Conference Year

2014

Keywords

commercial buildings, building energy conservation, building energy performance, sub-metered data

Abstract

With energy use growing rapidly around the world, building energy conservation is becoming a great concern especially for large commercial buildings. Therefore, it is of great significance to develop appropriate methods for energy use assessment of commercial buildings. In recent years, energy monitoring system (EMS) has been applied in some large-scale commercial buildings, which has laid the foundation for exhaustive and authentic evaluation. However, most of the current studies are only focused on annual or monthly aggregated energy consumption. Though end-use data are monitored in some buildings, only major categories or equipment are included. Little has been done to analyze the energy performance of numerous buildings with detailed hourly end-use data. With the access to hourly sub-metered data of detailed end uses, this study aims to introduce a comparing method to evaluate building energy performance through a case study. Information on selected buildings in the case was introduced. The research intends to compare energy use intensity (EUI) of the 19 malls based on a uniform energy data model, from total energy to detailed end-uses. It was shown that there is a significant discrepancy on the total energy use among these buildings, mainly due to HVAC (Heating, Ventilation and Air Conditioning) and public lighting. Then an in-depth comparative study was conducted on the energy consumption of public lighting and HVAC respectively. An unexpectedly remarkable discrepancy was illustrated on the EUI of public lighting. Thus the daily and hourly energy of public lighting were compared to identify the discrepancy in management mode. The study on HVAC was focused on the comparison of daily and hourly EUI in terms of four subordinate end uses (chillers, chilled water pumps, fans and cooling systems). The result showed that chillers accounts for larger proportions of total energy use, and the daily and hourly data were compared between buildings with similar climate. At last, the methods were summarized and challenges were discussed.

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