A classification of building energy performance indices

Energy performance indices are used around the world to evaluate and monitor residential and commercial building energy performance during design, construction, renovation, and operation. The two most common indices are Asset Ratings and Operational Ratings. Asset Ratings are based on modeled energy use with uniform conditions of climate, schedules, plug loads, occupancy, and energy management. Operational Ratings are based on measured energy use, often normalized for relevant variables like climate and level of energy service. Surprisingly, there is almost no discussion in the literature about the technical basis of these ratings and what they are attempting to measure. This paper analyzes the merits and weaknesses of the common ratings and introduces additional energy performance indices, in particular the Operation and Maintenance (O&M) Index, which is the ratio of the energy consumption as measured at the meter to the simulated energy performance, calibrated for the actual operating conditions of the building. We provide examples of how such indices are currently used, although we do so as examples to illustrate our hypothesis as to what indices are most helpful to improve energy management, rather than as a comprehensive review. We show how these indices work together to provide better feedback to energy managers. The Operational Rating answers the question: “how does the energy intensity of this building compare to its peers?” The Asset Rating answers the question: “how efficient is this building?” The O&M Index answers the question: “how well is this building being managed?” These questions are useful to answer in the context of a comprehensive energy management program, such as would be required by an Energy Management System standard.

[1]  Vice President,et al.  AMERICAN SOCIETY OF HEATING, REFRIGERATION AND AIR CONDITIONING ENGINEERS INC. , 2007 .

[2]  David B. Goldstein,et al.  Developing a Suite of Energy Performance Indicators (EnPIs) to Optimize Outcomes , 2013 .

[3]  Jen Chun Wang,et al.  A study on the energy performance of hotel buildings in Taiwan , 2012 .

[4]  Constantine Kontokosta,et al.  Predicting Building Energy Efficiency Using New York City Benchmarking Data , 2012 .

[5]  Cathy Turner,et al.  Green Building Performance Evaluation: Measured Results from LEED-New Construction Buildings , 2008 .

[6]  Yoshiyuki Shimoda,et al.  Classification of Japanese Retail Facilities to Establish Benchmark Energy Consumption , 2012 .

[7]  Yi Jiang,et al.  The reality and statistical distribution of energy consumption in office buildings in China , 2012 .

[8]  Lara Greden,et al.  Minnesota B3 Benchmarking Results: Prioritizing the Energy Savings Opportunity in Minnesota Public Buildings , 2008 .

[9]  J. Kenneth Monts,et al.  Assessing energy efficiency and energy conservation potential among commercial buildings: A statistical approach , 1982 .

[10]  Lee Schipper,et al.  Energy efficiency and conservation in buildings: The use of indicators , 1983 .

[11]  Harold E. Marshall,et al.  Economics and the selection and development of energy standards for buildings , 1979 .

[12]  Shilei Lu,et al.  Energy consumption quota of four and five star luxury hotel buildings in Hainan province, China , 2012 .

[13]  P. Bannister NABERS: Lessons from 12 Years of Performance Based Ratings in Australia , 2012 .

[14]  William Chung,et al.  Review of building energy-use performance benchmarking methodologies , 2011 .

[15]  Georgios A. Florides,et al.  The characteristics and the energy behaviour of the residential building stock of Cyprus in view of Directive 2002/91/EC , 2010 .