consumption. Results showed that MBE and CV (RMSE) represented with acceptable values of -0.1% and 5.7% respectively.

Keywords

References

  1. Park, C.-S., 2013, New Future Opportunities in Area of Building Energy, AIK special issue, Architectural Institute of Korea, Vol. 57, pp. 40-42.
  2. Ministry of Land, Infrastructure and Transport, Korea, webpage, http://www.molit.go.kr/USR/NEWS/m_71/dtl.jsp?lcmspage=1&id=95067770.
  3. ASHRAE, 2012, Procedures for commercial building energy audits second edition, American Society of Heating, Refrigeration and Air Conditioning Engineers, Atlanta.
  4. David, R. and Howard, R., 1992, The use of term measurements to decompose commercial billing data into primary end uses, ACEEE 1992 Summer Study on Energy Efficiency in Buildings, Vol. 3, ACEEE, Washington, D.C. pp. 239-249.
  5. Akbari, H., 1995, Validation of an algorithm to disaggregate whole-building hourly electrical load into end uses. Energy, Vol. 20, No. 12, pp. 1291-1301. https://doi.org/10.1016/0360-5442(95)00033-D
  6. Birt, Benjamin J., et al, 2012, Disaggregating categories of electrical energy end-use from whole-house hourly data. Energy and Buildings, Vol. 50, pp. 93-102. https://doi.org/10.1016/j.enbuild.2012.03.025
  7. Raftery, P., Keane, M., and O'Donnell, J., 2011, Calibrating whole building energy models : An evidence-based methodology, Energy and Buildings, Vol. 43, No. 9, pp. 2356-2364. https://doi.org/10.1016/j.enbuild.2011.05.020
  8. Heo, Y., Choudhary, R., and Augenbroe, G., 2012, Calibration of building energy models for retrofit analysis under uncertainty, Energy and Buildings, Vol. 47, pp. 550-560. https://doi.org/10.1016/j.enbuild.2011.12.029
  9. Reddy, T. A., Maor, I., and Panjapornpon, C., 2007, Calibrating Detailed Building Energy Simulation Programs with Measured Data-Part I : General Methodology(RP-1051), HVAC&R RESEARCH, Vol. 13, No. 2, pp. 221-241. https://doi.org/10.1080/10789669.2007.10390952
  10. Reddy, T. A., 2005, Literature Review on Calibration of Building Energy Simulation Programs : Uses, Problems, Procedures, Uncertainty, and Tools, ASHRAE Transactions, Vol. 112, pp. 226-240.
  11. Efficiency Valuation Organization(EVO), International Performance Measurement and Verification Protocol (IPMVP) Public Library of Documents, http://www.evoworld.org/index.php?option=com_content&view=article&id=272&Itemid=379&lang=en.
  12. EnergyPlus Engineering Reference, 2013, US Department of Energy.
  13. Adak, M. F., Duru, N., and Duru, H. T., 2013, Elevator simulator design and estimating energy consumption of an elevator system. Energy and Buildings, Vol. 65, pp. 272-280. https://doi.org/10.1016/j.enbuild.2013.06.003
  14. Kong, D. et al, 2014, Existing building energy simulation method using calibrated model by energy audit data, Korean Journal of Air-Conditioning and Refrigeration Engineering, Vol. 26, No. 5, pp. 231-239. https://doi.org/10.6110/KJACR.2014.26.5.231

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