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A multi-level energy performance diagnosis method for energy information poor buildings

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  • Yan, Chengchu
  • Wang, Shengwei
  • Xiao, Fu
  • Gao, Dian-ce

Abstract

A thorough assessment and diagnosis is critical for understating and enhancing building energy performance while most buildings cannot provide sufficient energy use data for a detailed diagnosis. This paper presents a multi-level energy performance diagnosis method for energy information-poor buildings where very limited energy use data are available. A simplified monthly energy performance calculation method based on basic energy balances within a building is developed. It provides sufficient energy performance data of a building at multiple levels (i.e., building, system and component levels) while only requiring monthly energy bill data and few in-situ measurements of the HVAC system. The energy performance level then can be determined by comparing the estimated performance data with the benchmark data. A customized benchmarking method using the “relative performance factor” is proposed to indicate the relative difference between the current performance and the expected performance, and to estimate the energy saving potentials. The developed multi-level energy performance calculation method is validated in a super high-rise building in Hong Kong. A case study on illustrating how to apply the proposed diagnosis method for identifying the poor performance areas and the causes behind as well as estimating the energy saving potentials is also presented.

Suggested Citation

  • Yan, Chengchu & Wang, Shengwei & Xiao, Fu & Gao, Dian-ce, 2015. "A multi-level energy performance diagnosis method for energy information poor buildings," Energy, Elsevier, vol. 83(C), pages 189-203.
    • Handle: RePEc:eee:energy:v:83:y:2015:i:c:p:189-203
    DOI: 10.1016/j.energy.2015.02.014
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    9. Wang, Huilong & Xu, Peng & Lu, Xing & Yuan, Dengkuo, 2016. "Methodology of comprehensive building energy performance diagnosis for large commercial buildings at multiple levels," Applied Energy, Elsevier, vol. 169(C), pages 14-27.
    10. Yang, Dong & Li, Ping, 2015. "Dimensionless design approach, applicability and energy performance of stack-based hybrid ventilation for multi-story buildings," Energy, Elsevier, vol. 93(P1), pages 128-140.
    11. Harish, V.S.K.V. & Kumar, Arun, 2016. "A review on modeling and simulation of building energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1272-1292.
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