1. Environmental Energy Technologies fridayforum020531.ppt The End-Use Forecasting Group: Who we are and what we do Jonathan G. Koomey JGKoomey@lbl.gov, 510/486-5974, http://enduse.lbl.gov/ Talk is on the web at http://enduse.lbl.gov/shareddata/fridayforum020531.ppt Friday Forum Lawrence Berkeley National Laboratory May 31, 2002

2. Environmental Energy Technologies fridayforum020531.ppt Who we are  LBNL’s End-Use Forecasting (EUF) Group established in 1991.  Core team includes Rich Brown, Bill Golove, Etan Gumerman, Greg Homan, Jon Koomey, Kathryn McCarthy, Marla McWhinney, Mithra Moezzi, Maggie Pinckard, Judy Roberson, Carla Rose-Holman, Alan Sanstad, Osman Sezgen, Carrie Webber, Tom Wenzel  Staff from other groups work with us regularly: Bart Davis, Karen Herter, Alan Meier, Evan Mills, Bruce Nordman, Jeff Warner  Funding almost exclusively from EPA.

3. Environmental Energy Technologies fridayforum020531.ppt Selected projects  5-lab (1997) and Clean Energy Futures Studies (mid-Nov 2000)  Tax credits analysis - Climate Change Technology Initiative (1997)  Energy Star technical support for program decisions (includes work on new products)  Energy Star (E*) impacts calculations for CCAP  Scenario analysis tools (e.g. NEMS, BEAST, other spreadsheet tools)  Information technology and resource use  Data collection/measurements for E* office equipment, consumer electronics, and other products (ongoing)  Home Energy Advisor/Home Energy Saver  Peak demand/screening curves  Conservation supply curves  Debunking of urban legend about office equipment electricity use  Collecting measured data on server farm power use.

4. Environmental Energy Technologies fridayforum020531.ppt How do we continue to be effective?  By thinking ahead: Understand EPA’s needs and be proactive in meeting them.  By relying on data: confront speculation with measurements, avoid obsessions with models and computer tools.  By being complete, accurate, and thorough: produce well- documented and well-constructed analysis focused on real decisions.  By being fast: get a credible answer in the time allotted  By being translators: draw on detailed technical work from other research (e.g. appliance standards analysis)  By being recognized: publish in peer-reviewed journals.  By being interdisciplinary: (fields include engineering, economics, statistics, architecture, energy and resources, and others).

5. Environmental Energy Technologies fridayforum020531.ppt Home Energy Saver/Advisor Sites http://hit.lbl.gov and http://hes.lbl.gov

6. Environmental Energy Technologies fridayforum020531.ppt Standby power for TVs Source: Karen Rosen, LBNL, May 1999, KBRosen@lbl.gov Share of units measured

7. Environmental Energy Technologies fridayforum020531.ppt How do tax credits work? Source: LBNL analysis of administration’s CCTI tax credits, memo dated 13 Feb 1998. http://enduse.lbl.gov/Projects/TaxCredits.html

8. Environmental Energy Technologies fridayforum020531.ppt Scenarios of U.S. Carbon Reductions Potential Carbon Savings from High-Efficiency Low Carbon Case in 2010

9. Environmental Energy Technologies fridayforum020531.ppt Market Imperfections: Efficient Magnetic Ballast Market Shares

10. Environmental Energy Technologies fridayforum020531.ppt CA Households per MW of Capacity Source: CEC; 1999 data

11. Environmental Energy Technologies fridayforum020531.ppt Electricity used by the Internet Source: LBNL-44698

12. Environmental Energy Technologies fridayforum020531.ppt local distribution lines to the building, 480 V HVAC system lights, office space, etc. UPSPDUcomputer racks backup diesel generators Electricity Flows in Data Centers computer equipment uninterruptible load UPS = Uninterruptible Power Supply PDU = Power Distribution Unit;

13. Environmental Energy Technologies fridayforum020531.ppt Additional research areas  Tom Wenzel--analysis of automobile emissions testing  Bill Golove--Technical support to clean energy projects  Alan Sanstad--Forecasting and divisia analysis

14. Environmental Energy Technologies fridayforum020531.ppt Lessons learned from the evaluation of vehicle inspection and maintenance programs Tom Wenzel Friday Forum Lawrence Berkeley National Laboratory May 31, 2002

15. Environmental Energy Technologies fridayforum020531.ppt Evaluation of I/M Programs  Use multiple data sources to evaluate programs — test result records — roadside remote sensing emissions measurements — vehicle registration data  Analyses of CA and AZ programs  Findings incorporated in — report of NRC panel on vehicle emissions modeling — report of NRC panel on I/M program evaluation — forthcoming EPA guidance to states on program evaluation  Find out more at: — http://eetd.lbl.gov/LabOnlyWS/Intranet/Archives/DivRev02/wenzel.p df

16. Environmental Energy Technologies fridayforum020531.ppt Theoretical I/M Program 01234 Year Average Emissions of Given Fleet emissions increase without I/M repair emissions increase after I/M

17. Environmental Energy Technologies fridayforum020531.ppt Lessons Learned about Actual I/M Programs 01234 Year Average Emissions of a Given Fleet emissions increase without I/M repair emissions increase after I/M actual emissions increase after I/M

18. Environmental Energy Technologies fridayforum020531.ppt Technical Support to Clean Energy Projects William Golove Friday Forum Lawrence Berkeley National Laboratory May 31, 2002

19. Environmental Energy Technologies fridayforum020531.ppt Project Areas  USPS — Building energy consumption management s Shared Energy Savings (SES) contract (1600 bldgs) s CEC demand response (24 plants) s Consumption tracking and goals (2000+ bldgs, 10 districts) — On-site generation s Marina PV (largest federal building intergrated system) s San Bernardino natural gas s Chiquita Canyon LFG to electricity — Renewables s Largest federal direct access purchase (4.7MW)  USDOE — Assistance to federal agencies (Air Force) in purchasing renewables — Assistance to Public Renewables Partnership (PRP)  USAID — ProForm

20. Environmental Energy Technologies fridayforum020531.ppt Chiquita Canyon Landfill Gas project (2MW)  USPS received offer of $0.14/kWh for 10 year firm delivery of electricity from LFG  Requested assistance with evaluation and negotiations from LBNL  Initial analysis looked at 15 yr project because of tax depreciation/residual value issue; completing 10 yr analysis  Found electricity prices should range between 5.0 to 7.1 cents/kWh at 20% after tax return on equity  Substantial additional cost uncertainties exist, including: exit fees, standby charges (energy and capacity), ancillary services and grid management fees, and historic procurement charges (total 3 – 8 cents additional)

21. Environmental Energy Technologies fridayforum020531.ppt Retrospective on long-term energy forecasts, and divisia decomposition of recent trends Alan Sanstad Friday Forum Lawrence Berkeley National Laboratory May 31, 2002

22. Environmental Energy Technologies fridayforum020531.ppt Retrospective evaluation of long-range energy projections (Sanstad, Laitner and Koomey 2001)  How well have energy models performed?  We examined five studies conducted in 1982-3, focusing on projections (U.S.) to year 2000  Characteristic pattern: reasonably accurate demand forecasts but dramatic over-estimation of energy prices

23. Environmental Energy Technologies fridayforum020531.ppt U.S. energy demand, 1982-2000: Five projections, and actual (Median year 2000 error: -5.2%)

24. Environmental Energy Technologies fridayforum020531.ppt World oil price, 1982-2000: Five projections, and actual (Median year 2000 error: +197%)

25. Environmental Energy Technologies fridayforum020531.ppt Estimated GDP losses from 15% energy tax in year 2000: Median and perfect hindsight model predictions

26. Environmental Energy Technologies fridayforum020531.ppt An index analysis of recent changes (Davis, Sanstad, Koomey 2001)  Focus: post-1996 acceleration of E/GDP and C/GDP declines.  The EIA says: "It was the weather."  Our approach to testing this: Weather-corrected Divisia index decomposition of changes in primary fossil energy use-to-GDP ratio  Conclusion: Weather accounts for about one-half the acceleration

27. Environmental Energy Technologies fridayforum020531.ppt Fuel mix and weather effects on energy and carbon intensity