estimation of ict sector footprintsestimation of ict sector footprints anders s.g. andrae , huawei...

Estimation of ICT Sector footprints

Anders S.G. Andrae , Huawei & Peter M. Corcoran,

www.huawei.com

HUAWEI TECHNOLOGIES CO., LTD.

Anders S.G. Andrae , Huawei & Peter M. Corcoran, National University of Ireland, Galway

Author/ Email: Dr. Anders

Andrae/[email protected]

� Case study: Electricity footprint of the ICT

Sector 2012-2017

� Experience of Huawei

Contents

� Challenges related to estimating a Sector

footprint

� Possible ways to make the estimation

� Electricity as indicator for ICT

� The role of LCA in ICT footprint

estimations

Situation: ICT electricity usage, footprint case study

� Several investigatons of ICT Sector footprints, around

eight

� Explosive data traffic growth + Considerable efficiency

gains

� Common wisdom ”ICT Sector is ≈2% of global CO2e” is about to

HUAWEI TECHNOLOGIES CO., LTD. 3

change in the coming years?

� Target

� Changing electricity share of ICT Sector from 2012 to 2017

� Compared to GeSI SMARTer 2020

� 1) more scenarios 2) different scope 3) more transparency 4)

more details on PCs 4) more details on TVs&Peripherals

� Scenarios

Worst, Best, and Expected are presented

https://www.researchgat

e.net/publication/255923

829_Emerging_Trends_in

_Electricity_Consumption

_for_Consumer_ICT

Problems� What is the annual and global electricity footprint

of the ICT Sector?

� What is the share of ICT Sector of the total global

electricity footprint?

� How does the share change between 2012-2017?


� How does the share change between 2012-2017?

� Which Sectors of the ICT Sector are dominating

the electricity footprint?

� How do these Sectors change between 2012 and

2017?

SOLUTION� Previous work was studied and used as starting point. 2008-2012 is

rather well studied and documented by at least 7 other groups.

� A clear scope of the ICT Sector was set for Upstream(”LCA”)+Use:

� Client Devices: Desktops, Monitors (Screens), Laptops, Smartphones,

Tablets

� TV Devices: TVs, Game Consoles, Set-top Boxes, A/V Receivers, DVD/Blue-

Rays


Rays

� Networks (CPE, Core Network, Office Networks, Networks between Data

Centers, and WiFi Access, Wired Access, Wireless Access)

� Data Centers (data processing, storage and HVAC infrastructures)

Data collected:

� Electricity usage in manufacturing and use,

� Shipped units, replacement rates, data traffic growth, energy saving and

growth.

Cut-off: network equipment in data centers

Devices� Device Use.

� Several investigations were studied to find typical electricity usages

� Different lifetimes were used to estimate the installed base

� Improvements in energy saving was included


� Device upstream

� Used LCA studies and other reports to arrive at the electricity/unit

� Improvement in energy saving year by year was included

� Market reports gave the global annual shipped units

Device electricity in TWhrs in 2012


Devices: Expected Growth Scenario 2012-2017 � TV sets growth

� Stagnating, 2.1 billion installed

� Desktop PCs and monitors

� Stagnating, (0.56 and 0.59 billion installed)

� Installed base of laptops

� growth rate CAGR 4.4% to around 1 billion


� Installed bases of smartphones and tablets

� grow 5% and 20% per year respectively

� Annual efficiency improvements

� for use electricity around 2% depending on the particular

device category.

� From 2008 on 5% annual improvement in manufacturing

electricity per unit

Device electricity in TWhrs in 2012-2017 for Expected Growth Scenario


Networks� Network Use.

� Includes”core” (core, metro, CPE, fixed) and mobile networks

(RAN).

� Started from others estimated (TWh) numbers from 2012

� Model includes Mobile traffic Data (EB/year) and % carried by LTE

� Model includes TWh/EB for mobile data and ”core” traffic

Model includes different improvements of the above TWh/EB


� Model includes different improvements of the above TWh/EB

� ”Core” IP incl. Data centers network traffic grows from 2600 EB/yr to

8500 EB/yr

� Mobile network traffic grows from 10.8 EB/yr to 134.4 EB/yr

� Network upstream

� Estimated from ”share of Use stage” as there were few reliable

markets statistics (except for base stations) for Network Equipment

Networks: Expected Growth Scenario 2012-2017 – Use stage 85%

� Data traffic

� LTE CAGR 2012-2017 109%, Non-LTE 51%

� LTE grows from 14% in 2012 to 45% in 2017 of Wireless Mobile Data

Traffic

� Core 26% CAGR of EB

� Energy efficiency

�”Core” Network 14% growth

rate for electricity from 2012

�“Wireless access” network


� Energy efficiency

� LTE 0.73 TWhrs/EB and Non-LTE (0.73/1.46=) 0.5 TWhrs/EB.

� ”Core” Network 0.14 TWhrs/EB

� Wireless LTE and non-LTE efficiency

� 5% annual TWh/EB improvement

� Core IP traffic: 10% year-on-year improvement in TWhrs/EB


grows to contribute 8.1% of total

Network electricity consumption

in 2017

Networks: Electricity in TWhrs in 2012-2017 for Expected Growth Scenario


Results&Conclusions: Annual footprint growth of ICT Sector

1,500

2,000

2,500

3,000

3,500

Best Case

Expected

Worst Case


� Best Case CAGR 1.8% which is below Global electricity CAGR of >2%

� Worst Case CAGR 13.1% which is a doubling in 5 years

� Expected Case is similar to Öko-Institute for EU27 from 2012-2020

1,000

1,500

2012 2013 2014 2015 2016 2017

Results&Conclusions: Share ICT Sector of Global electricity (with CAGR 3%)

8.0%

9.0%

10.0%

11.0%

12.0%

13.0%

14.0%

15.0%

Best Case

Expected Case

Worst Case


� Best Case decline from 7.8% to 7.4%

� Expected Case increase from 7.8% to 9.4%

� Worst Case increase from 7.8% to 12.5%

6.0%

7.0%

8.0%

2012 2013 2014 2015 2016 2017

Results&Conclusions: Change for Expected Case Scenario

Devices,

47%

Networks,

20%

Data

Centers,

15%

LCA, 18%Devices

Networks

Data Centers

LCA

Devices,

34%

Networks,

29%

Data

Centers,

21%

LCA, 16%

Devices

Networks

Data Centers

LCA


� 2012 � 2017

The trend is that there is a very little difference between the ratios of these components regardless of the growth scenario.

The combined contributions of networks & data centers willswitch place with direct electricity usage of end-user devices

Ways forward� Upstream facts

� Identification/agreement of the major Equipment which are the

ICT Sector

� Agreed Minimum and Maximum value/piece for the Upstream

”indicator values” of these Equipment


� Agree on the effect of including/excluding EoLT for the footprint in

Sector calculations

� Publications

� Peer reviewed academic publications apparently need extensive

review!

Thank youThank youwww.huawei.com

Copyright©2011 Huawei Technologies Co., Ltd. All Rights Reserved.The information in this document may contain predictive statements including, without limitation,

statements regarding the future financial and operating results, future product portfolio, new technology,

etc. There are a number of factors that could cause actual results and developments to differ materially

from those expressed or implied in the predictive statements. Therefore, such information is provided for

reference purpose only and constitutes neither an offer nor an acceptance. Huawei may change the

information at any time without notice.

ExperienceLife cycle assessments performed

› Radio Base Stations

› All sorts of mobile phones

› Tablets

› Metals

› FTTx Networks

› Radio Access Networks

› Cloud computing Networks

Sector analysis performed� ICT Sector with a defined scope

Possible ways to make the estimation• Shipped units

• Data traffic

• Intensity measures and their change over time

• Combine with LCA

• Focus on electricity and energy usage

Electricity usage as an indicator for ICT Sector environmental impact

• Advantages› Physical unit

› Statistics are abundants (IEA, etc.)

› High research interest for electricity markets LCA

› LCA studies often report electricity

› Most important energy form for ICT

› Energy drives most environmental impacts

› Climate Change can be readily estimated from electricity mixes (preferable marginal)

› Carbon taxes closely linked with electricity generation technologies

• Disadvantages› Just a metric and no actual impacts assessed

› Manufacturing and EoLT impacts are less driven by electricity production than other unit processes

The role of LCA in ICT Sector footprint estimations

• Raw Material Aquisition

• Production

• Transport

• Scrap generation

• Recycling

Challenges related to estimating Sector footprints

• Lack of standardization� The Scope of ICT Sector footprint studies have not been clearly

ICT Sector footprint estimations range from satisfyingly transparent

(understandable which inputs give a certain output) to black box (not fully

clear how the estimation was done)

� The Scope of ICT Sector footprint studies have not been clearly defined.

• Lack of LCA studies of high quality� For some important ICT Equipment LCA results are lacking

� Simplified approaches are likely enough for Sector footprint...but not preferable long-term.

Devices: Best Low Growth Scenario 2012-2017

• Installed base › All kinds of devices remains stable

• Overall year-on-year improvement› use stage energy efficiency of 5% for › use stage energy efficiency of 5% for

most device categories

› From 2008 on 5% annual improvement in manufacturing electricity per unit

Device electricity in TWhrs in 2012-2017 for Best Low Growth Scenario

Devices: (Worst) High Growth Scenario 2012-2017

• TV sets growth › CAGR 5% to 2.6 billion installed

• Desktop PCs and monitors› growth of 2% per year, (0.64 and 0.67 billion installed)

• Installed base of laptops› growth rate CAGR 14% to around 1.58 billion› growth rate CAGR 14% to around 1.58 billion

• Installed bases of smartphones and tablets› grow 15% and 25% per year respectively

• Annual efficiency improvements

› for use electricity vary from 1% to 5% depending on the

particular device category.

› From 2008 on 5% annual improvement in manufacturing electricity per unit

Device electricity in TWhrs in 2012-2017 for High (Worst) Growth Scenario

Networks: Best Low Growth Scenario 2012-2017 – Use stage 90%

• Data traffic › LTE CAGR 2012-2017 109%, Non-LTE 51%

› LTE grows from 14% in 2012 to 45% in 2017 of Wireless Mobile Data Traffic

› Core 26% CAGR of EB

• Energy efficiency› LTE 0.5 TWhrs/EB and Non-LTE (0.5/1.46=) 0.34 TWhrs/EB.

�”Core” Network 7.5% growth


�“Wireless access” network › LTE 0.5 TWhrs/EB and Non-LTE (0.5/1.46=) 0.34 TWhrs/EB.

› ”Core” Network 0.135 TWhrs/EB

• Wireless LTE and non-LTE efficiency

› 5% annual TWh/EB improvement

› Core IP traffic: 15% year-on-year improvement in TWhrs/EB


grows to contribute 7.5% of total

Network electricity consumption

in 2017

Networks: Electricity in TWhrs in 2012-2017 for Best Low Growth Scenario

Networks: (Worst) High Growth Scenario 2012-2017 – Use stage 80%

• Data traffic › LTE CAGR 2012-2017 109%, Non-LTE 51%

› LTE grows from 14% in 2012 to 45% in 2017 of Wireless Mobile Data Traffic

› Core 26% CAGR of EB

• Energy efficiency› LTE 1.37 TWhrs/EB and Non-LTE (1.37/1.46=) 0.94 TWhrs/EB.

�”Core” Network 20.4% growth


�“Wireless access” network › LTE 1.37 TWhrs/EB and Non-LTE (1.37/1.46=) 0.94 TWhrs/EB.

› ”Core” Network 0.142 TWhrs/EB

• Wireless LTE and non-LTE efficiency

› 5% annual TWh/EB improvement

› Core IP traffic: 5% year-on-year improvement in TWhrs/EB


grows to contribute 11.4% of

total Network electricity

consumption in 2017

Networks: Electricity in TWhrs in 2012-2017 for Worst High Growth Scenario

Data Centers: Electricity in TWhrs in 2012-2017 for Best Low Growth Scenario

Data Centers: Electricity in TWhrs in 2012-2017 for Worst High Growth Scenario

Results: Change for Best Case Scenario

Devices,

47%

Networks,

20%

Data

Centers,

15%

LCA, 18%Devices

Networks

Data Centers

LCA

Devices,

33%

Networks,

28%

Data

Centers,

20%

LCA, 19%Devices

Networks

Data Centers

LCA

• 2012� 2017

• In 2012 direct consumption by devices is justless than half of the total contribution

� The trend is that especially Networks Use and also Data

Center Use are growing and Device Use is shrinking.

Results: Change for Worst Case Scenario

Devices,

47%

Networks,

20%

Data

Centers,

15%

LCA, 18%Devices

Networks

Data Centers

LCA

Devices,

32%

Networks,

29%

Data

Centers,

21%

LCA, 18% Devices

Networks

Data

Centers

• 2012 � 2017

We can make a number of observations on this projected 2017 data:

• direct consumption by devices is less than 1/3 of electricity; compare

with 1/2 in 2012.

• data centers + networks combined now represent 1/2 of electricity

usage

• LCA remains approximately at the same level of contribution

Data Centers• Data Center Use.

› Scope: data processing, storage and HVAC infrastructures

› Network infrastructure within and between data centers is part of

“Core” Network but was cut-off (Lambert p. 6(12)Sect.3.1)

› Started from Koomey’s 2010 baseline, extrapolated to 2012

› Then Use the fixed rates (for electricity usage increase) determined

from the previous “core” network data to model data center electricity

growth rates: Low growth 7.5%, Expected growth 14%, High growth growth rates: Low growth 7.5%, Expected growth 14%, High growth

20%

• Data Center upstream› Estimated from ”share of Use stage” as there were no reliable market

statistics for any shipped Data Center Equipment

Data Centers: Electricity in TWhrs in 2012-2017 for Expected Growth Scenario

Results TWhrs: Comparision to SMARTer2020 in 2012

•SMARTer2020

does not show

manufacturing

electricity details,

but just 550

1504

704

18121776

726

2950

863

1520

1000

1500

2000

2500

3000

3500

2012 SMARTER2020

2012 Andrae&Corcoran BASELINE

2012 Mills, MAX

2012 Mills, MIN

•PCs: SMARTer2020 has assumed larger installed base and use the same use stage consumption for laptops and desktops

• Smartphones: SMARTER2020 added “ordinary” mobile phones to smartphones&tablets

•Peripherals: Present study include TVs,STB,GC,A/V Reciever,DVD whereas SMARTER2020 include Monitor,

Printer, STB, and Home router .

but just

CO2e/device/year

550

49 12

337 258343448

0

500

Results TWhrs: Comparision to SMARTer2020 in 2017(2020)

2000

2500

3000

3500

2189

2526.6

3332.7

2017 SMARTER2020

0

500

1000

1500

PCs Smartphones Tablets Peripherals Networks Data Centers TOTALS

612

90 102

343

562480

353

62 37

662

811.7

600.9

269 48 37

585

600

446

1985

414

72 99

840

1115.6

792.1

2017 SMARTER2020

2017 Andrae&Corcoran EXP

2017 Andrae&Corcoran BEST

2017 Andrae&Corcoran WORST

estimation of ict sector footprintsestimation of ict sector footprints anders s.g. andrae , huawei...

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