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Estimating electricity use “associated with the internet”: A cautionary tale

Estimating electricity use “associated with the internet”: A cautionary tale. Jonathan Koomey, Ph.D. Lawrence Berkeley National Laboratory JGKoomey@lbl.gov, 510/486-5974, http://enduse.lbl.gov/ For more details on the analysis discussed here, go to

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Estimating electricity use “associated with the internet”: A cautionary tale

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  1. Estimating electricity use “associated with the internet”: A cautionary tale Jonathan Koomey, Ph.D. Lawrence Berkeley National Laboratory JGKoomey@lbl.gov, 510/486-5974, http://enduse.lbl.gov/ For more details on the analysis discussed here, go to http://enduse.lbl.gov/projects/infotech.html Download: http://enduse.lbl.gov/shareddata/internetdatatalk001106.ppt Presented in Sydney, Australia November 15, 2000

  2. Beware false premises The fascinating impressiveness of rigorous mathematical analysis, with its atmosphere of precision and elegance, should not blind us to the defects of the premises that condition the whole process. There is perhaps no beguilement more insidious and dangerous than an elaborate and elegant mathematical process built upon unfortified premises. --T. C. Chamberlain-- Translation: Garbage in, Garbage out

  3. Background • The Internet Begins with Coal, by Mark Mills, was published in Forbes in May 1999. • Results were widely cited. • Memo to EPA dated 9 December 1999 was our response (http://enduse.lbl.gov/Projects/InfoTech.html). • Congressional testimony given by Mills, Jay Hakes, and Joe Romm on 2 February 2000.

  4. Mills’ analysis was flawed • Bad data: 1-2 kW PCs, 500 kW central offices, 250 kW mainframes, confusion of web sites and servers. • Bad boundary definitions: Just what part of a PC or a server is “associated with the internet”, anyway? • Overlooked systemic effects: information tech. can affect the efficiency of many processes.

  5. Mills’ electricity “used by the internet”, corrected by LBNL TWh per year

  6. Data needs • Equipment sales • Power use (W) by operating mode • Usage (Hours) by operating modes • Equipment stocks (estimate using sales and lifetimes, and/or assess using surveys) • Materials use, reuse, and recycling • Estimate energy use and emissions • Systemic effects (e.g., telecommuting, e-commerce)

  7. Latest estimate of office equipment electricity use by sector in 1999 Network 4% Residential 12% Industrial 13% Total = 74 TWh Commercial 71% http://enduse.lbl.gov/Projects/InfoTech.html

  8. Comparison of Estimates of Energy Use for Commercial Office Equipment in 1999 Printer Desktop/Portable/Server Computer Display/Terminal Annual Energy Use (TWh) Mainframe/Minicomputer Copier/Fax

  9. A key uncertainty: Data centers/server hotels • Some utilities receiving requests for tens to hundreds of MW of power from proposed data centers • Estimates for power use almost certainly too large • One facility maximum = 90 W/sf, actual <40W/sf. • Another facility claimed 65 W/sf, but floor area defined incorrectly to exclude aisles and other common areas, leading to an overestimate of power use (this definition is critical) • Still another facility took direct server load and multiplied by three (!) to account for cooling, lighting, and other uses (implies a COP of about 0.5, 3-4 times too low)

  10. Upper bound estimate to electricity used by data centers in the U.S (1) Floor area taken from Juarez, Richard A. 2000. Virtual Bricks II: Virtual Econ 101 Update: A Comprehensive Guide for Understanding eCommerce Infrastructure Evolution and Convergence. Boston, MA: FleetBoston Robertson Stephens Inc. May. (2) Power density is an upper bound based on recent discussions with experts. (3) Electricity use calculated assuming 8760 hours per year operation, flat load curve. (4) Total U.S. electricity use taken from EIA’s Annual Energy Outlook 2000. Contact: JGKoomey@lbl.gov, 510/486-5974.

  11. Possible systemic effects of information technology (IT) • Commercial floor space • Reduced office space • Reduced warehouse space • Changes in travel patterns • More efficient use of energy and materials • IT + utility deregulation = energy service markets for Enron

  12. Something unusual is going on Source: Joe Romm, Center for Energy and Climate Solutions

  13. The Information and Communication Technologies Diffusion Curve Where the economy seems to be right now Where most models seem to focus

  14. Conclusions • Misinformation seems to spread more quickly than truth. • Electricity used by computers and network equipment is at least a factor of eight smaller than Mills implies. • Understanding the systemic effects of information technology is critically important. • Credible data are urgently needed.

  15. Join the network for energy, environment, efficiency, and the information economy (N4E) http://n4e.lbl.gov

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