SectorEstablished BaseEnergy Consumption PCsRegression Model + Intuition (w/o ref. but with middle checkpoints) Regression Model + Intuition (w/o ref.)

Sector Established Base Energy Consumption

PCs Regression Model + Intuition (w/o ref. but with middle checkpoints)

Regression Model + Intuition (w/o ref.)

Data Centers Regression Model Regression Model

Mobiles Regression Model + Intuition (w/o ref.)

Intuition (w/o ref.)

Gaming Consoles + TV Regression Model + Intuition (w/o ref.)

Regression Model + Intuition (w/o ref.)

3-5 Historial Data Points

5+ Historial Data Points

1-3 Historial Data Points

Types of Regression Models• Following types of regression models were considered

– Logarithmic – ln(x)– Linear – ax+b– Quadratic – ax2+bx+c– Polynomial – a1xn + a2xn-1 + .. + anx + c

– Power - abx

– Exponential - aex

– Combination of above families

Example of Regression Models

Exponential

Polynomial

Linear

Power

Logarithmic

Important Assumptions on PC Sector

The PCs sector was divided into two main sectors: Desktop PCs Laptop PCs

Percentage share of each sector was in accordance with the Smart2020 report In 2002,

─ desktop had 84% of market share─ Laptops had 16% of market share

By 2020, ─ laptops taking 74% of market share ─ Desktops have 26% of market share

linear increase in use of laptops was assumed

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Established Base


PC sales numbers from Gartner are used to estimate the established base Needs an accurate estimate of PC life cycle to get the established base

Three scenarios showing the life cycle of PCs are obtained 3-year “typical” life cycle as mentioned in Gartner news release 4-year life cycle derived from Gartner’s “1.1 Billion PCs in Use in 2008” statement 5-year life cycle for laptops and 6-year life cycle for desktops as mentioned in “European

Commission DG TREN : Personal Computers (desktops and laptops) and Computer Monitors─ Can be obtained at www.ecocomputer.org

Plugging in the recent data (2009 and 2010(est.)) from Gartner Inc. gave different estimates than before

Estimating PC life cycle as 3 or 4 years gave surprisingly low estimates even with the most aggressive curve fit (exponential growth)

─ 2.75 Billion PCs in 2020 for 3 year life cycle─ 3.6 Billion PCs in 2020 for 4 year life cycle

Estimating PC life cycle of 5 years gave the most reasonable estimate of PC established base─ Closely matches Smart2020 established base prediction of 4.067 Billion PCs by 2020

• A reasonable 50% PC penetration by 2020 4.3 Billion PCs in 2020

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Established Base Computation – Case I


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3-Year Life Cycle

4-Year Life Cycle


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5-Year Life Cycle


Internet Users numbers from CIA World Factbook to derive PC established base Assume number of internet users to reflect PC base closely

─ Non-internet connect PCs and sharing of PCs cancel each other out maybe?─ Only 3 world data points but gives very good curve fit as the data points are spread over a long period

• 2002, 2005 & 2008 years estimates

Gives an estimate of 5.75 Billion Pcs by 2020

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Established Base Computation – Case II


To estimate the energy consumption of a PC, its operation was divided into 3 different modes: Active mode – when PC is on and CPU is functioning Sleep mode – when CPU is on standby Off mode – when CPU is off but is plugged into the socket

Usage patterns for different modes of operation are obtained from TIAX from the report submitted to the US Dept. of Energy.

The usage pattern values was based on data of year 2005─ Lower bound estimate that usage in future years will be at least as much as 2005 was made

Sleep & Off modes power consumption from the ENERGY STAR ratings The latest energy star ratings was used to define the lower bound on sleep and off mode power consumption

─ All PCs are assumed to satisfy Energy Star ratings

As the top 5 models PC power numbers weren’t available, the active PC power consumption of some popular models listed in following websites was used

Univ. of Pennsylvania, Information Systems and Computing Apple Energy and Environment website White paper “Review of Computer Energy Consumption and Potential Savings” sponsored by Dragon Systems

Software Limited. Note: Lowest values of power consumption were taken

─ for having lower bound estimates for the energy consumption

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Energy Consumption


All the power consumption analysis was done independently for desktops and laptop PCs

decrease in power consumption of desktops – polynomial fit─ in accordance with the historical trends observed

Two curves showing both increase and decrease in power consumption of laptops – polynomial fit

─ Ambiguous historical data in which some models have increased energy consumption while some show a slight decrease

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Energy Consumption

Important Assumptions on Data Center Sector

Established base numbers till 2020 were extrapolated based on Gartner and Koomey’s reports

Matched Smart 2020 report’s extrapolated establised base numbers

A linear increase in energy consumption of data centers was assumed As opposed to Smart2020’s view of no increase in energy consumption Equal energy consumption for running and cooling the data center was assumed for all

extrapolations─ In accordance with assumption by Koomey et al.

Half the energy consumption of data centers is assumed to be from electronics usage The other half is by cooling

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Energy Consumption

Established Base

Important Assumptions on Mobile Sector

Only mobile devices have been considered in this study Other telecom devices not considered

─ Like IPTV boxes, broadband modems

Telecom infrastructure was not considered

Extrapolations using curve fitting were done based on the historical data of Gartner Inc. Life cycle of a mobile phone was assumed to be 3 years 2009 data from Gartner was used as well Best regression model gives an estimate of 6.5 Billion established mobile base by 2020

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Established Base Computation – Case I


Extrapolations using curve fitting were done based on the data from CIA World Factbook.

Best regression models give an estimate of 20-50 Billion established mobile base by 2020 Two reasonable fits were found

─ Linear model gave 11 Billion established base─ Power model gave 7.3 Billion established base

To decide on the growth trends, the basket approach was used─ Was not conclusive

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Linear Regression


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Power Regression


OECDUSAUKJapanFranceAustralia

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“Basket” Approach

Under DevelopedZimbabweCongoAfghanistanSomaliaNigeria

DevelopingBrazilRussiaIndiaChina

Best Fit - Polynomial

Total established base for these countries is 12

Billion by 2020!!


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“Basket” Approach

Linear Fit – 97.2% accurate

Power Fit – 91.2% accurate

Total established base for these countries is 5.5 Billion by 2020

Not Conclusive

!


For the mobile phone power consumption Energy consumption of a device is equal to the battery energy storage capacity

─ Different values based on charging frequency were given• lower bound estimate: charging once in two days• Average estimate: charging once a day• Higher bound estimate: charging twice a day

─ Doesn’t impact the total values by much as Mobile sector energy consumption is negligible compared to other sectors

Popular Nokia models were only considered for obtaining the energy consumption per device─ As most of the similar cellphones have the same battery capacity

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Energy Consumption

Important Assumptions on Gaming Sector

Extrapolations using curve fitting were done based on the historical data of NPD group and VGChartz

A quadratic increase in established base is assumed─ Gives a reasonable 700,000 game consoles by 2020

Number of televisions is same as the video game consoles in that year─ As televisions are assumed to be used with gaming consoles in our analysis

Power consumption values were obtained from: The Energy Saving Trust, “The ampere strikes back”

─ Detailed power consumption of various popular gaming consoles─ Different modes of power consumption

Projections to power consumption were assumed to increase logarithmically─ Gave a reasonable 250 watts per device by 2020─ Linear increase gave unreasonably high 800Watts per device by 2020

Usage statistics of gaming device was obtained from Consumer Electronic Association (CEA) Alternate scenarios with higher gaming device usage will be plotted as well

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Energy Consumption

Established Base

Important Assumptions on Gaming Sector

Weighted average of the different gaming consoles based on their market share was done to obtain the energy consumption per device

─ Different power modes were considered

Television power consumption was based on ”Efficiency standards for televisions”, California Energy Commission, 2008.

Television power consumption is assumed to be decreasing over the years─ An constant average TV screen size 26” is taken for all extrapolations

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Energy Consumption

Our Projections on Total Energy Consumption of ICT Sector

2008 2012 2020

Data Centers 192.676 326.7 695PCs 354.11 493.34 1015.28Mobile 6.215 11.096 30.55Gaming Consoles & TV 52.6 117.8 418.6Total 605.601 948.936 2159.43

EIA 2008 2012 2020

Total Electricity consumption

19,460 22,010 27,500

Total energy consumption in (billion KWhrs/yr)

IT % of total 3.11% 4.31% 7.85%

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Will be updated based on

case choice

Our Projections on Carbon Footprint of ICT Sector

2008 2012 2020(Our)

2020(Smart2020)*

Conversion Factors:(1KWhr of electricity = ? lbs of

CO2) 1.306 1.27 1.238 1.44

Data Centers 114.3795 188.595 391.0955 259

PCs 210.2126 284.7917 571.3257 500

Mobile 3.68945 6.405418 17.19132 10

Gaming Consoles 31.22527 68.00273 235.5576 -----

Total 359.5068 547.7949 1215.17 769

Total carbon footprint in (Mega tonnes of CO2)

IT % of total Carbon Cap (14.5 Gt of CO2 per year) 2.48% 3.78% 8.38% 5.3%

*Embodied carbon & Telecommunications Infrastructure has been ignored in this analysis

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Will be updated based on

case choice

Documents

SectorEstablished BaseEnergy Consumption PCsRegression Model + Intuition (w/o ref. but with middle checkpoints) Regression Model + Intuition (w/o ref.)