Volume 01: Proceedings of Applied Energy Symposium: MIT A+B, United States, 2019

A comparative analysis of data-driven building energy benchmarking methods: a case study in China Xue Liu, Yong Ding, Hao Tang


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 performance and outcomes of different methods. To fill this gap, this paper selects two benchmarking methods— multiple linear regression (MLR) based on Energy Star, and stochastic frontier analysis (SFA) 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 and explanatory ability of two 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 scores obtained from these methods. The results show that even though the ranks of sampled buildings are basically consistent, the energy efficiency scores have significant differences especially for the buildings with low energy efficiency scores. Furthermore, we discuss the explanatory ability of each method. In addition to building characteristics, the design and operational characteristics of the HVAC system have great effects on building energy consumption.

Keywords energy benchmarking, multiple linear regression, stochastic frontier analysis, comparative analysis

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