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Estimation Method of Energy Consumption by End-Use in Office Buildings based on the Measurement Data

계측데이터를 이용한 업무시설에서의 에너지용도별 사용량 추정방법 연구

  • 김성임 (이케이 에너지연구소) ;
  • 양인호 (동국대학교 건축공학과) ;
  • 하수연 (이화여자대학교 건축도시시스템공학과) ;
  • 이수진 (이화여자대학교 건축도시시스템공학과) ;
  • 진혜선 (이화여자대학교 건축도시시스템공학과) ;
  • 서인애 (이화여자대학교 건축도시시스템공학과) ;
  • 송승영 (이화여자대학교 건축도시시스템공학과)
  • Received : 2020.02.28
  • Accepted : 2020.05.16
  • Published : 2020.05.30

Abstract

The purpose of this study is to develop a estimation method of energy consumption by end-use in office buildings. For this, the current status of information on building energy use was investigated, and the domestic and foreign literature on the classification of energy use in non-residential buildings and the estimation method of energy use were reviewed. In addition, the characteristics of energy consumption by end-use were analyzed with measurement data of 48 office buildings in Seoul. As results, the annual and monthly estimation method of energy consumption by end-use in office buildings using public and measurement data was presented, and the applicability of the estimation method was examined by applying to sample office buildings.

Keywords

Acknowledgement

이 연구는 2019년도 국토교통부 도시건축연구개발사업의 연구비 지원에 의한 결과의 일부임. 과제번호:19AUDP-B079104-06

References

  1. Kim, S.I. (2019). Estimation method of end-use energy consumption in office buildings using public and measured data, Ph.D. Thesis, Department of Architectural and Urban Systems Engineering, Ewha Womans Univ.
  2. Ewha University-Industry Collaboration Foundation & Dongguk University Industry-Academic Cooperation Foundation (2019). Patent No. 10-1976784, Estimation method for annual and monthly energy consumption by end-use in non-residential buildings using public and measurement data
  3. Kim, S.I., Jin, H.S., Lee, S.J., Kim, Y.J., Song, S.Y., Lim, J.H., & Yang, I.H. (2018). Analysis of measurement data to develop estimation method for monthly energy consumption by end-use in office building of Korea, Korea Journal of Air-Conditioning and Refrigeration Engineering in Winter Conference, 306-309
  4. Kim, S.I., Lim, S.H., Jin, H.S., Yang, I.H., Lim, J.H., & Song, S.Y. (2017). Estimation method for energy consumption by end-use in office building of Korea, Summer Annual Conference of the Society of Air-Conditioning and Refrigerating Engineers of Korea, 885-888
  5. Kim, S.I., Lim, S.H., Jin, H.S., Yang, I.H., Lim, J.H., & Song, S.Y. (2017). Investigation on the current status of building, equipments, and operation to develop standard conditions in office building of Korea, Spring Annual Conference of Architectural Institute of Korea, 37(1), 429-432
  6. C.R., B.D., J.H., W.Z., S.G., & R.M.P. (2017). Machine learning approaches for estimating commercial building energy consumption, Applied Energy, 208, 889-904 https://doi.org/10.1016/j.apenergy.2017.09.060
  7. H. AKABARI (1995). Validation of an algorithm to disaggregate whole-building hourly electrical load into end uses, Energy, 20, 1291-1301 https://doi.org/10.1016/0360-5442(95)00033-D
  8. Chengchu Y., Shengwei W., & Fu X. (2012). A simplified energy performance assessment method for existing buildings based on energy bill disaggregation, Energy and Buildings, 55, 563-574 https://doi.org/10.1016/j.enbuild.2012.09.043
  9. Shengwei W., Chengchu Y., & Fu X. (2012). Quantitative energy performance assessment methods for existing buildings, Energy and Buildings, 55, 873-888 https://doi.org/10.1016/j.enbuild.2012.08.037