期刊
ENERGY AND BUILDINGS
卷 209, 期 -, 页码 -出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.enbuild.2019.109711
关键词
Energy performance; Energy benchmarking; Data-driven approaches; Comparative analysis
资金
- project Standard System for Post-assessment of Green Building Performance (National Key Projects in 13th Five -Year) [2016TFC0700105]
- National Natural Science Foundation of China [51978095]
- project A Big Data Platform of Supervison, Management and Evaluation for Institional Buidlings in Chongqing
- China Scholarship Council [201806050085]
A reasonable building energy efficiency benchmarking program plays an important role in energy consumption control and supervision. Previous studies have focused on the process of establishing a single benchmarking method, but few have compared the performances and outcomes of different methods. To fill this gap, this paper selects three benchmarking methods-multiple linear regression (MLR) based on Energy Star, stochastic frontier analysis (SFA) and the descriptive statistics method (DSM) based on the national energy consumption standard in China-to develop benchmarking models. We demonstrate each method using data on the energy and building characteristics of 45 four- and five-star hotel buildings located in Chongqing, China. To compare the consistency, robustness and explanatory ability of the three methods, we first utilize the Spearman rank correlation analysis to test whether these methods have consistent energy efficiency ranks and then present Sankey diagrams to further reveal the interactions of the estimated energy efficiency grades obtained from the three methods. It is found that the results of DSM and SFA are most consistent, while MLR vs. SFA and MLR vs. DSM present significant differences in evaluating building energy performance. In addition, DSM is more robust for evaluating the ranks of sampled buildings, while SFA is more robust for evaluating energy efficiency grades. Furthermore, we discuss the explanatory ability of each method. In addition to the building characteristics, the design and operational characteristics of the HVAC system have great effects on building energy consumption. Finally, we present suggestions for policy-makers regarding the development and implementation of the building energy benchmarking program in Chongqing and for the management of buildings with different energy performances to further improve the energy efficiency. (C) 2019 Elsevier B.V. All rights reserved.
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