Scanning the Horizon of Energy Performance Rating Approaches Michael MacDonald Oak Ridge National Lab ASHRAE Winter Mtg, 2002

Range of Approaches Subjective subset, e.g., BREEAM (BRE) Objective subset with some proxies, e.g., LEED (USGBC) Objective, empirical ranking by building type, e.g., Energy Star commercial (EPA) Objective, empirical ranking across sector, e.g., Home Energy Yardstick (EPA)

Subjective Approach General categories such as: Building Envelope and Systems and Operation and Management Scoring depends on judgment of an “expert” Scoring also depends on any sub-categories used under the major categories and the weighting (max score) of each

Objective Approach Mix of empirical and proxies Weights of categories affect scoring Range and mix of categories affects scoring Increased empiricism should improve results (proxies show lack of data) Proxies may be somewhat subjective ASHRAE Std 90.1 being used as a proxy

Empirical Methods Actual data required – if estimated, estimating methods must be trusted Specific rankings then allowed Decisions on allowable data still required Decisions on weighting may still be needed Segmentation issues, e.g., by building type or cross-sectoral

Rating Progression Energy use is inherently empirical, so empirical rankings are by nature more appropriate (meaning subjectivity should be limited) Objective proxies may still be questionable Ratings of both designs and actual performance of buildings of interest to ASHRAE

Design Performance Rating Many attempts to use ASHRAE Std 90.1 in methods to rate energy performance of building designs Of most import is perhaps the notion of using a barely compliant building as a reference point for obtaining relative scores

Design Rating Issues With so many efforts and changes occurring on a frequent basis, some increased level of specificity, e.g., an ASHRAE Guideline, would be desirable Without ASHRAE leadership, those making changes will assume increased leadership, while ASHRAE may lose leadership position

Initial Energy Data

Initial Cost Data

Initial Energy-Product Data

Example Rating Data

Performance Scoring

Cross-Sectoral Ratings Enter your home's size, age, ZIP code and the number of people who live there. Enter the amount and cost of energy your home used during a 12-month period. Check your score on the rating tool Compare Your Home's Energy Performance

Example Commercial Sector Prediction = log-based fractions are from zero to one 5.55 = Intercept x natural log of sq ft per worker 0.47 x fraction of space heated 0.10 x fraction of space cooled 0.21 x open Mon-Fri, '0' or '1', is '1' if open Sat and M-F 0.01 x hours per week open x Annual heating degree days, base 65F x Annual cooling degree days, base 65F 0.96 x fraction of area that is food sales (grocery) 0.56 x fraction of area that is restaurant x fraction of area that is worship space x fraction of area that is non-refrigerated warehouse 0.42 x fraction of area that is laboratory 0.06 x fraction of area that is office / professional 0.33 x fraction of area that is lodging / dorm 0.48 x fraction of area that is refrigerated warehouse

Conclusion Building energy performance rating systems, both for designs of new buildings and for existing buildings are beginning to have an impact ASHRAE is currently not a leader here Future ASHRAE leadership in building energy performance areas may depend on addressing both design and actual energy performance rating system approaches