2 Why Care About Building Energy Performance?  Aside from building energy increasing?  Ignoring performance ratings is choosing to fly fairly blind — staying at the “dumb” end of the “dumb and dumber” scale  Performance ratings are an evaluation, quickly, and not an investigation

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6 New Construction has been a problem for 50 years, increasing carbon footprint   2003 CBECS data with malls, kBtu/sq-ft-yr weighted means, higher source energy EUIs in newer buildings   CBECS data show same pattern with each survey year, life-cycle influences are shown

7 Basic Energy Benchmarking (Performance) Info  Go to TC 7.6 website (shown on title slide previously)  Select Program Activities at bottom  Chicago 2006, Seminar 17, first presentation  Atlantic City 2002, Seminar 41, first two presentations

8 Current ASHRAE High-Performance Protocol Project  “ASHRAE needs to provide guidance regarding the measurement and reporting of the performance of new and existing [commercial] buildings....”  “... to further the development of building energy performance standards.”  “Measuring and Reporting the On-site Performance of Buildings...”

9 ASHRAE STANDARD to now  BSR / ANSI / ASHRAE Standard (RA99) covers measurement and expression of building energy performance at a basic level, with suggested optional extensions  Standard 105-[2007?] is a major revision and has been submitted for publication. It extends the coverage of energy performance measurement and expression, and comparison of building energy performance against others  The nature and level of performance comparison requires some performance “standard” and requires or intrinsically offers some evaluation

10 Standards of Comparison 1.Minimum prescriptions or best practice levels (Stds 90.1, 90.2, 189P, LEED) 2.Self-reference, e.g., past and future 3.Ad-hoc building populations 4.Representative populations, e.g., CBECS, RECS for USA and CEUS for CA

Applications Handbook Energy Comparisons using CBECS  Chapter 35, energy management, 3 tables on commercial buildings  Based on 2003 CBECS micro-data without malls  About 50 building types  Site energy use indexes for mean and percentiles 10, 25, 50, 75, and 90  Electricity and cost indexes at same detail

12 Commercial Buildings Energy Consumption Survey, CBECS  Latest survey micro data available = 2003, next is 2007 (released in 2010?)  Publicly available government reports and data on EIA website  Nationally representative sample, with fairly complicated cluster sampling frame  Different versions have been available, ~5,000 records  Not including imputation flags, there are ~350 data parameters  Data seem to get better each time

13 CBECS and CEUS, some important differences ItemCBECS 2003CEUS 2003 Survey approachPhoneSite, skilled Unit of interestOne building, even if a campus Site, including campuses Characteristics detailLimitedVery detailed Floor area limits due to masking < 1,000,000 sq ft for valid data No limit, but not over 2M here Fuel data limitationsPropane data coarseOnly gas and electric real Simulated or regressed end uses NoneSimulated Fuel cost dataAnnual by fuelNone Fuel data intervalsAnnual onlyMonthly

14 Basic EUI Statistics kBtu/sq-ft per yr Quantity, all weightedCBECS 2003 N = 4678 CEUS 2003 N = 2360 Mean th percentile th percentile Median th percentile th percentile449521

15 Floor Area Distributions, Sq Ft Quantity, all weightedCBECS 2003 N = 4738 CEUS 2003 N = 2360 Mean14,3528, th percentile th percentile Median th percentile th percentile ,960

16 Week Schedule, hr/week open Quantity, all weightedCBECS 2003 N = 4360 CEUS 2003 N = 2360 Mean th percentile th percentile4045 Median50 75 th percentile th percentile16898

17 Worker Density workers per 1,000 Sq-ft Quantity, all weightedCBECS 2003 N = 4360 CEUS 2003 N = 2352 Mean th percentile th percentile Median th percentile th percentile

18 Density of PCs PCs per 1,000 Sq-ft Quantity, all weightedCBECS 2003 N = 4360 CEUS 2003 N = 2127 Mean th percentile th percentile Median th percentile th percentile

19 Rough-cut, Incomplete Regression Models, weighted Parameter coefficient >> intercepts not signif. CBECS 2003 N = 4300 CEUS 2003 N = 2352 EUI change per hr/wk EUI change w/ worker density Lab, change in EUI from average 386NS Offices– 52– 49 Clinics– 42– 33 Restaurant Fast Food Average EUI245179

20 Not done fishing yet