1、Roger (Jui-Chen) Chang, PE, LEED Fellow, is a Principal at Westlake Reed Leskosky, Washington, DC. Energy Utilization Effectiveness (EUE): A New Metric for Commercial Building Energy Use Characterization Roger Chang, PE Member ASHRAE ABSTRACT The energy utilization index (EUI) is commonly used to de
2、scribe a buildings energy performance. This index is not without shortcomings, as it does not adequately address issues such as space utilization, occupant density, or irreducible process loads. This paper explores the use of a bottom-up approach for energy benchmarking, both for design optimization
3、 and portfolio analysis, utilizing a concept known as energy usage effectiveness (EUE). The EUE metric is based on the ratio of a buildings total energy use divded by an adapted calculation of process energy use. Benchmark EUE values will be calculated based on the Department of Energys Commercial R
4、eference Buildings for new construction, existing buildings “post-1980“ and existing buildings “pre-1980s.“ The full range of ASHRAE climate ones will be represented for all of the major building types available. EUE will be compared to calculated EUI, to highlight correlations and divergences in th
5、e outcome data. The EUE concept will also be applied to data from a heavily sub-metered high-performance building, as well as public data published in ASHRAE high-performance building case studies. INTRODUCTION The ever increasing focus on low-energy buildings has created significant interest in the
6、 concept of energy benchmarking. The energy use intensity (EUI) continues to be a very common metric for bencharmking commercial office building with an EUI of 25 kBTU/yr-gsf (78.9 kwh/yr-gsm) would be considered low-energy. Energy use intensity can often mask poor performance, as the metric does no
7、t explicitly capture the impact of a partially occupied building or a building with a low net-to-gross floor area ratio. Low-energy buildings require the participation of an engaged occupant group to realize process energy use savings. Yet, there is also a need to achieve energy efficiency without c
8、ompromising user productivity. Benchmarking often starts with an energy use intensity target, either determined using the EPAs ENERGY STAR Target Finder or based on the Architecture 2030 challenge framework. What if targets were instead built up starting with a buildings process load? Although there
9、 is some movement within ASHRAE Standard 90.1 and Californias state energy code (T24) to regulate control of these loads, these loads have often been considered unregulated, leaving them to be a point of focus later in a design process than they should be. Based on a recent high-performance building
10、 project, the design team found that ASHRAE standard utilization schedules had poor correlation to measured process load energy use profiles (Chang 2014). When tenants were questioned about their use, the reaction resulted in unintended consequences, including frustration over being encouraged to re
11、duce the energy use of equipment that simply could not be further reduced, without compromising function. This interaction with tenants over an 18-month period inspired a new way of thinking about energy use. What if design teams also focused on a building level coefficient of performance, in additi
12、on to EUI? EUE METRIC DEFINITION The proposed metric is termed energy usage effectiveness (EUE). This consists of the ratio of building energy use divided by process energy use. This metric has similarities to the Power Usage Effectiveness (PUE) metric used for data centers (Avelar 2012), but with t
13、he intent of broader application to a wide range of commercial buildings. The intent is to provide a greater focus on annualized energy use, rather than power demand. *Some debate may occur over what should be counted as process energy use. For example, elevators, escalators,and lavatory service hot
14、 water could be interpreted as not directly contributing to the core function of a commercial entity. The EUE can be used to start setting targets for a range of buildings, with an emphasis on office buildings. It is conjectured that this methodology is not as suitable for building types with a sign
15、ificant amount of ventilation driven process requirements, such as hospitals, restaurants, and laboratories. The EUE metric is intended to capture demand reduction measures; on-site renewable energy production would be excluded from the metric. TEST CASES Exploration of the EUE concept was performed
16、 using data developed by the Department of Energy for commercial reference buildings (http:/energy.gov/eere/buildings/new-construction-commercial-reference-buildings). The DOE has provided EnergyPlus modeling results for 16 reference building types situated in 16 ASHRAE climate zones. Data is availa
17、ble for three vintages of construction: New Construction (90.1-2004), post- 1980, and pre-1980. The intent was to determine correlations between EUE and EUI and determine a reasonable range for EUE across the 16 building types available. The following hypotheses were made: EUE values would be lower
18、for a building type/vintage in less extreme climate zones. While climate normalized data is often referenced, it generally makes sense that it is more energy intensive to operate a building in certain climate zones. The PUE concept for data centers has shown the incredible benefits of building these
19、 centers in climates with a significant amount economizer cooling hours (High-Performance PUE = 1.0 to 1.2).Total Interior Process Energy Use Typical Items: Computers, Printing Equipment, Machine Tools, Medical Equipment, Specialty Lighting* Total Interior Building Energy Use Regulated by ASHRAE Sta
20、ndard 90.1 (Enclosure, Lighting, Service Hot Water, HVAC) + Process Energy EUE values would generally be highest for pre-1980s era construction and lowest for new construction. There would be a correlation between EUE and EUI, with a fixed process load. EUE is better suited for office and education
21、building types, where ventilation driven processes are non-dominant.The data generally aligns with the hypotheses, as presented in Figures 1 to 4. 0123456EUEEUE (2004) EUE (1980) EUE (Pre-1980)Figure 1 EUE for All Climate Zones for Medium Size Office Building (ASHRAE 90.1-2004). The data shows a gen
22、eral decrease in EUE going from an older to a newer building vintage. 0100200300400500600051015202530AveragedEUI(kBTU/yr-gsf)AveragedEUE2004 EUE Post 1980 EUE Pre-1980 EUE 2004 EUIFigure 2 EUE For All Building Types and Vintages (Non-Weighted Average Across All Climate Zones). This data generally sh
23、ows a challenge with applying EUE to Warehouses and Retail facilities, given a high interior lighting power demand or limited traditional process load. EUI (SI units, kwh/yr/gsm) = EUI (IP units) x 3.15. 0510152025303540450 100 200 300 400 500 600 700 800EUEEUI (kBTU/yr-gsf)83BClimate Zone (Lowest E
24、UI)Climate Zone (Highest EUI)Figure 3 EUE versus EUI (ASHRAE 90.1-2004). Given a fixed process load, the EUE shows a linear relationship with EUI, across 16 individual models (4 are plotted) covering the primary ASHRAE climate zones. This figure focuses on the 4 building types with either high overa
25、ll EUI or EUE values, outside the range of a typical commercial office building. EUI (SI units, kwh/yr/gsm) = EUI (IP units) x 3.15. 0123456789100 10 20 30 40 50 60 70 80 90 100EUEEUI (kBTU/yr-gsf)Figure 4 - EUE versus EUI (ASHRAE 90.1-2004). The following building types generally show a consistent
26、relationship between EUI and EUE (slope-function): Multi-Family, Secondary School, Primary School, Small Office, Medium Office, Large Office, Large Hotel, Hospital. This figure shows a zoomed-in view of EUI in the range of typical commercial office buildings. EUI (SI units, kwh/yr/gsm) = EUI (IP uni
27、ts) x 3.15. APPLICATION EUE may be utilized for preliminary design target setting. Assume that a building has an average process load of 0.5 W/sf over a typical year. This would equate to a process load EUI of 15 kBTU/yr-gsf (47.3 kwh/yr-gsm). A building with an EUE of 3.0 would theoretically not be
28、 able to have an overall EUI any lower than 45 kBTU/yr-gsf (142 kwh /yr-gsm). This simple metric allows for realistic targets to be set, before any energy modeling is performed, within a typical building type for a defined ASHRAE climate zone. The National Renewable Energy Laboratory has developed g
29、ood guidance on evaluating process loads, based on daytime and nighttime demand for one of their high-performance office buildings (Lobato 2011), which could be used in conjunction with EUE ranges to set targets for buildings both during design and operation phases. A sample of past case studies was
30、 evaluated to contrast EUI to EUE. This is not intended to be an exhaustive evaluation, given the coarse nature of the data used, but is intended to generate discussion about the relationship between process loads and overall building energy use for buildings at the forefront of energy use efficienc
31、y. In these case studies, the calculated EUE was typically under 3.0. The sample set primarily included office buildings and K-12 schools, mostly in ASHRAE Climate Zone 5B or 4C. Table 1: EUI to EUE Comparison (ASHRAE HPB) Project Climate Zone Building Type Area sf EUI kBTU/yr-gsf EUI kwh/yr-gsm EUE
32、 Wayne Aspinall Federal Building 5B Medium Office 41,562 (3,861 m2) 21 66.2 2.9 Exploratorium 3C Museum 190,000 (17,658 m2) 50 157.5 2.9 PNC Bank 1A Stand-Alone Retail 4,620 (429 m2) 36.6 115.3 3.3 Portland Community College Newberg Center 4C Higher Education 13,500 (1,255 m2) 33.2 104.6 2.4 Federal
33、 Center 1202 4C Large Office 188,587 (17,527 m2) 25.7 81.0 4.1 St. Martens University Cebula Hall4C Higher Education 26,900 (2,500 m2) 18.2 57.3 1.9 Gateway West 6A Medium Office / Warehouse 34,000 (3,160 m2) 41.8 131.7 15.5 Oberlin College Lewis Environmental Center 5A Higher Education 13,600 (1,26
34、4 m2) 32.9 103.6 4.5 NREL RSF 5B Large Office / Data Center 220,000 (20,446 m2) 35.4 111.5 1.8 Gettysburg Museum 5A Museum 140,000 (13,011 m2) 228 718.2 2.6 CONCLUSION The concept of energy utilization effectiveness (EUE) warrants additional research, coupled with actual data from a wider range of p
35、rojects, both typical and high-performance. This concept can be utilized for early design stage benchmarking and target setting, as well as evaluation of performance during measurement and verification processes. An EUE of 1.0 provides an interesting stretch target for building projects, as this ess
36、entially represents a building with no regulated energy use, such as for lighting or HVAC systems. For an increasingly mobile workforce reliant on smartphones and tablets, working outdoors in a park would equate to an EUE of 1.0 and provide an alternative contextfor building energy use goal setting.
37、 Ultimately, the intent of the EUE metric is to encourage development of buildings that support productive contributions to society, with the lowest amount of resource use possible. As data analytics continues to gain industry interest, integrating EUE forecasting with research work that relates occ
38、upancy to process load use (Zhao 2013) would allow for enhanced building benchmarking. NOMENCLATURE Only Imperial Units are provided in this document, due to the nature of the study based on United States centric projects and benchmarking data. EUE may be utilized for projects using the metric syste
39、m by ensuring consistent units for energy (kwh) and area (square meters). ACKNOWLEDGMENTS Id like to extend my gratitude to the ASHRAE HPB advisory committee and editorial staff for informally peer reviewing this research paper. Id like to acknowledge Jason Sielcken and the General Services Administ
40、ration for providing the inspiration and project experience that shaped the foundation of this research work. REFERENCES Avelar, V., Azevedo, D., French, A., PUE: A Comprehensive Examination of the Metric, 2012. ASHRAE, High-Performance Building Magazine, Multiple Issues (Summer 2011, Winter 2011, F
41、all 2012, Winter 2013, Fall 2014, Spring 2014, Summer 2014, Spring 2015, Winter 2015). Chang, R., Landmark Resurrection, ASHRAE High-Performance Building Magazine, Summer, 2014. Lobato, C., Pless S., Sheppy M., Torcellini. Reducing Plug and Process Loads for a Large Scale, Low Energy Office Building: NRELs Research Support Facility, ASHRAE Winter Conference, 2011. Zhao, J, Yun, R., Lasternas, B., Wang, H., Lam, K.P., Aziz, A., Loftness, V., Occupant Behavior and Schedule Prediction Based on Office Appliance Energy Consumption Data Mining, CISBAT, 2013.
