Fraunhofer USA Center for Sustainable Energy Systems 5 Channel Center Street, Boston, MA 02210 

# Fraunhofer USA Center for Sustainable Energy Systems



# ENERGY CONSUMPTION O F CONSUMER ELECTRONI CS
IN U.S

. HOMES IN 2013

FINAL REPORT TO THE CONSUMER ELECTRONICS ASSOCIATION (CE A ® )

June 2014

by Bryan Urban

, Victoria Shmakova, Brian Lim, and Kurt Roth

PI
Dr

. Kurt Roth, Building Energy Efficiency Group Leader kroth@fraunhofer.org 617 575

- 7256Fraunhofer USA Center for Sustainable Energy Systems 

### 2



# Disclaimer

This report was commissioned by the Consumer Electronics Association on terms specifically limiting

F raunhofer USA’s liability

. Our conclusions are the results of the exercise of our best professional judgment, based in part upon materials and information provided to us by the Consumer Electronics
Association and others

. Use of this report by any third pa rty for whatever purposes should not, and does not, absolve such third party from using due diligence in verifying the report’s contents.

Any use which a third party makes of this document, or any reliance on it, or decisions to be made based on it, are th e responsibility of such third party

. Fraunhofer USA accepts no duty of care or liability of any kind whatsoever to any such third party, and no responsibility for damages, if any, suffered by any third party as a result of decisions made, or not made, or actions taken, or not taken, based on this document.

This report may be reproduced only in its entirety, and may be distributed to third parties only with the prior written consent of the Consumer Electronics Association

.Fraunhofer USA Center for Sustainable Energy Systems 

### 3



# Table of C ontents
List of Figures

................................ ................................ ................................ ................................ ................................ ........... 5 List of Tables

................................ ................................ ................................ ................................ ................................ ............ 7 List of Acronyms and Abbreviations

................................ ................................ ................................ ................................ ......... 9 Acknowledgements

................................ ................................ ................................ ................................ ................................ 10 Executive Summary

................................ ................................ ................................ ................................ ................................ 11 1 Introduction

................................ ................................ ................................ ................................ ............................... 14
1.1 Approach

................................ ................................ ................................ ................................ ................................ ............ 14 1.2 Report Organization

................................ ................................ ................................ ................................ ........................... 14 2 Energy Consumption Calculation Methodology

................................ ................................ ................................ .......... 15 2.1 Residential Installed Base

................................ ................................ ................................ ................................ ................... 15 2.2 Power Draw by Mode

................................ ................................ ................................ ................................ ........................ 15 2.3 A nnual Usage by Mode

................................ ................................ ................................ ................................ ...................... 16 3 Energy Consumption of Consumer Electronics in U.S. Homes

................................ ................................ ..................... 17 3.1 Summary

................................ ................................ ................................ ................................ ................................ ............ 17 3.2 Devices Selected for Further Analysis

................................ ................................ ................................ ................................ 19 3.3 Computer Speakers

................................ ................................ ................................ ................................ ............................ 20 3.3.1 Current Energy Consum ption

................................ ................................ ................................ ................................ ...... 20 3.3.2 Comparison with Prior Energy Consumption Estimates

................................ ................................ .............................. 23 3.3.3 References

................................ ................................ ................................ ................................ ................................ ... 23 3.4 Desktop Computers

................................ ................................ ................................ ................................ ............................ 24 3.4.1 Current Energy Consumption

................................ ................................ ................................ ................................ ...... 24 3.4.2 Comparison with Prior Energy Consumption Estimates

................................ ................................ .............................. 31 3.4.3 References

................................ ................................ ................................ ................................ ................................ ... 32 3.5 Portable Computers

................................ ................................ ................................ ................................ ........................... 34 3.5.1 Cu rrent Energy Consumption

................................ ................................ ................................ ................................ ...... 34 3.5.2 Comparison with Prior Energy Consumption Estimates

................................ ................................ .............................. 42 3.5.3 References

................................ ................................ ................................ ................................ ................................ ... 43 3.6 Home Audio: Shelf/Compact Audio and Speaker Docks

................................ ................................ ................................ .... 45 3.6.1 Current Energy Consumption

................................ ................................ ................................ ................................ ...... 45 3.6.2 Comparison with Prior Energy Consumption Estimates

................................ ................................ .............................. 49 3.6.3 References

................................ ................................ ................................ ................................ ................................ ... 50 3.7 Monitors

................................ ................................ ................................ ................................ ................................ ............. 51 3.7.1 Current Energy Consumption

................................ ................................ ................................ ................................ ...... 51 3.7.2 Comparison with Prior Energy Consumption Estimates

................................ ................................ .............................. 56 3 .7.3 References

................................ ................................ ................................ ................................ ................................ ... 57 3.8 Network Equipment

................................ ................................ ................................ ................................ ........................... 58 3.8.1 Current Energy Consumption

................................ ................................ ................................ ................................ ...... 58 3.8.2 Comparison with Prior Energy Consumption Estimates

................................ ................................ .............................. 62 3.8.3 References

................................ ................................ ................................ ................................ ................................ ... 63 3.9 Smart Phones

................................ ................................ ................................ ................................ ................................ ..... 65 3.9.1 Current Energy Consumption

................................ ................................ ................................ ................................ ...... 65 3.9.2 Comparison with Prior Energy Consumption Estimates

................................ ................................ .............................. 68 3.9.3 References

................................ ................................ ................................ ................................ ................................ ... 68 3.10 Tablet Computers

................................ ................................ ................................ ................................ ............................... 70 3.10.1 Current Energy Consumption

................................ ................................ ................................ ................................ ...... 70 3.10.2 Comparison with Prior Energy Consumption Estimates

................................ ................................ .............................. 74 3.10.3 References

................................ ................................ ................................ ................................ ................................ ... 74 3.11 Set

- top Boxes

................................ ................................ ................................ ................................ ................................ ..... 7 6 3.11.1 Current Energy Consumption

................................ ................................ ................................ ................................ ...... 76 3.11.2 Comparison with Prior Energy Consumption Estimates

................................ ................................ .............................. 84 3.11.3 References

................................ ................................ ................................ ................................ ................................ ... 86 3.12 Televisions

................................ ................................ ................................ ................................ ................................ .......... 88 3.12.1 Current Energy Consumption

................................ ................................ ................................ ................................ ...... 88 3.12.2 Comparison with Prior Energy Consumption Estimates

................................ ................................ .............................. 95 3.12.3 References

................................ ................................ ................................ ................................ ................................ ... 96 3.13 Video Game Systems

................................ ................................ ................................ ................................ .......................... 98 3.13.1 Current Energy Consumption

................................ ................................ ................................ ................................ ...... 98Fraunhofer USA Center for Sustainable Energy Systems 

### 4

3.13.2 Comparison with Prior Energy Consumption Estimates

................................ ................................ ............................ 103 3.13.3 References

................................ ................................ ................................ ................................ ................................ . 105 3.14 Other Devices

................................ ................................ ................................ ................................ ................................ ... 106 3.14.1 References

................................ ................................ ................................ ................................ ................................ . 112
4 Conclusions

................................ ................................ ................................ ................................ .............................. 115
4.1 Key Trends

................................ ................................ ................................ ................................ ................................ ........ 118 4.1.1 Televisions

................................ ................................ ................................ ................................ ................................ . 118 4.1.2 Computers

................................ ................................ ................................ ................................ ................................ . 119 4.2 References

................................ ................................ ................................ ................................ ................................ ....... 120 Appendix A

– CE Usage Surveys

................................ ................................ ................................ ................................ ............ 121 A.1 Personal Computers (Desktops and Portables)

................................ ................................ ................................ ...................... 121 A.2 Home Audio

................................ ................................ ................................ ................................ ................................ ............ 123 A.3 Mob ile Devices (Smartphones and Tablets)

................................ ................................ ................................ ........................... 125 A.4 Televisions

................................ ................................ ................................ ................................ ................................ .............. 126 A.5 Video Game Consoles

................................ ................................ ................................ ................................ ............................. 131 Appendix B

– Energy and Usage Models

................................ ................................ ................................ ............................... 135 B.1 Energy Models

— Personal Computers (Desktops and Portables)

................................ ................................ ......................... 135 B.1.1 Plugged

- In Install Base

................................ ................................ ................................ ................................ ............... 135 B.1.2 Operational Modes

................................ ................................ ................................ ................................ .................... 136 B.1.2.1 Operational Modes for External Power Supplies of Portable PCs

................................ ................................ .............. 136 B.1.3 Usage Modeling

................................ ................................ ................................ ................................ ......................... 137 B.1.3.1 Day Periods

................................ ................................ ................................ ................................ ................................ 137 B.1.3.1.1 Sample Energy Consumption across Daytime Periods

................................ ................................ ............................... 138 B.1.3.2 Daytime Periods

................................ ................................ ................................ ................................ ......................... 139 B.1.3.3 Usage Session

................................ ................................ ................................ ................................ ............................ 139 B.1.3.4 Post

- Session

................................ ................................ ................................ ................................ ............................... 140 B.1.3.4.1 Manual Power Management Routines

................................ ................................ ................................ ...................... 140 B.1.3.4.2 Automate d Power Management Settings Modes

................................ ................................ ................................ ...... 141 B.1.3.4.3 Usage Time by Operational Mode in Post

- Session

................................ ................................ ................................ .... 141 B.1.3.5 Non

- Session

................................ ................................ ................................ ................................ ............................... 141 B.1.3.6 Total Usage by Operational Mode in Daytime Period

................................ ................................ ............................... 142 B.1.4 Pre

- Evening Period

................................ ................................ ................................ ................................ .................... 142 B.1.5 Evening Period

................................ ................................ ................................ ................................ ........................... 142 B.1.6 Night Period

................................ ................................ ................................ ................................ ............................... 142
B.1.7 Whole Day

................................ ................................ ................................ ................................ ................................ . 143 B.1.7.1 Desktop PC

................................ ................................ ................................ ................................ ................................ . 143 B.1.7.2 Portable PCs

................................ ................................ ................................ ................................ ............................... 143 B.1.8 References

................................ ................................ ................................ ................................ ................................ . 144 B.2 Energy Usage Models

— Mobile Devices (Tablets and Smartphones)

................................ ................................ ............. 145 B.2.1 Plugged

- In Install Base

................................ ................................ ................................ ................................ ............... 145 B.2.2 Energy Consumption

................................ ................................ ................................ ................................ .................. 145 B.2.2.1 Charging

................................ ................................ ................................ ................................ ................................ ..... 146 B.2.2.2 Usage

................................ ................................ ................................ ................................ ................................ ......... 147 B.2. 2.3 Idle

................................ ................................ ................................ ................................ ................................ ............. 147 B.2.2.4 Unplugged

................................ ................................ ................................ ................................ ................................ .. 147 B.2.2.5 Representative Weights for Mobile Device and Charger Models

................................ ................................ .............. 148 B.2.2.6 Whole Day Energy Consumption

................................ ................................ ................................ ............................... 151 B.2.3 References

................................ ................................ ................................ ................................ ................................ . 151 B.3 Video Game Consoles

................................ ................................ ................................ ................................ ............................. 154 B.3.1 Installed Base

................................ ................................ ................................ ................................ ............................. 154 B.3.2 Usage of video game consoles including 8 th generation models

................................ ................................ ............... 154 B.3.3 Power Draw

................................ ................................ ................................ ................................ ............................... 155 B.3.4 Usage estimates

– Video Game Consoles

................................ ................................ ................................ .................. 156 B.3.4.1 Calculations of Time Spe nt in Operational Modes

................................ ................................ ................................ ..... 156 B.3.5 References

................................ ................................ ................................ ................................ ................................ . 157 B.4 Home Audio

................................ ................................ ................................ ................................ ................................ ..... 158
B.4.1 Speaker Docks

................................ ................................ ................................ ................................ ............................ 158 B.4.2 Shelf Stereo Systems

................................ ................................ ................................ ................................ .................. 158Fraunhofer USA Center for Sustainable Energy Systems 

### 5



# List of Figures

Figure ES

- 1: Residential CE ann ual electricity consumption by category.

................................ ................................ ...................... 12 Figure ES

- 2: Residential CE annual electricity consumption by device.

................................ ................................ .......................... 12 Figure ES

- 3: Annual unit electricity consumption for categories evaluated in detail.

................................ ................................ .... 13 Figure 2

- 1: UEC and AEC calculation methodology (ADL 2002).

................................ ................................ ................................ ..... 15 Figure 3

- 1 : UEC, installed base, and AEC of CE categories evaluated in detail.

................................ ................................ ............. 18 Figure 3

- 2: Distribution of computer speaker systems per desktop and portable computer.

................................ ........................ 20 Figure 3

- 3: Unit Energy Consumption by mode and Annual Energy Consumption by computer speaker system type.

................ 22 Figure 3

- 4: Distribution of hou seholds with numbers of desktop PCs plugged in during the past month (Nov 2013).

.................. 25 Figure 3

- 5: Representative power draw by mode of tower and AIO desktop PCs.

................................ ................................ ......... 27 Figure 3

- 6: Average per session usage duration and number of sessions “yesterday” for primary and secondary desktop PCs.

.. 28 Figure 3

- 7: Total usage duration “ye sterday” for primary and secondary desktop PCs.

................................ ................................ 28 Figure 3

- 8: Likelihood of users manually setting desktop PCs into various modes for the daytime or night.

................................ 29 Figure 3

- 9: Percentage of desktop PCs with different automatic PM modes enabled.

................................ ................................ .. 29 Figure 3

- 10: Average time spent in various operational modes in one day and in one year for desktop PCs. Weighted average across primary and secondary tower and AIO desktop PCs.

................................ ................................ ................................ ........... 30 Figure 3

- 11: Total energy consumed in various operational modes in one day and in one year for desktop PCs. Weighted average across primary and secondary tower and AIO desktop PCs.

................................ ................................ ............................. 31 Figure 3

- 12: Distribution of households by number of portable PCs owned or plugged

- in during the pas t month (Nov. 2013).

.. 34 Figure 3

- 13: Representative power draw by mode of notebook and netbook portable PCs.

................................ ........................ 37 Figure 3

- 14: Avera ge per session usage and number of sessions “yesterday” for primary and secondary portable PCs.

.............. 38 Figure 3

- 15: Average total usage “yesterday” for primary and secondary portable PCs.

................................ ............................... 38 Figure 3

- 16: Portion of users manually setting portable PCs into various power modes for the daytime or nighttime.

............... 39 Figure 3

- 17: Perce ntage of portable PCs with various automatic PM modes enabled.

................................ ................................ .. 39 Figure 3

- 18: Average time spent in various operational modes in one day (left) and in one year (right) for portable PCs.

........... 41 Figure 3

- 19: Total energy consumed in various operational modes in one day and in one year for portable PCs. Weighted average across primary and secondary notebook and netbook portable PCs.

................................ ................................ ............... 42 Figure 3

- 20: Example of a speaker dock (left), and shelf stereo system (right), source: iHome, Sony.

................................ .......... 45 Figure 3

- 21: Active power dra ws of different mini

- shelf stereo systems (Fraunhofer measurements).

................................ ........ 47 Figure 3

- 22: Frequencies of responses regarding the active daily usage of speaker systems.

................................ ....................... 48 Figure 3

- 23: Speaker dock UEC distribution among different modes

................................ ................................ ............................. 49 Figure 3

- 24: Installed base of monitors and computers.

................................ ................................ ................................ ................ 51 Figure 3

- 25: Distribution of monitors per desktop and portable computer.

................................ ................................ .................. 52 Figure 3

- 26: Distribution of LCD monitors installed base in 2013 by diagonal screen s ize (FhCSE 2011, DisplaySearch 2014).

..... 52 Figure 3

- 27: Portion of monitor sales by backlight technology (DisplaySearch 2014).

................................ ................................ ... 53
Fi gure 3

- 28: Active

- mode power draw measurements for ENERGY STAR LCD monitors by backlight technology (EPA 2013).

..... 5 4 Figure 3

- 29: Decision diagram for determining monitor operational mode.

................................ ................................ .................. 55 Figure 3

- 30: Portion of households with broadband Internet subscriptions and home networks (CEA 2013b).

........................... 58 Figure 3

- 31: Type of Inter net service at home (CEA 2013a).

................................ ................................ ................................ .......... 60 Figure 3

- 32: AEC for small network equipment.

................................ ................................ ................................ ............................. 62 Figure 3

- 33: U.S. broadband household subscri bers by technology type (LBNL 2010, TIA 2013, CEA 2013a).

............................... 63 Figure 3

- 34: Distribution of households with smartphones used during the past month (Nov. 2013) vs. Ownership (Feb. 2013, CEA 2013).

................................ ................................ ................................ ................................ ................................ ....................... 65 Figure 3

- 35: Energy consumption of smartphones in different operational modes.

................................ ................................ ...... 68 Figure 3

- 36: Percentage of households with t ablets used during the past month (Nov. 2013) vs. Ownership (Feb. 2013) (CEA 2013).

................................ ................................ ................................ ................................ ................................ .............................. 70 Figure 3

- 37: Energy consumption of tablets in different operational modes.

................................ ................................ ................ 74 Figure 3

- 38: Power draw of subscription set

- top boxes by provider type and selected features, n=84 (EPA 2012).

..................... 81 Figure 3

- 39: Summary of installed base, UEC and AEC for STBs.

................................ ................................ ................................ .... 83 Figure 3

- 40: Annual STB sales to dealers by display technology.

................................ ................................ ................................ .... 86Fraunhofer USA Center for Sustainable Energy Systems 

### 6

Figure 3

- 41: Cumulative STB sales to deale rs by display technology since 2005.

................................ ................................ ........... 86 Figure 3

- 42: TV ownership distribution (CE Usage Survey).

................................ ................................ ................................ ............ 88 Figure 3

- 43: Screen size for LCD and Plasma TVs from 2010 to 2012. Reclassifying survey responses for Plasma TVs of 37 in. or lower as LCD TVs improves surveyagreement with sales data.

................................ ................................ ................................ ...... 89
Table 3

- 69: Distribution of TVs by display type. Figure 3

- 44: TVs by display type.

................................ ................................ .... 90 Figure 3

- 45: TVs by screen size and age (Nov. 2013 survey). Bin ranges not of equal size.

................................ ............................ 90 Figure 3

- 46: Distribution of TVs by display technology and usage priority.

................................ ................................ .................... 91 Figure 3

- 47: Power regressions for LCD and Plasma TVs (CEC 2013).

................................ ................................ ............................. 92 Figure 3

- 48: Impact of TV brightness on power draw (EPA 2013).

................................ ................................ ................................ . 93 Figure 3

- 49: TV unit energy consumption by usage priority and display type.

................................ ................................ ............... 94 Figure 3

- 50: Active and off mode AEC by TV priority and display type.

................................ ................................ .......................... 95 Figure 3

- 51: Annual TV sales to dealers by display technology (CEA 2013, 2010).

................................ ................................ ......... 96 Figure 3

- 52: Cumulative TV sales to dealers by display technology since 1999 (CEA 2013, 2010).

................................ ................ 96 Figure 3

- 53: Fraction of video game systems installed in U.S. homes by platform.

................................ ................................ ....... 99 Figure 3

- 54: Turned ON and actively used hours/day for different video game console platforms.

................................ ............ 101 Figure 3

- 55: Distribution of active usage among gaming and video (streaming and playback) by platform.

............................... 102 Figure 3

- 56: Video game console UEC and usage by mode.

................................ ................................ ................................ ......... 102 Figure 3

- 57: Annual Energy Consumption by different video game consoles

................................ ................................ .............. 103 Figure 3

- 58: Historical active

- gaming mode power draw values for video game systems (Calland 2014, Jessop 2014, Boxleitner 2014, NRDC 2010)

................................ ................................ ................................ ................................ ................................ ......... 104 Figure 3

- 59: UEC, installed base, and AEC of other CE devices evaluated in less detail.

................................ .............................. 107 Figure 4

- 1: Residential electricity consumption in 2013 by major end uses (DOE 2012, Current Study).

................................ .... 115 Figure 4

- 2: Residential primary energy consumption in 2013 by major end uses (DOE 2012, Current Study).

............................ 116 Figure 4

- 3: Residential CE electricity consumption by category.

................................ ................................ ................................ .. 116 Figure 4

- 4: Unit electricity consumption for the CE categories evaluated in detail.

................................ ................................ ..... 117 Figure 4

- 5: AEC by operational mode for the categories evaluated in detail.

................................ ................................ .............. 117 Figure 4

- 6: Breakdown of UEC by operational modes for the categories evaluated in detail.

................................ ..................... 118Fraunhofer USA Center for Sustainable Energy Systems 

### 7



# List of Tables

Table ES

- 1: Consumer electronics analyzed in further detail.

................................ ................................ ................................ ........ 11
Table 3

- 1: Residential CE energy consumption summary.

................................ ................................ ................................ .............. 17
Table 3

- 2: CE analyzed in the current study.

................................ ................................ ................................ ................................ .. 19
Table 3

- 3: Installed base of computer speaker systems (CE Usage Survey).

................................ ................................ .................. 21
Table 3

- 4: Power dra w by mode for computer speaker systems.

................................ ................................ ................................ .. 22
Table 3

- 5: Annual usage by mode of computer speaker systems (hours/year).

................................ ................................ ............. 22
Table 3

- 6: UEC and AEC calculation for computer speaker systems.

................................ ................................ .............................. 23
Table 3

- 7: Prior energy consumption estimates for computer speaker systems.

................................ ................................ ........... 23
Table 3

- 8 : Installed base estimates for desktop PCs from different data sources.

................................ ................................ ........ 24
Table 3

- 9: Plugged

- In installed base estimates for Tower and All

- in

- One (AIO) Desktop Computers from CE Usage Survey.

....... 24
Table 3

- 10: Plugged

- In installed base estimate for All

- in

- One Desktop Computers based on sales via consumer channels (DisplaySearch 2014).

................................ ................................ ................................ ................................ ................................ ..... 25
Table 3

- 11: Power draw estimates for desktop computers from different data sources.

................................ .............................. 26
Table 3

- 12: Estimated desktop PC installed base by computer vintage to eva luate relative power draw characteristics derived from Figure 3 of (CEA 2014). Average age: 3.2 years.

................................ ................................ ................................ ..................... 26
Table 3

- 13: Comparison of percentage of time desktop PCs spent in various operational m odes with other data sources.

........ 30
Table 3

- 14: UEC and AEC values for desktop PCs.

................................ ................................ ................................ .......................... 31
Table 3

- 15: Current and prior energy consumpti on estimates for desktop PCs.

................................ ................................ ............ 32
Table 3

- 16: Installed base estimates for portable PCs from different data sources.

................................ ................................ ...... 34
Table 3

- 17: Plugged

- In installed base estimates for notebook and netbook portable PCs from the CE Usage Survey.

................. 35
Table 3

- 18: Power draw estimates for portable PCs from different data sources.

................................ ................................ ......... 35
Table 3

- 19: Determining relative power draw characteristics from age of portable PCs owned in Dec. 2013 derived from Figure 3 of (CEA 2014). Average age: 2.4 years.

................................ ................................ ................................ ................................ ........... 36
Table 3

- 20: Power draw estimates of the external power supply for portable PCs (DOE 2012), weighted by shipment distribution. This excludes the power draw due to the portable PC.

................................ ................................ ............................. 36
Table 3

- 21: Time usage estimates of portable PC EPSs from DOE (2012). Weighted average by shipment distribution of the
reference case.

................................ ................................ ................................ ................................ ................................ ............... 40
Table 3

- 22: Comparison of percentag e of time notebook PCs spent in various operational modes with other data sources.

...... 41
Table 3

- 23: Unit energy consumption (UEC), installed base, and annual energy consumption (AEC) of portable PCs.

................. 42
Table 3

- 24: Current and prior energy consumption estimates for portable PCs.

................................ ................................ ........... 43
Table 3

- 25: Installed base of speaker dock s and shelf stereo systems (CE Usage Survey).

................................ ............................ 45
Table 3

- 26: Power draw by mode for audio systems

................................ ................................ ................................ ...................... 47
Table 3

- 27: Annual usage by m ode of speaker dock and shelf stereo systems

................................ ................................ .............. 48
Table 3

- 28: UEC calculation for speaker systems.

................................ ................................ ................................ .......................... 49
Table 3

- 29: AEC summary for sp eaker systems.

................................ ................................ ................................ ............................. 49
Table 3

- 30: Prior energy consumption estimates for speaker docks.

................................ ................................ ............................. 50
Table 3

- 31: Prior energy consumption estima tes for mini

- shelf stereo system.

................................ ................................ ............ 50
Table 3

- 32: Installed base of monitors.

................................ ................................ ................................ ................................ ........... 51
Table 3

- 33: Average power draw estimates for monit ors.

................................ ................................ ................................ ............. 54
Table 3

- 34: Daily usage of monitors by mode.

................................ ................................ ................................ ............................... 55
Table 3

- 35: UEC and AEC estimates for monitors.

................................ ................................ ................................ .......................... 56
Table 3

- 36: Prior energy consumption estimates for monitors.

................................ ................................ ................................ ..... 56
Table 3

- 37: Installed base of network devices (LBNL 2010, CEA 2013a, NRDC 2013).

................................ ................................ .... 59
Table 3

- 38: Power draws for network equipment (NRDC 2013, EPA 2013b)

................................ ................................ ................. 61
Table 3

- 39: UEC and AEC calculations for network equipment.

................................ ................................ ................................ ..... 62
Table 3

- 40: Prior energy consumption estimates for broadband access devices (modems and IADs)

................................ ........... 63
Table 3

- 41: Prior energy consumpt ion estimates for routers and other devices (non

- modem)

................................ .................... 63
Table 3

- 42: Installed base estimates for smartphones from different data sources.

................................ ................................ ..... 65
Table 3

- 43: Plugged

- In installed base estimates for smartphones from the CE Usage Survey.

................................ ...................... 66Fraunhofer USA Center for Sustainable Energy Systems 

### 8

Table 3

- 44: Representative battery capacity for smartphones, and power draw estimates for original and other chargers.

....... 66
Table 3

- 45: Energy consumption estimates due to charging smartphones.

................................ ................................ ................... 66
Table 3

- 46: Energy co nsumption estimates due to smartphones being plugged into chargers after being fully charged (idle).

... 67
Table 3

- 47: Energy consumption estimate for smartphones in unplugged mode.

................................ ................................ ......... 67
Table 3

- 48: UEC and AEC values for smartphones.

................................ ................................ ................................ ......................... 68
Table 3

- 49: Current and prior energy consumption estimates for smartphones.

................................ ................................ .......... 68
Table 3

- 50: Recent installed base estimates for tablets.

................................ ................................ ................................ ................ 70
Table 3

- 51: Plugged

- In installed base estimates for tablets from the CE Usage Sur vey.

................................ ................................ 71
Table 3

- 52: Representative capacity and efficiency of original and aftermarket batteries and chargers for tablets.

.................... 72
Tabl e 3

- 53: Energy consumption estimates due to charging tablets.

................................ ................................ ............................. 72
Table 3

- 54: Energy consumption estimates of tablets in idle mode.

................................ ................................ .............................. 73
Table 3

- 55: Energy consumption estimate for tablets in unplugged mode.

................................ ................................ ................... 73
Table 3

- 56: UEC and AEC values for tablets.

................................ ................................ ................................ ................................ ... 74
Table 3

- 57: Current and prior energy consumption estimates for tablets.

................................ ................................ .................... 74
Table 3

- 58: Pay TV customers by service, millions.

................................ ................................ ................................ ......................... 77
Table 3

- 59: Installed base of pay TV STBs by service (Nov. 2013 survey).

................................ ................................ ...................... 77
Table 3

- 60: Installed base of pay TV STBs, millions.

................................ ................................ ................................ ........................ 78
Tabl e 3

- 61: Subscribers with multi

- room STBs, millions (Nov. 2013 survey).

................................ ................................ ................. 79
Table 3

- 62: Cumulative STB shipment projections from Q2

- 2010 to Q4

- 2013 (DOE 2013a).

................................ ......................... 79
Table 3

- 63: Installed base of standalone STBs, millions.

................................ ................................ ................................ ................. 80
Table 3

- 64: Power draw and installed base by device.

................................ ................................ ................................ ................... 82
Table 3

- 65: UEC and AEC summary for STBs.

................................ ................................ ................................ ................................ .. 84
Table 3

- 66: Prior energy consumption estimates for subscription STBs.

................................ ................................ ........................ 85
Table 3

- 67: Prior energy consumption estimates for standalone STBs.

................................ ................................ ......................... 85
Table 3

- 68: Installed base estimates for TVs in 2013.

................................ ................................ ................................ ..................... 88
Table 3

- 69: Distribution of TVs by display type. Figure 3

- 44: TVs by display type.

................................ ................................ .... 90
Table 3

- 70: ENERGY STAR power draw requirements for TVs.

................................ ................................ ................................ ....... 91
Table 3

- 71: Active mode power regressions by TV screen area, display, and production year.

................................ ..................... 92
Table 3

- 72: UEC and AEC calculations for TVs for 2013.

................................ ................................ ................................ ................. 94
Table 3

- 73: Prior energy consumption estimates for TVs.

................................ ................................ ................................ .............. 95
Table 3

- 74: Installed base of video game consoles.

................................ ................................ ................................ ........................ 98
Table 3

- 75: Installed base and power draw by mode of video game systems.

................................ ................................ ............. 100
Table 3

- 76: Usage by different video game consoles (CE Usage Survey).

................................ ................................ ..................... 101
Table 3

- 77: Annual hours by mode for video game consoles for LBNL 2013, FhCSE 2011 and current study.

............................. 101
Table 3

- 78: Comparison of different esti mates for the portion of active time in gaming and other modes.

............................... 101
Table 3

- 79: UEC calculation for video game systems.

................................ ................................ ................................ ................... 102
Table 3

- 80: AEC summary for video game systems

................................ ................................ ................................ ...................... 103
Table 3

- 81: Prior energy consumption estimates for video game systems.

................................ ................................ ................. 1 03
Table 3

- 82 : UEC and installed base estimates for other products.

................................ ................................ ............................... 106
Table 3

- 83: Average power draw by mode estimates for other products.

................................ ................................ ................... 108
Table 3

- 84: References for power draw by mode estimates for other products

................................ ................................ .......... 109
Table 3

- 85: Annual usage by mode estimates for other products.

................................ ................................ ............................... 110
Table 3

- 86: References for annual usage by mode estimates for other products.

................................ ................................ ....... 111
Table 3

- 87: References for installed base estimates for other products.

................................ ................................ ..................... 112
Table 4

- 1: Consumer electronics analyzed in further detail.

................................ ................................ ................................ ........ 115Fraunhofer USA Center for Sustainable Energy Systems 

### 9



# List of Acronyms and Abbreviations

AEC Annual electricity c onsumption
AVR Audio

- v ideo r eceivers CE Consume r electronics
CEA Consumer Electronics Association
DOE U.S

. Department of Energy
DTA D igital terminal a dapters 1



### DVD Digital versatile disc
DVR Digital video re corder
EP Electro

- photographic
EPA U.S

. Environmental Protection Agency
HD High definition
IAD Integrated Access Device
LBNL Lawrence Berkeley National Laboratory
MFD Multi

- function device
NA Not a pplicable
NRD Natural Resources Defense Council
PC Personal Computer
STB Set

- top b ox TEC Total energy c onsumption
, Typical energy consumption
TV Tele vision TWh Terawatt

- hour
UEC Unit electricity consumption
USB Universal Serial Bus
VCR Video cassette recorder

1 Also called digital

- to

- analog converter boxes, digital transport adapters, and digital television adapters

.Fraunhofer USA Center for Sustainable Energy Systems 

### 10



# Acknowledgements

The authors would like to express our gratitude to the following people for their support in making this
report possible

.

T hank s to the project sponsors at the Consumer Electronics Association, and especially Doug las Johnson, Vice President, Technology Policy , for advocating for and leading the project at CEA

. In addition, t hanks

to Steve Koenig for providing CE market data an d consultations on our installed base estimates and to
Jessica Boothe and Robin Trembley for their input and collaboration on the CE Usage Survey.

Thanks to our reviewer s for reviewing and providing helpful feedback on the draft final report :

 Warren Boxl eitner, Nintendo

 Sibylle Braungardt, Fraunhofer Institute for Systems and Innovation Research (ISI)

 Tim Calland, Microsoft

 Louis

- Benoit Desroches, LBNL

 Paul Glist, National Cable and Telecommunications Association (NCTA)

 Jerry Jessop, Sony

 Gary Langille , EchoStar

 Lauren Liecau, Unaffiliated

 Adrian Liga, Apple

 David Maciel, Sony

 R.J. Meyers, EPA ENERGY STAR

 James Morgan, Sony

 Bruce Nordman, LBNL

 Scott O’Connell, Dell

 Verena Radulovic, EPA ENERGY STAR

 Vida Rozite, International Energy Agency

 Mark Sharp, P anasonic

 Hans

- Paul Siderius, SenterNovem

 Michael Warnecke, Entertainment Software Association

 Andrew Ware, Logitech

 Liz Westbrook, Trenholm, Natural Resources Canada

 Robert White, Dell

Finally, we would like to thank Paul Semenza with NPD DisplaySearch for providing display data and Ian Olgeirson of SNL Kagan for providing set top box data.Fraunhofer USA Center for Sustainable Energy Systems 

### 11



# Executive Summary The Consumer Electronics Association (CEA ® ) commissioned this study to quantify the electricity consumption of consumer electronics (CE) in U.S

. hou seholds in 2013

. Relative to other energy end uses,
the characteristics of CE typically change very quickly due to short product cycles and lifetimes, evolving usage patterns and dynamics, and rapid technology adoption that can strongly influence device po wer draw by mode

. As a result, the characteristics of the installed base of most CE can change dramatically in a few years

. Such rapid changes in the energy consumption characteristics of CE make it essential to develop up

- to

- date and accurate assessments of CE energy consumption

. If older data are used to analyze potential energy policy decisions, such as voluntary or mandatory regulatory programs, they can lead to less effective policy decisions that may not achieve their end goals

.

We used a bottom

- up a pproach to characterize U.S

. residential consumer electronics (CE) en ergy consumption in 2013

. Our effort focused on 17 priority categories , shown in Table ES

- 1

. We selected these for more refined AEC analysis based on preliminary AEC estimates (higher mor e likely to be selected) and uncertainty in the preliminary AEC estimate (higher more likely to be selected). In addition, we developed preliminary estimates for 29 other CE categories

. For each CE category, we used a range of sources to develop estimates for the installed base and average power draw and annual usage by mode

.

Table ES

- 1 : Consumer electronics analyzed in further detail.



### Audio

- Visual Equipment Computers & Peripherals
Home Audio Speaker Dock Compact Stereo Syst em Televisions Video Game Consoles Set Top Boxes Cable Standalone Satellite Telco Desktop PC

Portable PC Computer S peaker s Computer Monitor Smart Phone Tablet Networking Equipment Integrated Access Device Modem
Router



### Notably, we developed five (5) phone survey s to assess the usage of CE in greater detail, with a particular focus on refining our understanding of audio personal computer , smart phone, tablet, television, and video game console usage by mode

. Subsequently, we used the survey respon ses as inputs into detailed usage

- by

- mode models.

Overall, w e estimate that the 3.8 billion CE in homes consumed 1 6 9 TWh in 2013 , an amount equal to

12 % of residential electricity consumption and 8.4 % of residential primary 2 

### energy consumption

. Figure s
ES

- 1 and ES

- 2 show the breakdown in annual electricity consumption ( AEC ) by category and device

.

2 Residentia l primary energy is the total energy content of the fuel required to meet all end uses. Primary energy includes the fuel cons umed at the home, as with non

- electric space heating applications and appliances (e.g., oil or gas furnaces, gas powered clothes dr yers, etc.), as well as fuel consumed at the power plant to generate electricity and to overcome transmission and distribution losses . For example, when a home

consumes 1 kWh of electricity , the power plant must consume an average of 3 .1 kWh of primary ene rgy ( DOE 2012 )

.Fraunhofer USA Center for Sustainable Energy Systems 

### 12

Figure ES

- 1 : Residential CE annual electricity consumption by category.

Figure ES

- 2 : Residential CE annual electricity consumption by device.



### A limited number of CE categories accounted for the majority of CE electricity consumption

. Notab ly,
televisions accounted for 30 % of residential CE electricity consumption, set

- top boxes 1 8 % , and computers 13%

. The AEC of all the categories analyzed in further detail equals 83 % of the estimated
total residential CE AEC.

The average unit electricity consumption (UEC) of the categories evaluated in detail varies greatly among categories , with more than an order o f magnitude difference between the categ ories with the highest and lowest UEC , shown in Figure ES

- 3

. 28 1.4 2.6 5.6 12 21 6.7 11 31 50

0 10 20 30 40 50 Other CE Devices Mobile Computing Devices Computer Speakers Computer Monitors Network Equipment Personal Computers - All

Home Audio Video Game Consoles Set-top Boxs - All Television Information Technology Home Entertainment

Annual Energy Consumption [TWh]

28 0.6 0.8 1.9 2.5 2.6 2.7 3.4 3.9 4.8 4.9 5.5 5.7 11

11 15 16 50

0 10 20 30 40 50 Other CE Devices

Tablet Smart Phone Speaker Dock STB - Standalone Computer Speaker

Modem STB - Telco Internet Access Device Compact Stereo System

Portable PC Router and other Computer Monitor STB - Satellite Video Game Console STB - Cable Desktop PC Television

Annual Energy Consumption [TWh]Fraunhofer USA Center for Sustainable Energy Systems 

### 13

Figure ES

- 3 : Annual unit electricity consumption for categories evaluated in detail.



### T he active mode accounts for 70 % of th e total AEC of all the categories evaluated in more detail , while the idle, sleep, and off modes account for 12, 11, and 7 percent , respectively

. This masks large differences in the distribution of UEC by mode among different CE categories

. 12 4.5 6.1 19 42

45 53 55 58 59 62 75 88 106 112 128 166 186

0 50 100 150 200 Other CE Devices Smart Phone Tablet Speaker Dock Computer Speaker STB - Standalone Portable PC Modem Computer Monitor Router and other Internet Access Device Compact Stereo System Video Game Console

STB - Telco STB - Satellite STB - Cable Television Desktop PC

Unit Energy Consumption [kWh/year]Fraunhofer USA Center for Sustainable Energy Systems 

### 14



# 1 Introduction

Th e Consumer Electronics Association (CEA) commissioned this study to quantify the electricity consumption of consumer electronics (CE) in U.S

. households in 2013 as a follow

- up to the two prior
studies it commissioned for 2006 (Roth and McKenney 2007) and 2 010 (Urban et al. 2011)

. Relative to other energy end uses, the CE end use characteristics typically change very quickly due to innovation, short product cycles and lifetimes, evolving usage patterns and dynamics , and rapid technology adoption that can str ongly influence device power draw by mode

. As a result, the characteristics of the installed base of most CE have changed dramatically since the first study.

Such rapid changes in the energy consumption characteristics of CE make it essential to develop u p

- to

date and accurate assessments of CE energy consumption

. If older data are used to analyze potential energy policy decisions, such as voluntary or mandatory regulatory programs, they can lead to less
effective policy decisions that may not achieve thei r end goals

. Consequently, CEA commissioned this
follow

- up study to provide high

- quality data to inform public policy decisions affecting CE.



## 1.1 Approach This study used the same approach as the first two CE energy consumption studies :

1. Develop preliminary Ann ual Energy Consumption (AEC) estimates for a long list of CE

2. Select a subset of priority CE for more refined analysis

3. Develop more refined AEC estimates for the priority categorie s
4. Compare current energy consumption characteristics with prior estimates

5. Compose a Final Report to CEA suita ble for widespread distribution



## 1.2 Report Organization The report has the following organization:

Section 2 describes the methodology used to characterize CE energy consumption

.

Section 3 presents an overview of CE energy consumption and the detailed analyses for the priority CE categories

.

Section 4 presents the conclusions of this study.

Appendix A contains the CE Usage Survey

.
Appendix B explains our methodology for estimating computer and monitor usage by mode based on the CE Usage Survey responses

.Fraunhofer USA Center for Sustainable Energy Systems 

### 15



# 2 Energy Consumption Calculation Methodology

We used a bottom

- up approach to evaluate the annual electricity consumption (AEC) of each CE
category shown in Figure 2

- 1

. For each device we developed est imates for the annual average usage in
each power mode (in hours) and multiplied them by the estimated average power draw in that mode (in

watt s) to calculate the unit electricity consumption (UEC) by mode

. The sum of the UEC over all modes equals the tota l device UEC, and the product of the UEC and installed base equals the AEC

. The modes
shown in Figure 2

- 1 are illustrative and were tailored for the analysis of each specific category.

Figure 2

- 1 : UEC and AEC calculation methodology (ADL 2002)

. 

### Prior studies of CE energy consumption describe the methodology in further detail (Kawamoto et al

. 2001, Roth et al

. 2002, Roth et al

. 2006 , etc. )

. A succinct over view of how we typically evaluated each component of the AEC calculation follow s

.



## 2.1 Residential Installed Base The residential installed base equals the total number of devices actively used in homes, excluding
devices that are not used (e.g., those stored, unplugged in basements or closets)

. Most installed base
estimates came from market researc h studies (most notably CEA 2013 a,b), the CE Usage Survey (see Appendix A) , and, to a lesser extent, CE sales data

. Typically, the installed base estimates have the lowest uncertainty of any AEC component

.



## 2.2 Power Draw by Mode All consumer electronics have at least two basic operating modes, e.g., on and off , and most have more

. For many CE, the operational power draw can vary appreciably due to changes in operation, e.g., computer microprocessor utilization scaling, imaging equipment activity, and (in some cases) display brightness

. For each CE category , we identified the most relevant pow er modes and developed
estimates for the average power draw of its installed bas e in each mode

.
Ideally, our assessment would use measurements of CE deployed in a larger sample ( of at least several hundred) of demographically representative U.S

. households to generate the power draw by mode



## x Annual Unit

Electricity Consumption by mode



# UEC active



# UEC sleep



# UEC off 

# Mode

Active

Sleep

Off 

# Σ =

=

= x

x = Hours of Annual Usage by mode Power

by mode



# P active



# P sleep



# P off 

### Device Unit Energy Consumption



# UEC x 

# IB

Residential Installed
Base



# AEC = 

# T active



# T sleep



# T off 

### Annual Energy ConsumptionFraunhofer USA Center for Sustainable Energy Systems 

### 16



### estimates

. Regrettably , the cost and time r equired to perform such a study lies well beyond the scope of this project

. Instead, we relied upon several different sources to estimate power draw by mode, including:

 Field measurement campaigns

 CE energy consumption characterization studies

 ENERGY STAR measurement databases

 Targeted measurements by Fraunhofer

 Measurements by CEA member companies

We were able to consult multiple sources for most CE categories, which increased our confidence in our power draw by mode estimates

.



## 2.3 Annual Usage by Mode

For most CE categories , the annual number of hours that an average device spends in different power
modes is the most difficult aspect of the UEC calculation to accurately estimate

. Ideally, the usage
estimates would be based on a sustained field measurement campaign that accurately recorded the
time that all CE spent in different modes from a sample of at least several hundred demographically representative U.S

. households, over the course of weeks or months

. Unfortunately, such a thorough
evaluation is beyon d the scope of this study

.

We used instead a combination of approaches to estimate annual usage by mode, including:

 The CE Usage Survey (see Appendix A)

 Data from prior field measurement campaigns 3



###  Data from prior CE energy consumption characterization s tudies

Notably , we used the CE Usage Survey responses as inputs into more refined models to assess computer and monitor usage (see Appendix B)

. We posed more questions for computers and video game consoles because they have higher AEC values that have part icularly high

– and are highly sensitive to

– uncertainties in their usage. In addition, we included several questions about smart phone and tablet usage because their energy consumption had not been thoroughly characterized in the past. Finally, we
also f ielded survey s about audio products and televisions

.

3 Although very useful, prior field measurement campaigns usually fall short of the ideal described due to a limited and biased (i.e., non

- random and unrepresentative) sample of households used and devices measured.Fraunhofer USA Center for Sustainable Energy Systems 

### 17



# 3 Energy Consumption of Consumer Electronics in U.S

. Homes

3.1 Summary
We estimate that 3.8 billion r esidential consumer e lectr onics consumed approximately 169 TWh of electricity in 2013 (see Table 3

- 1 and Figure 3

- 1 ), an amount equal to 12 % of residential electricity consumption and 4.5 % of total U.S

. electricity consumption in 2013 (DOE/EIA 2014a,b)

. This translates
into 8.4 and 1.8 percent of residential an d U.S

. total primary energy consumption 4 

### , respectively (DOE /EIA 2014a,b )

.

Table 3

- 1 : Residential CE e nergy c onsumption s ummary

.

Device UEC [kWh /yr ] Installed Base

[millions] AEC

[TWh] Computer s Desktop 186 88 16 Portable 53 93 4.9 Computer Speakers 42 63 2.6 Computer Monitors 58 9 7 5. 7 Network Devices Integrated Access Device 62 64 3.9 Modem 55 49 2.7
Router 59 94 5.5 Set

- top Boxes 75 67 5.0 Cable 128 113 15 Standalone 45 55 2.5 Sat ellite 112 94 11 Telco 106 32 3.4 Shelf

- Stereo / Compact Audio 75 6 4 4.8 Smart Phone 4.5 166 0.8 Speaker Dock 19 98 1.9 Tablet Computer 6.1 100 0.6 Television 166 301 50 Video Game Consoles 88 128 11 Other CE Devices 12 2,110 28 Total NA 3,8 0 9 16 9



### The remainder of this section presents the analyses for the devices selected for further analysis.

4 Using 10, 462 Btu of pr imary energy per kWh of electricity (DOE 2012).Fraunhofer USA Center for Sustainable Energy Systems 

### 18

Figure 3

- 1 : UEC, installed base, and AEC of CE categories evaluated in detail

. 12 6.1 4.5 19 45 42 55 106 62 75 53 59 58 112 88 128 186

166

0 50 100 150 200 Other CE Devices

Tablet Smart Phone Speaker Dock STB - Standalone Computer Speaker

Modem STB - Telco Internet Access Device Compact Stereo System

Portable PC Router and other Computer Monitor STB - Satellite Video Game Console STB - Cable Desktop PC Television

Unit Energy Consumption [kWh/yr] 100 166 98 55 63 49 32 64 64 93 94 97 94 128 113 88 301

0 100 200 300 400

Installed Base [millions] 2,110 28 0.6 0.8 1.9 2.5 2.6 2.7 3.4 3.9 4.8 4.9 5.5 5.7 11 11 15 16 50

0 10 20 30 40 50 Annual Energy Consumption [TWh]Fraunhofer USA Center for Sustainable Energy Systems 

### 19



## 3.2 Devices Selected fo r Further Analysis Although this study would have, ideally, evaluate d the AEC of all CE in greater detail, time and scope constraints required that we focus our effort on a subset of CE where a more refined analysis would yield the greatest value

. Consequ ently, in conjunction with CEA, we selected 17 distinct CE categories for more refined AEC analysis based on:

 Preliminary AEC estimates (higher more likely to be selected)

 Uncertainty in the preliminary AEC estimate (higher more likely to be selected)

.

Table 3

- 2 summarizes the categories selected for further analysis

. Since a relatively small number of CE categories account for the vast majority of all CE energy consumption (see Table 3

- 1 ), this approach does not have a major impact on the accuracy of our estimate for total residential AEC

.

Table 3

- 2 : CE analyzed in the current study

. Analyzed in Higher Detail Analyzed in Lesser Detail Computer Speaker AV R eceiver with surround sound processor Computer

- Desktop Bluetooth Headset Computer

- Portable Blu

- ray player Integrated Access Device Boombox Modem Camcorder Computer Monitor Copy machine (stand

- alone)
Router Cordless phone
Set

- top Box

– Cable Dig ital camera
Set

- top Box

– Standalone Digital picture frame
Set

- top Box

– Satellite DVD Player
Set

- top Box

– Telco eReader Shelf

- Stereo / Compact Audio External Storage Device Speaker Dock Fax Machine (stand

- alone) Smart Phone Handheld GPS Tablet Com puter Headphones Television Home Theater in a Box (HTIB) Video Game Console Internet Phone Device Mobile (non

- smart) Phone Portable DVD or Blu

- ray disc player Portable Game Devices Portable media/MP3 Player/CD Player Portable Wireless Speaker Printer + MFD (multi

- functional device) Projector Radio Scanner (stand

- alone) Soundbar Telephone Answering Device Video Cassette Recorder (VCR)Fraunhofer USA Center for Sustainable Energy Systems 

### 20



## 3.3 Computer Speaker s

3.3.1 Current Energy C o nsumption Computer speakers are defined as external, self

- powe red systems that reproduce audio signals generated by a computer. They typically incorporate a built

- in amplifier powered by a dedicated internal or external power supply that draws less power than home theater and stereo systems. Some smaller
systems, esp ecially for portable computers, are powered directly through a USB port. This analysis
excludes those devices

, as in the previous report (FhCSE 2011). A typical computer speaker system configuration includes either two speakers without a subwoofer , or two or five speakers with a
subwoofer (2.1 system/5.1 channel surround system). We were unable to find precise data on the
breakdown of speaker systems by the number of channels they have ; however, we were able to breakdown the installed base between speakers with and without a subwoofer in this study.

3.3.1.1 Installed Base The 2013 CE Usage Survey included questions about two types of computer speaker systems in households, namely, computer speakers with and without a subwoofer. Figure 3

- 2 summarizes the results for the portion of desktop and portable computers with zero, one, two, three or four and more computer speaker systems with and without subwoofer connected. The CE Usage Survey found that 40% of primary computers (i.e., the most

- used computer in a household) were connected to at least one computer speaker system without a subwoofer and 19% of primary computers were connected to a computer speaker system with a subwoofer. On average, secondary desktop computers had slightly fewer compu ter speaker systems without and with a subwoofer, 29% and 16%, respectively. We did not ask about speakers connected to a third computer. Instead, we assumed that the proportion of the remaining computers with a speaker system has not changed from 2010, i. e., we estimated that 16% of tertiary desktop computers had an external speaker (FhCSE 2011). In contrast, the survey responses indicated that less than 10% of primary and secondary portable computers were connected to any kind of computer speaker system. In total, we estimate that 72% of all residential computers are not connected to a computer speaker system.

Figure 3

- 2 : D istribution of computer speaker systems per desktop and portable computer

.



### The CE U sage Survey data for computers found an installed base of the 88 million home desktop computers and 93 million home portable computers, of which 60% and 57% are used as the primary

11% 55%

29%

5% 0% 0% 11% 71%

15%

2% 1% 0% 0% 20% 40% 60% 80% 100%

Don’t know 0 1 2 3 4+ Desktop Computer

Speakers without a subwoofer Speakers with a subwoofer

6% 87%

6% 1% 0% 0% 6% 89%

4% 0% 0% 0% 0% 20% 40% 60% 80% 100%

Don’t know 0 1 2 3 4+ Portable Computer

Speakers without a subwoofer
Speakers with a subwooferFraunhofer USA Center for Sustainable Energy Systems 

### 21



### desktop computer and primary portable computer, respectively. This yields a n installed base of 63 million computer speaker systems ( Table 3

- 3 ) , and represents a 15 percent decrease in the installed base of computer speaker systems from 2010 (FhCS E 2011). This likely is due to the recent decrease in
the i nstalled base of desktop PCS (13% since 2010 ) , since the survey indicates that most computer speakers are used with desktop PCs.

Table 3

- 3 : Installed base of computer speaker systems (CE Usage Survey)

.

Type Home Computers

[millions] % with s peakers and

no subwoofer % with s peakers and a subwoofer Total

[millions] Desktop 88 39% 20% 52 Portable 93 7% 5% 11 Total/ Avg. 181 23% 12% 63



### The data indicate a household penetration rate of 35% for computer speake r systems without a subwoofer and 18% for speaker system with a subwoofer. We could not find other estimates for the installed base of computer speaker systems.

3.3.1.2 U nit Energy Consumption
3.3.1.2.1 Power Draw 

### Computer speaker systems can be characterized by three opera ting modes (FhCSE 2011) :

 Active

– Device is actively used, playing music or other audio

 Active standby

– Device is neither playing audio, nor turned off manually

 Off

– Device is turned off manually but remains connected to the energy source

.

Since w e coul d not find new data sources for computer speaker power draw by mode , we measured the power draw in Jan. 2014 of two computer speaker sy stems with a subwoofer (2.1 channel) and one
computer sys tem without a subwoofer (2.0). Specifically, we selected compute r speaker systems to
measure from the best

- selling units sold at A mazon.com and Best Buy. The one 2.0 computer speaker system had a maximum power draw of 4 W at maximum volume, whereas in 2010 a 2.0 computer speaker system drew an average 6 W in active mod e (Meister et al. 2011).

Due to the limited number of measurements, we used straight averages to calculate the power draw for computer speakers in different modes. The straight average power draws for computer speakers without a subwoofer, we estimated fr om 18 speakers 5 

### measured by ECOS ( Meister et al. 2011 ), 6 speakers measured by ECW (Bensch et al. 2010), and the one 2.0 speaker system we measured in 2014. In contrast, a very small sample (n=4) of 2.1 system power draw measurements from Meister et al. (2 011) and Fraunhofer 6 

### has an average power draw of 44W . Results are shown in Table 3

- 4

.

5 Meister et al. (2011) notes n=18 in the Appendix and n=20 in its Figure 17.

6 Two 2.1 computer speaker systems were measured and had an average active

- mode power draw of 15W.Fraunhofer USA Center for Sustainable Energy Systems 

### 22

Table 3

- 4 : Power draw by mode for c omputer s peaker s ystem s

.

Type Power [W] Sources

Active Act ive Standby Off Without Subwoofer 5.5 2.4 1.6 Fraunhofer measurements, Meister et al. 2011, Bensch et al. 2 010
W ith S ubwoofer 44 7.5 1.2 Fraunhofer measurements, Meister et al. 2011



### 3.3.1.2.2 Usage 

### We did not ask about computer speaker usage in the 2013 CE Usa ge Survey
, so we based our usage estimates on the findings from the 2010 CE Usage Survey (FhCSE 2011). Thus, we assumed that usage patterns have not changed appreciabl y since 2010. We did, however, scale the 2010 usage estimates with computer usage in 201 3. In the 2010 CE Usage Survey
, 61% of U.S. adults answered that their computer speakers are always on when the computer is used, i.e . 3.1 hours per day on average, another 30% are on often or half of the time the computer is used, which results in an acti ve use of 2.7 hours per day. The data suggest in 2010 that 61% of computer speaker systems are not switched off over night. During the day when the computer is not in use, 39% of computer speakers are never off, while 54% are reported to be always or often off and 17% are reported off occasionally or half of the time. Overall, this suggests that the average speaker system spends 11% of the day in active mode, 47% of the time in active standby mode, and 42% of time in off mode ( Table 3

- 5 ).

Table 3

- 5 : Annual usage by mode of c omputer speaker systems (hours/year)

.
Active Active standby Off Sources
986 4,125 3,649 Current study computer usage, FhCSE 2011



### Versions 2.0 and 3.0 of the ENE RGY STAR specifications for audio products both require qualifying devices to have auto power down (APD) functionality with a default setting of two hours or less. This would tend to decrease the time spent in active standby mode by ENERGY STAR devices (EP A 2013). As of May, 2014, the ENERGY STAR products database did not include any computer speakers; therefore we did not include APD in our computer speaker usage model.

3.3.1.2.3 Unit Energy Consumption 

### We calculate a compu ter speaker UEC of 42 kWh/year (see Table 3

- 6 ).

3.3.1.3 Annual Energy Consumption We estimate that computer speakers consumed 2.6 TWh in 2013. Systems with a subwoofer accounted
for about 6 5 % of the AEC (see Figure 3

- 3 and Table 3

- 6 ).

Figure 3

- 3 : Unit Energy Consumption by mode and Annual Energy Consumption by computer speaker system type

.

Active Active

standby Off

0 15 30 45 UEC [kWh/year] With subwoofer Without

subwoofer

0 1 2 3 AEC [TWh]Fraunhofer USA Center for Sustainable Energy Systems 

### 23

Table 3

- 6 : UEC and AEC calculation for computer speaker systems

.

Type Installed

[millions] Percent Power [W] UEC [kWh/yr] AEC [TWh] Active S tandby Off Active Standby Off Total Without Subwoofer 42 65% 5.5 2.4 1.6 5.4 10 6.0 21 0.9 With Subwoofer 21 35% 44 7.5 1.2 44 31 4.5 79 1.7
Tot al/ Wt. Avg. 63 100% 19 4 .0 1.5 19 17 5.5 42 2.6



### 3.3.2 Comparison with Prior Energy Consumption Estimates
We estimate that the UEC value has increased from 2010 due to the integration of higher power speakers systems with subwoofers into our energy model. On th e other hand, total AEC decreased 7% from 2010, reflecting a 15% decrease in the installed base of computer speakers systems ( Table 3

- 7 )

.

Table 3

- 7 : Prior energy consumption estimate s for computer speaker systems

.

Year Installed Power [W] Usage [h/yr] UEC AEC Source [millions] Active Standby Off Active Standby Off [kWh/yr] [TWh]
2013 63 19 4 1.5 986 4,125 3,649 42 2.6 Current
2010 74 8 4 3 1,314 4,380 3,066 37 2.8 FhCSE 2011



### 3.3.3 R eferences
ECW. Bensch, I., S. Pigg, K . Koski and R. Belshe. 2010 . “Electricity Savings Opportunities for Home Electronics and Other Plug

- In Devices in Minnesota Homes

– A technical and behavioral field assessment.” Final Report by the Energy Center of Wis consin, R eport 257

- 1 . May.
EPA. 2013. ENERGY STAR program requirements Audio/Video. Version 3.0. U.S. Environmental Protection Agency. http://www.energystar.gov/ia/partners/prod_development/ revisions/downloads/audio_video/Final_Version_3_AV_Program_Requirements.pdf?5c24

- 7fe5

. May.

FhCSE. Urban, Bryan, K urt Roth, and Verena Tiefenbeck. 2011. “Energy C onsumption of C onsumer E lectronics in U.S. H omes in 2010.” Final Report to the Consumer Electronics Association. http://www.ce.o rg/CorporateSite/media/Government

- Media/Green/Energy

- Consumption

- of

- CE

- in

U

- S

- Homes

- in

- 2010.pdf . Dec.
Meister, B.C., C. Scruton,V. Lew, L. ten Hope and M. Jones. 2011. “Office Plug Load Field Monitoring Report.” Final Field Project Report by Ecos Consulti ng to the California Energy Commission

. http://www.energy.ca.gov/2011publications/CEC

- 500

- 2011

- 010/CEC

- 500

- 2011

- 010.pdf

. Apr.Fraunhofer USA Center for Sustainable Energy Systems 

### 24



## 3.4 Desktop Computer s Desktop comput ers include personal computers (PCs) housed in a box and computers with built

- in
monitors called All

- in

- One (AIO) PCs (also known as i ntegrated d esktop computers ) , such as iMac.

3.4.1 Current Energy Consumption
3.4.1.1 Installed Base
We estimate an installed base of 88 million desktop PCs that ha ve been used in the past month . This equals 83% of the ownership installed base of 105

- 113 million estimated reported by CEA (2013a,b). As with our 79% plugged

- in rate in 2010 (FhCSE 2011), this diff erence likely reflects that some desktop PCs in homes have not been recently used. Indeed, our estimate of ownership penetration for desktop PCs of 62% agrees with other sources (see Table 3

- 8 ).

Although our plugged

- in penetratio n estimate of 44% is lower than our previous report ( 62%
, Fraunhofer 2011), we think it is more accurate, because the 2013 CE Usage Survey includes questions that more precisely distinguish between device ownership and plugged

- in status during the past mon th

. Therefore, these results provide a richer representation of the plugged

- in and ownership installed bases.

Table 3

- 8 : Installed base estimates for d esktop PCs from different data sources.

Year Description Household penetration Households

[millions] Units/owner

household Installed Base

[millions] Source

2013 2013 Desktop PCs p lugged in last month 44% 53 1.67 88 CE Usage Survey Desktop PC ownership 62% * 74

- - CE Usage Survey
2013 Desktop PC ownership 6 3% 75 1.41 105 CEA 2013a 2013 Desktop PC ownership

- - - 113 CEA 2013c 2013 Desktop PC ownership

- - - 114 DRG 2013 2011 Desktop or portable PC ownership 76% †

- - - U.S. Census 2013 2012 Desktop or portable PC ownership

- - 1.80 ‡

- A&E 2012
2013 Deskt op PCs plugged in

- - - 88 Representative
* Estimated based on survey responses that indicated no ownership of desktop PCs ( 0 desktop PCs plugged in, but ≥1 ow ned , see Figure 3

- 4 )

. 

### To understand PC usage, we asked about the most used (primary) and second

- most used (secondary) desktop PCs. We classified desktop PCs without an external mon itor as an AIO unit. In addition, we assumed that AIO desktop PCs will tend to be the primary or secondary desktops given their recent
introduction into the market.

Table 3

- 9 : Plugged

- In installed base estimat es for Tower and All

- in

- One (AIO) Desktop Computers from CE Usage Survey.

Type Households [million s ] Plugged

- In [million units]

Not Own ed PCs Plugged

- In per Owner Household

0 1 2 3 ≥4 ≥1 † All Primary Second+
Tower 45 21 26 4.1 1.8 3.4 35 69.6 37 34 All

- in

- One

- - 16 1.0

- - 17 18.0 16 1.0 Any Desktop 45 21 42 5.1 1.8 3.4 53 87.6 53 35

† Equivalent to the household penetration of plugged

- in PCs. Primary: number of primary PCs. Second+: number of PCs that are not primary, i.e., secondary, tertiary, etc.; treated as secondary in energy model.Fraunhofer USA Center for Sustainable Energy Systems 

### 25

Figure 3

- 4 : Distribution of households with numbers of d esktop PCs plugged in during the past month (Nov 2013)

.


### We compared the AIO installed base estimates with sales data from DisplaySearch ( 2011

- 2013 ). Given an average age of desktop PCs of 3.2 years (CEA 2014), we consider a retirement age of 4 years for AIO desktop PCs along with sa les of AIO PCs since 2009 to develop another estimate of the installed base of AIO desktop PCs of 16.3 million. This assumes that no units sold since 2009 have been retired (see Table

3

- 10 ). This generally agrees with the 18 milli on units from the 2013 CE Usage Survey.

Table 3

- 10 : Plugged

- In installed base estimate for All

- in

- One Desktop Computers based on sales via consumer channels ( DisplaySearch 2014 ).

2009 e 2010 2011 2012 2013 Q1

- Q3 Sales (All North America)

- 3.6 3.2 3.1 3.7 Sales (U.S. Only) †

- 3.2 2.9 2.8 3.3 Installed Base since year (U.S.) 16.3 12.2 9.0 6.1 3.3
† Adjusted based on U.S. and Canada population ratios

, 316M and 35M (U.S. Census 2013

, Statistics Canada 2013).

e Estimated based on extrapolation from 2010

- 2013.



### 3.4.1.2 Unit Energy Consumption
3.4.1.2.1 Power Draw 

### PC power draw varies with operational mode. For our analysis, we use the modes defined in the ENERGY STAR requirements for Computer v6.0 (EPA 2013a):

 Active : W hen the PC is actively used, or idles for a short while awaiting user input and before entering lower power modes.

 Short Idle : W hen the PC has been idle for about 5 minutes and has entered a low power mode
with the monitor still on.

 Long Idle : W hen the PC has bee n idle for about 15 minutes and has entered a low power mode
with the monitor off.

 Sleep : Entered manually or automatically after about 30 minutes from which the PC can quickly
wake.

 Off : PC is turned off but remains plugged in.

The main difference from t he previous ENERGY STAR specification (v5.2) is the splitting of the idle state into Short and Long Idle to better characterize computers with integrated monitors ( i.e., AIO desktop

PC s). 0% 10% 20% 30% 40%

0 1 2 3 ≥4 Weighted % of U.S. Households

Tower

AIOFraunhofer USA Center for Sustainable Energy Systems 

### 26



### Table 3

- 11 presents recent power draw esti mates for desktop PCs. Together, these sources indicated that average power draw values have decreased for all modes since 2010. The much larger difference between short idle and long idle mode power draw of the AIOs relative to the Towers reflects the pow er draw of the integrated display

.

Table 3

- 11 : Power draw estimates for d esktop c omputers from different data sources.

Type Power Draw [W] Year Source

Active Short Idle Long Idle * Sleep Off
Tower

- 48 47 2.5 1.1 2012 EPA 2013b †

Tower

- - 46 2.1 1.0 2013 NRDC 2013 AIO

- 63 36 1.9 0.9 2012 EPA 2013b †

AIO

- - 30 1.8 0.9 2013 NRDC 2013 Any Desktop

- 51 45 2.4 1.0 2012 EPA 2013b † Any Desktop

- 67

- 2.4 0 2012 LBNL 2013 ‡ Any Desktop

- - 60 4 2 2010 Fraunho fer 2011
* The ENERGY STAR v6.0 specification for computers maps the Idle mode of v5.2 as equivalent to Long Idle in v6.0. † Power draw of each test device in the dataset reweighted based on the portion of unit sales (21%) meeting the ENERGY STAR v6. 0

s pecifications (EPA 2012). ‡ The field study (with 39 desktop PCs) had grouped modes as “high power”>10W, “low power”≤10W, and "off"=0W. This roughly maps to Short Idle and Sleep power draws, respectively, in the ENERGY STAR v6.0 specification for computers.



### We use data from these d ata sets to derive a representative estimate of power draw for different modes (see Table 3

- 11 ). In particular, we consider a mixture of newer and older PCs in the total installed base. We use power draw values from the ENERGY STA R v6.0 dataset of qualified and unqualified PCs (EPA 2013b) to represent PCs sold from 2011 to 2013, and power draw values from our previous study ( Fraunhofer 2011) to represent older PCs. We use the results of (CEA 2014) for the age of desktop PCs
owned to derive a relative weight between newer and older PCs ( Table 3

- 12 ).

Table 3

- 12 : Estimated desktop PC installed base by computer vintage to evaluate relative power draw characteristi cs derived from Figure 3 of (CEA 2014 ). Average age: 3.2 years.

“Older” “Newer” Year of Purchase 2009 2010 2011 2012 2013 Age ≥4 3 2 1 <1
% of Desktop PCs Owned 10% 12% 19% 18% 41% 41% 59% Source for Power Draw Model Fraunhofer 2011 EPA 2013b



### Most of the data sources in Table 3

- 11 do not include estimates for power draw in active mode. Based

on mete red power draw of one notebook in a commercial setting, NRDC estimates an active power
draw overhead of 30% more than in idle mode ( NRDC 2013 ) . This overhead is similar to that reported by CEC (2012), which metered one desktop PC purchased in 2007 running an office productivity benchmark test. A lab metering study of four desktop PCs browsing consumer

- oriented websites and videos found
lower overhead of 8

- 21% (Fraunhofer 2013). Therefore, we apply a scaling factor of 115%, i.e., active mode power draw is 15 % higher than short idle mode power draw. Ultimately, the power draw values by mode that we use to represent the installed base agree quite well with the LBNL field monitoring study of 559 households (LBNL 2013).Fraunhofer USA Center for Sustainable Energy Systems 

### 27

Figure 3

- 5 : Representative power draw by mode of tower and AIO desktop PCs.



### 3.4.1.2.2 Usage 

### A desktop PC enters different operational modes depending on whether the user is currently using it, how recently it was last used, how the user manually manages its power, and its automatic power management settings. We compute the time each PC spends in different operational modes using the energy model presented in Appendix B.1. O ur model draws heavily on the data gathered from the CE Usage Survey, where we asked re spondents about their household use of the two most used desktop PCs. The subsequent subsections explain findings for key aspects of the model in more detail.

3.4.1.2.2.1 Usage per Session 

### We evaluated the active usage of PCs during the day for each session and for th e whole day to account for the cumulative time desktop PCs spend in different operational modes. More specifically, we evaluated the usage for different periods of the day

, pre

- evening (morning and afternoon) and evening

, via specific survey questions, and inferred usage for weekdays or weekends based on what day “yesterday” was for the survey response. On average, households’ primary desktop PCs are used about
two times before the evening, and about once in the evening. In contrast, secondary PCs are used about half as frequently. For both primary and secondary desktop PCs, we found that each session lasts for about one hour, and appears to be shorter on weekend days than on weekdays ( Figure 3

- 6 ).

65 87

70

57 75

61 56

42 54

3.5 2.7 3.4 1.6 1.4 1.6 0 20 40 60 80 100

Tower All-in-One Any Desktop

Active Short Idle Long Idle Sleep Off Power Draw [W]Fraunhofer USA Center for Sustainable Energy Systems 

### 28 Primary Desktop PC

Secondary Desktop PC

Figure 3

- 6 : Average per session usage duration and number of sessions “yesterday” for primary and secondary desktop PCs.



### 3.4.1.2.2.2 Usage per Day 

### On average, households use primary and secondary desktop PCs for about 3 to 4 hou rs per day, with the primary desktop PC used somewhat more than secondary ones (3.9 vs. 3.0 hours).

Primary Secondary

Figure 3

- 7 : Total usage duration “yesterday” for primary and secondary desktop PCs.



### 3.4.1.2.2.3 Power Management 

### PC energy consumption can be reduced through power management (PM). The user may do so using manual routines of power management (e.g., by putting the PC to sleep at night), or by enabling automatic PM settings (e.g., auto

- hibernate to ha ve the computer save its state and automatically turn off after a chosen period of inactivity). We discuss these two manual and automatic power management
methods in the next section.

1.2 1.3 1.1 1.1 1.2

0.8

0 1 2

Any Day Week-day Week-end Per Session Usage [hours] Pre-Evening Evening

1.7 1.6 2.0

1.2 1.3

1.0

0 1 2

Any Day Week-day Week-end # Sessions per Day Pre-Evening Evening

1.0 1.1

0.6 1.3 1.4

0.8

0 1 2

Any Day Week-day Week-end Per Session Usage [hours]

0.8 0.7 1.0 0.8 0.9

0.6

0 1 2

Any Day Week-day Week-end # Sessions per Day

0 1 2 3 4 5

Any Day Weekday Weekend Evening 1.6 1.8 1.1 Pre-Evening 2.3 2.4 2.1 Whole Day 3.9 4.1 3.2 h/day

0 1 2 3 4 5

Any Day Weekday Weekend Evening 1.7 1.9 1.0 Pre-Evening 1.4 1.3 1.5 Whole Day 3.0 3.2 2.6 h/dayFraunhofer USA Center for Sustainable Energy Systems 

### 29



### Manual Power Management We asked U.S. adult s how often they manually tur ned their PC off or put it to sleep. The survey results indicate that users tend to manually turn off their desktop PCs (40% of the time during the day and 56% at night), while leaving them on 37% of the time during the day. Desktop PCs are manually put to sleep about 22% of the time during the day. However, even if a PC is left on, automated PM may cause the PC down to a low power mode.

Daytime Night *

* Night

- sleep and

- left

- on determined from daytime ratio s. Figure 3

- 8 : Likelihood of users manually setting desktop PCs into various modes for the daytime or night. 

### Automatic Power Management Setting To infer the automatic PM settings, we asked U.S. adult s about the initial state or start

- up duration of their PC at the start of the day “yesterday” if they were the first to use it. For example, if the display is already on, this indicates that PM is disabled, while if the computer takes more than a few seconds to boot up, auto

- hibernate is enabled. We als o account for whether the U.S. adult s had manually turned
the PC off. Our model assumes that PCs with auto

- hibernate enabled also have auto

- sleep enabled, and
PCs with auto

- sleep enabled have auto

- screen off enabled. Based on the survey responses, 90% of
de sktop PCs have some level of power management enabled, particularly with auto

- screen off (53%) where the PC enters short idle mode, followed by auto

- sleep (31%), which engages the long idle mode.

Figure 3

- 9 : Percentage of desktop PCs with different automatic PM modes enabled.



### 3.4.1.2.2.4 Time in Operational Modes 

### Though not necessarily the same, the time distributions for different desktop types (Tower vs. AIO) and priorities (primary vs. secondary) are very similar. W e present only their weighted average, but account for the differences in the energy model analysis.

32% 45% 37% 25% 18% 22% 43% 37% 40%

0% 20% 40% 60% 80% 100%

Primary Secondary Any Desktop % of Users with Manual Power Management

Off Sleep Left On

23% 34% 27% 18% 14% 16% 59% 53% 56%

0% 20% 40% 60% 80% 100%

Primary Secondary Any Desktop

10% 6% 7% 30% 32% 31% 51% 49% 53% 9% 14% 10%

0% 20% 40% 60% 80% 100%

Primary Secondary† Any Desktop % Desktop PCs in Power Management Mode PM Disabled
Auto-Screen Off Auto-Sleep

Auto-Hibernate

†High uncertainty for secondary PC, 37% of responses are “Don’t Know.”Fraunhofer USA Center for Sustainable Energy Systems 

### 30



### Figure 3

- 10 shows the average amount of time each desktop PC spent in various operational modes. Desktop PCs spend a considerabl e amount of time in sleep and off modes (68%) mainly due to manual power management or automatic powering down after each session of use. Table 3

- 13 shows our results for the portion of time in Active + Idle modes; they are simil ar to those from other studies.

‡ Our model defines night as when the household has gone to sleep, so we assume no active usage.
Figure 3

- 10 : Average time spent in various operational modes in one day and in one year for desktop PCs . W eighted average across primary and secondary tower and AIO desktop PCs.

Table 3

- 13 : Comparison of percentage of time desktop PCs spent in various operational modes with othe r data sources.

Time [%] in Operational Mode
Year Setting Source Active Short Idle Long Idle Active + Idle Sleep Off
14% 5.2% 12% 32% 24% 44% 2013 R esidential CE Usage Survey

- 32%

- 32% 48% 20% 2012 R esidential LBNL 2013 *

18%

- 21% 39% 25% 36% 2 010 R esidential Fraunhofer 2011

- 35% 15% 50% 5% 45% 2013 Office ENERGY STAR v6.0 (EPA 2013a) †

- - 40% 40% 5% 55% 2009 Office ENERGY STAR v5.2 (EPA 2009) †

41%

- - 41% 48% 20% 2008 Office Microsoft 2008

* Field measurement with a small sample size of 3 9 desktop PCs.
† ENERGY STAR values are based on studies of computer usage in office buildings (ECMA 2010, Microsoft 2009).



### 3.4.1.3 Unit and Annual Energy Consumption We compute the energy consumption by multiplying the time a PC spends in each operational mode with the corresponding power draw in that mode. Figure 3

- 11 shows the energy consumption in various operational modes. Active usage accounts for the largest portion of energy consumption (47%), followed by long idle (31%), then s hort idle (15%). Together, sleep and off modes combine for 7% of energy consumption.

0 4 8 12 16 20 24

Whole Day PreEvening Evening Night‡

Off 11 3.8 2.1 4.7 Sleep 5.7 2.6 1.4 1.8 LongIdle 3.0 1.2 0.7 1.1
ShortIdle 1.3 0.6 0.4 0.3

Active 3.4 1.9 1.6 0.0

Total 24 10 6.1 7.9 hours/day

0 2,000 4,000 6,000 8,000

All Days Weekdays Weekends
Off 3,883 2,570 1,339 Sleep 2,088 1,484 604 LongIdle 1,083 902 161

ShortIdle 458 357 99

Active 1,248 944 300 Total Plugged In 8,760 6,257 2,503 hours/yrFraunhofer USA Center for Sustainable Energy Systems 

### 31 ‡ Our model defines night as when the household has gone to sleep, so we assume no active usage.
Figure 3

- 11 : Total energy consumed in various operational modes in one day and in one year for desktop PCs . W eighted average across primary and secondary tower and AIO desktop PCs. 

### We found that the Unit Energy Consumption (UEC) of a typical desktop PC is 186 kWh/year, with tower and AIO desktop PCs having similar UECs. The Annual Energy Consumption (AEC) for all desktop PCs is 16 TWh/year.

Table 3

- 14 : UEC and AEC values for desktop PCs.

Type Energy Consumption

[Wh/day] UEC [kWh/ yr] Installed Base [millions] AEC

[TWh/yr] Active Short Idle Long Idle Sleep Off Total
Tower 514 87 24 63 7.3 6.2 188 70 13 AIO 505 89 43 41 5.6 5.7 184 18 3.3 Any Desktop 511 87 28 58 7.0 6.2 186 88 16



### 3.4.2 Comparison with Prior Energy Consumption Est imates We found a decrease in the both desktop PC UEC and AEC from 2010. A major reason is the drop in plugged

- in installed base (101 to 88 million) driven by a sharp decrease in sales market share (22% in 2010 to estimated 8% in 2013, CEA 2013b) and resul ting decreased household ownership installed base of desktop PCs (128 million (CEA 2010) to 105 million (CEA 2013a)) and almost a 10

- fold increase in the ownership of tablets, from 4% (Fraunhofer 2011) to 39% (CEA 2013a). This trend could also explain the
decrease in active use time which we found.

We refined our computer usage survey from 2010, and believe that it increases the accuracy of our estimates for time in operational modes for desktop PCs. Specifically, we have increased the precision of

our su rvey questions by asking about three times of day (morning, afternoon, and evening) that are in better agreement with our analysis of usage patterns reported in ATUS (2012); see details in Appendix
Section B.1.3 . This provides a richer representation of usage throughout the whole day than our previous estimates (Fraunhofer 2011). In addition, breaking the day into more discrete time periods should increase the accuracy of peoples’ responses for total computer usa ge

.
On the other hand, our estimate for the portion of PCs with PM enabled is lower than our previous report (38% vs. 70%) due to several improvements in our energy model. First, we infer PM settings by

0 100 200 300 400 500 600

Whole Day PreEvening Evening Night‡

Off 17 6.2 3.4 7.6 Sleep 19 8.6 4.6 5.9 LongIdle 160 64 36 61

ShortIdle 76 35 23 18

Active 238 129 109 0

Total 511 243 175 92 Wh/day

0 50 100 150 200

All Days Week-days Weekends
Off 6.2 4.1 2.2 Sleep 7.0 5.0 2.0 Long Idle 58 49 9

Short Idle 28 22 6.0

Active 87 66 21

ALL 186 145 40 kWh/yrFraunhofer USA Center for Sustainable Energy Systems 

### 32



### asking about the PC state at the beginning of the day (vs. anytime during the day) and this better captures the PM settings by eliminating usage by other household members of which the respondent may be unaware. Next, to estimate the portion of PCs in auto

- hibernate, we subtract responses that
indicated that the PC was manually turned off at night from responses that indicated the PC is off at the beginning of the day. Therefore, assuming that users who manually turn off their PC s do not use auto

hibernate, this significantly reduces the portion of PCs with a uto

- hibernate enabled.

Table 3

- 15 : Current and prior energy consumption estimates for desktop PCs.

Year Units [millions] Power Draw [W] Time in Mode [hr/yr] PM *
Enabled UEC

[kWh/yr] AEC

[TWh/yr] Source Acti ve Sleep Off Active Sleep Off
2013 88 62 † 3.4 1.6 2,789 ‡ 2,088 3,883 38% 186 16 Current
2010 101 60 4 2 3,420 2,150 3,190 70% 220 22 Fraunhofer 2011 2006 90 75 4 2 2,954 350 5,456 20% 235 21 TIAX 2008 2005 85 75 4 2 2,950 350 5,460 20% 234 20 TIAX 2006 2005 108 58

- 3 2,116

- 183 15% 151 16 CCAP 2005 2001 68 50 25 1.5 1,495 163 7,102 20% 90 6.1 LBNL 2004 1999 54.5 50 25 2 717 65 7,978 25% 49 2.7 LBNL 2001
* Percent of computers with power management enabled, i.e., auto

- sleep or auto

- hibernate, but excluding auto

- screen off. † Weighed average of power draw for active, short idle, and long idle modes. ‡ Combined time in active, short idle, and long idle modes.



### 3.4.3 References A&E. 2013. “The Infinite Dial 2013: Navigating Digital Platforms.” Arbitron & Edison Research. Apr. 2, 2013. http://www.arbitron.com/downloads/InfiniteDial2013.pdf . Retrieved Sept. 16, 2013. A&E. 2012. “The Infinite Dial 2012: Navigating Digital Platforms

– Pr esentation Companion.” Arbitron & Edison Research. April, 2012. http://www.edisonresearch.com/wp

content/uploads/2012/04/2012_infinite_dial_comp anion_report.pdf . Retrieved Sept. 16, 2013.
ATUS. 2012. “ American Time Use Survey

— 2012 Microdata Files .” Jun. 20, 2013. United States Department of Labor. http://www.bls.gov/tus/datafiles_2012.htm . Retrieved Oct. 30, 2013.

CEA

. 2010

. “12 th 

### Annual hou sehold CE Ownership and Market P otential.” CEA Market Research Report

. Consumer Electronics Association

. May , 2010. Consumer Electronics Association.
CEA. 2013a. “15 th 

### Annual CE Ownership and Market Po tential Study.” CEA Market Research Report, April, 2013. Consumer Electronics Association.
CEA. 2013b. “U.S. Consumer Electronics Sales & Forecasts 2009

- 2014.” CEA Market Research Report, July, 2013. Consumer Electronics Association.

CEA. 2013c. Steve Koen ig. Private correspondence, Nov. 2013. Consumer Electronics Association.
CEA. 2014. “Consumer Outlook on Tablets

– Jan. 2014 Edition.” Jan. CEC. 2012. “How low can you go? A White Paper on Cutting Edge Efficiency in Commercial Desktop Computers.” Public In terest Energy Research (PIER) Program Final Project Report. Ecos Consulting.
Mar. 2012. http://www.energy.ca.gov/2012publications/CEC

- 500

- 2012

- 065/CEC

- 500

- 2012

- 065.pdf

. Retrieved Feb. 3, 2014. DisplaySearch. 2014. “DisplaySearch Quarterly Desktop Monitor Shipment and Forecast Report, 2011

- 13.” Jan. 2014.

ECMA. 2010. ECMA

- 383 3rd Edition

- Majority Profile. Dec. 2010. http://www.ecma

international.org/publications/files/ECMA

- ST/ECMA

- 383.pdf . Retrieved Dec. 9, 2013.Fraunhofer USA Center for Sustainable Energy Systems 

### 33



### EPA. 2009. “ENERGY STAR Computer Program Requirements Version 5.2.” https://www.energystar.gov/ia/partners/product_specs/program_reqs/Computers_Program_Requir ements.pdf?0e9f

- 5a79 . Retrieved Jan. 30, 2014. EPA. 2012. “ENERGY STAR Unit Shipmen t and Market Penetration Report 2012.” December, 2012. http://www.energystar.gov/ia/partners/downloads/unit_shipment_data/2012_USD_Summary_Repo

rt. pdf . Retrieved Sept. 16, 2013. EPA. 2013a. “ENERGY STAR Computer Program Requirements Version 6.0.” Sept. 12, 2013. http://www.energystar.gov/products/specs/comp uter_specification_version_6_0_pd . Retrieved Dec. 12, 2013. EPA. 2013b. “ENERGY STAR Computers Draft 2 Version 6.0 Dataset.” May 15, 2012. https:// www.energystar.gov/products/specs/system/files/Computers_Draft_2_Dataset_masked.xlsx

. Retrieved Sept. 16, 2013. EPA 2013c. “ENERGY STAR Qualified Product List.” Oct. 28, 2013. http://downloads.energystar.gov/bi/qplist/Computers_Product_List.xls . Retrieved Feb. 5, 2014.
FhCSE. Urban, Bryan, K urt Roth, and Verena Tiefenbeck. 2011. “Energy C onsumption of C onsumer E lectronics in U.S. H omes in 2010.” Final Report to the Consu mer Electronics Association. http://www.ce.org/CorporateSite/media/Government

- Media/Green/Energy

- Consumption

- of

- CE

- in

U

- S

- Homes

- in

- 2010.pdf . Dec.

FhCSE. 201 3

. Roth, K., S. Patel, and J. Perkinson. “The Impact of Internet Browsers on Computer Energy Consumption.” Jun. 2013.

LBNL. 2013. Greenblatt, J. B. 2013. “Field data collection of miscellaneous electrical loads in Northern Califo rnia: Initial results.” Lawrence Berkeley National Laboratory. LBNL Paper LBNL

- 6115E. Jul. 22, 2013. http://escholarship.org/uc/item/5cq425kt . Retrieved Sept. 16, 2013.
Microsoft. 2008. “Microsoft Po wer Transition Report.” Microsoft Corporation. http://www.energystar.gov/ia/partners/prod_development/revisi ons/downloads/computer/Microso ft_PowerTransitionReport.pdf?%20f0fe

- 40d2 . Retrieved Dec. 9, 2013. Pew. 2012. “Adult gadget ownership over time.” Pew Internet surveys 2006

- 2013. April, 2012. http://www.pewinternet.org/Trend

- Data

- (Adults)/Device

- Ownership.aspx . Retrieved Oct. 30, 2013. Pew. 2013. “Demographics of internet users” Apr. 17

– May 19, 2013. http://pewinternet.org/Static

Pages/Trend

- Data

- (Adults)/Whos

- Online.aspx . Retrieved Jan. 30, 2014. NRDC. 2013. “NRDC’s Response to CEC’s Invitation to Participate in the Development of Appliance Energy Efficiency Measures. NRDC Computers Att achment 2. ENERGY STAR v6.0 Dataset v2 with additions from NRDC.” May 9, 2013. http://www.energy.ca.gov/appliances/2013rulemaking/documents/responses/Consumer_Electronic s_12

- AAER

2A/NRDC_Response_to_CEC_Invitation_to_Participate_with_Excel_Spreadsheets_REFERENCES /NRD C_Computers_2_ESTAR

- NRDC_v6.0_Dataset_v2.xlsx . Retrieved Dec. 12, 2013. Statistics Canada. 2013. “Canada Population Estimates.” http://www.statcan.gc.ca/start

- debut

eng.html

. Oct. 2013. Ret rieved Jan. 30, 2014.

U.S. Census . 2012. State & County QuickFacts. http://quickfacts.census.gov/qfd/states/00000.html

. Retrieved Jan. 25, 2014. U.S. Census. 2013. “US Census 2011: Computer and Internet Use in the United States.” May 1, 2013. http://www.census.gov/prod/2013pubs/p20

- 569.pdf . Retrieved Sept. 16, 2013.Fraunhofer USA Center for Sustainable Energy Systems 

### 34



## 3.5 Portable Computers Portable computers includes both laptops (a lso known as notebooks) and netbook computers (small er, less powerful laptops ) , but excludes mobile computing devices such as smart phones and tablets.

3.5.1 Current Energy Consumption 3.5.1.1 Installed Base We estimate a plugged

- in installed base of 93 million portabl e PCs used in the past month ( Nov. 2013). The plugged

- in installed base measured from CE Usage S urvey is 63% of the ownership installed base of 148 million as reported by CEA (2013a). This is likely due to some portable PCs not being recently used.
The survey also reports the ownership penetration for portable PCs of 64%

, which is similar to other sources (see Table 3

- 16 ).

Although the estimate of plugged

- in penetration of 44% is lower than in our previous report of 62% (Fraunhofer 2011), we think that it is accurate

, because the 2013 CE Usage Survey included questions to distinguish between households that did not own a portable PC and households that have at least one
but that ha d not plugged one in within the past month . Therefore, the results provide a richer representation of the plugged

- in and ownership installed bases.

Table 3

- 16 : Installed base estimates for portable PCs from different data sources.

Year Description Household penetration Households

[millions] Units/owner

household Installed Base

[millions] Source

2013 2013 Portable PCs plugged in last month 45% 53 1.75 93 CE Usage Survey Portable PC owner ship 64% * 76

- - CE Usage Survey 2013 Portable PC ownership 65% 77 1.90 148 † CEA 2013a 20 11 Desktop or Portable PC ownership 76%

- - - U.S. Census 2013 2012 Desktop or Portable PC ownership

- - 1.80 §

- A&E 2012
2013 Portable PCs plugged in

- - - 93 Rep resentative
* Estimated based on survey responses that indicated no ownership of portable PCs (see Figure 3

- 12 ).
† 123.4 million notebook and 24.3 million netbook portable PCs. § Based on 61% of Online U.S. adu lts; 2012 U.S. population as 313.9M, 76.5% of population over 18 years old (U.S. Census 2012); 85% of U.S. adults use the Internet (Pew 2013).

† 0 portable PCs plugged in, but ≥1 owned. * Ownership data from (CEA 2013a)

. Figure 3

- 12 : Distribution of h ouseholds by number of p ortable PCs owned or plugged

- in during the past month (Nov. 2013 )

. 

### According to CEA (2013), netbooks account for 17% of all portable PCs. Although we expect fewer
netbooks to be used and plugged

- in in 201 3 due to their declining sales and discontinued production

0% 10% 20% 30% 40%

Do Not Own 0† 1 2 3 ≥4

Plugged In 36% 19% 32% 6.6% 2.8% 3.2% Ownership* 35% 33% 16% 9% 7% Weighted % of U.S. HouseholdsFraunhofer USA Center for Sustainable Energy Systems 

### 35



### (DigiTimes 2012)

, for an estimate, we use this ratio to compute the annual energy consumption of all portable PCs

.

Table 3

- 17 : P lugged

- In installed base estimates for notebook and netbook portable PCs from the CE Usage Survey.

Type Households [million s ] Plugged

- In [million units]

Not Own ed PCs Plugged

- In per Owner Household

0 1 2 3 ≥4 ≥1 † All Primary Second+ Notebook 36 19 32 6.6 2.8 3.2 44 77.7 44 33 Netbook 7 3.8 6.3 1.3 0.6 0.6 8.8 15.3 8.7 6.6 Any Portable 43 23 38 7.9 3.3 3.8 53 93.0 53 40

† Equivalent to the household penetration of plugged

- in PCs. Primary: number of primary PCs. Second+: number of PCs that are not primary, i.e., secondary, tertiary, etc.; treated as secondary in energy model.



### 3.5.1.2 Unit Energy Consumption
3.5.1.2.1 Power Draw 

### We consider the same power draw modes (EPA 2013a) for portable PCs as for desktop PCs in Section

3.4.1.2 : active, short idle, long idle, sleep, and off.

Table 3

- 18 presents recent power draw estimates for portable PCs. Overall, power draw has decreased compared to the 2010 estimate ( Fraunhofer 2011) by about half for sleep and off modes, and about a quarter for idle mode.

Table 3

- 18 : Power draw estimates for portable PCs from different data sources.

Type Power Draw [W] Year Source

Active Short Idle Long Idle * Sleep Off Notebo ok

- 14 9.4 1.0 0.5 2012 EPA 2013b †
Notebook

- - 10 1.1 0.5 2013 NRDC 2013 Notebook 21 15

- - - 2013 Fraunhofer 2013 §
Netbook

- 9.1 6.1 0.8 0.5 2012 EPA 2013b † Any Portable

- 14 9.1 1.0 0.5 2012 EPA 2013b † Any Portable 40

- - 1.1 0 2012 LBNL 2013 ‡

An y Portable

- - 19 2 1 2010 Fraunhofer 2011
* ENERGY STAR v6.0 specification for computers maps the Idle mode of v5.2 as equivalent to Long Idle in v6.0. † Power draw of each test device in the dataset reweighted based on unit sales of 69% of unit shipme nts meeting the ENERGY STAR v6.0 specifications (EPA 2012). Netbook models identified by processor type (10% of dataset). § Lab metering of 6 notebook portable PCs. ‡ The field study (with 11 portable PCs) had grouped operational modes as “high power”>1 0W, “low power”≤10W, and "off"=0W. This roughly maps to a combined active, short idle and long idle power draw, sleep, and off power draws, respectively, in the ENER GY STAR v6.0 specification for computers.



### Similar to Section 3.4.1.2 , we derive a representative estimate of power draw for different modes with a weighted average of newer and older PCs in the total installed base (see Table 3

- 19 ).Fraunhofer USA Center for Sustainable Energy Systems 

### 36

Table 3

- 19 : Determining relative power draw characteristics from age of portable PCs
, derived from Figure 3 of (CEA 2014 ). Average age: 2.4 years.

“Older” “Newer” Year of Purchase 2009 2010 2011 2012 2013 Age [years] ≥4 3 2 1 <1

% of Portable PCs Owned 19% 22% 26% 17% 17% 41% 60% *

Source for Power Draw Model Fraunhofer 2011 EPA 2013b

* Total does not sum to 100% due to rounding

. 

### Several data sources suggest a higher ratio of power draw in active to short idle mod e for portable PCs than for desktop PCs, e.g., 1.4 for Fraunhofer (2013) and 1.3 for NRDC (2013). Therefore, we apply a scaling factor of 1.3 for active

- mode power draw relative to short idle mode power draw. Furthermore, since Fraunhofer (2011) referred t o ENERGY STAR v5.2 (EPA 2009) and does not include a power draw estimate for the short idle mode, we apply the same overhead ratio for short idle to long idle (1.5:1) as EPA (2013b).

Unlike a desktop PC, a portable PC may be disconnected from the wall soc ket and run on its battery. The battery will need to be charged with an external power supply (EPS). Therefore, in addition to the power modes for desktop PCs (see Section 3.4.1.2 ), we consider the following additional operati onal modes due to the power draw of the EPS:

 Active + Charging: when the portable PC is actively used and charging its battery.

 Off + Charging: when the portable PC is off and charging its battery.

 Unplugged: when the portable PC is unplugged from its EPS.

 EPS Unplugged: when the EPS is also unplugged from the wall socket. There is no power draw (0W) in this “mode.”

DOE (2012) provides an estimate for the power draw of the EPS of notebook and netbook portable PCs (see Table 3

- 20 ). According to the test method for ENERGY STAR v6.0 (EPA 2013b), we consider the EPS power draw to already be accounted for when the portable PC is not charging and not unplugged.

Table 3

- 20 : Power draw estimat es of the external power supply for portable PCs ( DOE 2012), w eighted by shipment distribution. This excludes the power draw due to the portable PC.

Type External Power Supply Power Draw [W]

Active * + Charging Active * Sleep Off + Charging Off Unplugged

Notebook 11 4.6 0.8 6.3 0.7 0.7 Netbook 6.6 2.8 0.6 3.8 0.5 0.5
* We consider EPS active mode to correspond to the weighted average of the portable PC active, short

- and long

- idle modes.Fraunhofer USA Center for Sustainable Energy Systems 

### 37

Figure 3

- 13 : Representative power draw by mode of notebook and netbook portable PCs.



### 3.5.1.2.2 Usage 

### A portable PC enters different operational modes depending on whether the user is currently using it, how recently it was last used, how the user manually manages its power, its automatic power management settings, how often it is charging, and how often it is unplugged from the EPS. We compute the time each PC spends in different operational modes using the energy model presented in Appendix B.1. Our model draws heavily on the d ata gathered from the CE Usage Survey where we asked
U.S. adults about their household use of the most used (primary) portable PC and second

- most used (secondary) portable PCs. The subsequent subsections explain findings for key aspects of the model in
more detail.

3.5.1.2.2.1 Usage per Session 

### We evaluated the active usage of PCs during the day for each session and for the whole day to account for the cumulative time portable PCs spend in different operational modes. More specifically, we
evaluated the usage for different periods of the day (morning and evening) via specific survey questions, and inferred usage for weekdays or weekends based on what day “yesterday” was for the survey response. We estimate that an average primary portable PC is used abou t 1.5 times before the evening, and about once in the evening. The secondary PC is used about half as much. We found that each session lasts about one hour, and is likely somewhat shorter on a weekend than on a weekday.

0 10 20 30 40

Notebook Netbook Any Portable Active + Charging 36 23 34

Active 30 19 29

Short Idle 23 15 22 Long Idle 15 10 15 Sleep 1.6 1.2 1.6 Off + Charging 6.3 4.1 6.0
Off 0.8 0.8 0.8 Unplugged 0.6 0.5 0.6 Power Draw [W]Fraunhofer USA Center for Sustainable Energy Systems 

### 38 Primary Portable PC

Secondary Portable PC

Figure 3

- 14 : Average per session usage and number of sessions “yesterday” for primary and secondary portable PCs.



### 3.5.1.2.2.2 Usage per Day 

### On average, household occupants actively use portable PCs for 2.8 hours per day, using the primary portable PC more than secondary ones (3.4 vs. 2.4 hours), more before the evening than after (1.9 vs. 1.5 hours for primary), and more during the weekdays than weekends (3.6 vs. 2.8 hours for primary).

W e note that prim ary desktop PCs have a higher reported active usage per day than primary portable PCs (3.9 vs. 3.4 hours ).

Primary Secondary

Figure 3

- 15 : Average total usage “yesterday” for primary and secondary portab le PCs.

1.0 1.0 1.0 1.1 1.2

0.7

0 1 2

Any Day Week-day Week-end Per Session Usage [hours] Pre-Evening Evening

1.5 1.5 1.6

1.1 1.2 1.0

0 1 2

Any Day Week-day Week-end # Sessions per Day Pre-Evening Evening

0.8 0.8
0.6 0.9 1.1

0.8

0 1 2

Any Day Week-day Week-end Per Session Usage [hours]

1.0 0.9 1.0

0.7 0.8
0.6

0 1 2

Any Day Week-day Week-end # Sessions per Day

0 1 2 3 4 5

Any Day Weekday Weekend Evening 1.5 1.7 1.0 Pre-Evening 1.9 1.9 1.8 Whole Day 3.4 3.6 2.8 h/day

0 1 2 3 4 5

Any Day Weekday Weekend Evening 1.1 1.4 0.2 Pre-Evening 1.3 1.3 1.1 Whole Day 2.4 2.7 1.3 h/dayFraunhofer USA Center for Sustainable Energy Systems 

### 39

3.5.1.2.2.3 Power Management 

### PC energy consumption can be reduced through power management. The user may do so manual routines of power management (e.g., by putting the PC to sleep at night), or by enabling automatic power management (PM) settings (e.g., auto

- hibernate to have the computer save its state and automatically turn off after a chosen period of inactivity). We discuss these two manual and automatic power management methods in the next section.

Manual Power Management We asked U.S. adult s how often th ey manually turned off their PC or put it to sleep. Our survey results indicated that users tend to manually turn off their portable PCs (60% of the time during the day and 65% at night), while leaving them on for 19% of the time during the day. Portable P Cs are manually put to sleep 21% of the time during the day. However, even if the PC is left on, automated PM can place the
PC in a low

- power mode. Relative to desktop PCs (see Section 3.4 ), users turn off a higher portion of portable PCs (e.g., 60% vs. 4 0%) during the daytime.

Daytime Night

* Responses estimated based on ratio between Left On and Sleep for daytime. Figure 3

- 16 : Portion of users manually setting portable PCs into various power modes for the daytime or night time

. 

### Automatic Power Management We infer automatic power management (PM) settings using the method described in . This indicates that most portable PCs have some level of PM enabled (94%), particularly with auto

- screen off (52%), which engages the long idle mode, followed by auto

- screen off (29%) where the PC enters short idle
mode. Relative to desktop PCs (see Section 3.4 ), portable PCs have a higher rate of PM enabling (63 vs. 38% with auto

- sleep or auto

- hibernate enabled).

Fi gure 3

- 17 : Percentage of portable PCs with various automatic PM modes enabled. 20% 18% 19% 20% 22% 21% 61% 60% 60%

0% 20% 40% 60% 80% 100%

Primary Secondary Any Portable % of Users with Manual Power Management

Off
Sleep

Left On

16% 18% 17% 16% 22% 18% 69% 60% 65%

0% 20% 40% 60% 80% 100%

Primary Secondary Any Portable Off
Sleep*

Left On*

13% 13% 13% 48% 55% 52% 33% 27% 29% 6% 6% 6%

0% 20% 40% 60% 80% 100%

Primary Secondary Any Portable % Desktop PCs in Power Management Mode

PM Disabled

Auto-Screen Off
Auto-Sleep

Auto-HibernateFraunhofer USA Center for Sustainable Energy Systems 

### 40

3.5.1.2.2.4 Time in Operational Modes 

### A portable PC enters different power modes depending on whether or not the user is currently using it, how recently it was last used, how the user manually manages its power, and its automatic PM settings.
As with desktop PCs, we compute the time each PC spends in different power modes using the energy model presented in Appendix B.1. However, we use shorte r default time thresholds for lower power modes to be triggered, i.e., 10 vs. 15min for short idle and 25 vs. 30min for long idle (values empirically determined from the ENERGY STAR qualified product list (EPA 2013c); see Appendix section B.1.2 for more details). Furthermore, because we do not have reliable data differentiating the usage time of netbooks and notebooks, we assume that notebooks and netbooks spend equal portions of time in different power modes.

To estimate the time portable PCs spend charging or unplugged, we draw on the DOE (2012) EPS and battery charger rulemaking analysis (see Table 3

- 21 ). Specifically, we re

- scale our time estimates from the CE Usage Survey by applying ratios for the times charging to not charging, and unplugged to plugged.

Table 3

- 21 : Time usage estimates of portable PC EPSs from DOE (2012). Weighted average by shipment distribution of the reference case.

Type Time of Day [%] in Operational Mode

Active * + Charging Active * Sleep Off + Charging Off Un plugged † EPS Unp lugged

Notebook 2.5% 17% 13% 3.1% 48% 0.0% 16% Netbook 3.4% 14% 3.6% 0.0% 54% 0.0% 25%
* The portable PC is plugged in to the charger in t his mode. We consider the EPS active mode to correspond t o the weighted average of the portable PC active, short idle, and long idle modes. † Note that the reference case assumes no time spent with the portable PC unplugged from the EPS.



### Figure 3

- 18 shows the average amount of time each portable PC spent in different operational modes. Portable PCs spend a large majority of time in sleep and off modes (77%) mainly due to manual PM or automatic powering down after each session of use. Table 3

- 22 shows our results for the portion of time spent in Active + Idle modes; they broadly agree with other studies on residential PC use.

Compared to desktop PCs, portable PCs spend more time in lower power modes (19 v s . 16 hours i n sleep , off, or EPS unplugged modes ) , less time in short and long idle modes (2.0 vs. 4.2 hours), and less time in active mode (2. 9 vs. 3.4 hours). This is due to portable PCs, being manually put into low power modes more frequently, having m ore aggressive automated PM settings, and lower power modes triggering after shorter time thresholds. Portable PCs also spend 2.0 hours charging (in both Active and Off modes), but are unplugged from the EPS for 3.3 hours a day on average.Fraunhofer USA Center for Sustainable Energy Systems 

### 41 ‡ Our mode l defines night as when the household has gone to sleep, so we assume no active usage. * Note that usage time for charging is already counted in usage times for active and off modes, so that does not count towards the total time plugged in. Charging (Active): time spent charging while in active mode. Charging (Off): time spent charging while in off mode. Figure 3

- 18 : Average time spent in various operational modes in one day ( l eft) and in one year ( r ig ht) for portable PCs.

Table 3

- 22 : Comparison of percentage of time notebook PCs spent in various operational modes with other data sources.

Time [%] in Operational Mode
Year Setting Source Active * Short I dle Long Idle Active + Idle † Sleep Off **

14% 2.6% 6.9% 23% 29% 48% 2013 R esidential CE Usage Survey

- 16%

- 16% 42% 42% 2012 R esidential LBNL 2013 ‡

18%

- 15% 33% 25% 42% 2010 R esidential Fraunhofer 2011

- 35% 15% 50% 5% 45% 2013 Office ENERGY STAR v 6.0 (EPA 2013a) §

- - 40% 40% 5% 55% 2009 Office ENERGY STAR v5.2 (EPA 2009) §

41%

- - 41% 48% 20% 2008 Office Microsoft 2008
* Includes active + charging time. ** Includes charging (off) and unplugged, but excludes EPS unplugged time.
† Combined activ e and idle. ‡ Field measurement with a small sample size of 11 portable PCs. § ENERGY STAR Typical Energy Consumption values are based on studies of computer usage in office buildings (ECMA 2010, Microsof t 2009).



### 3.5.1.3 Unit Energy Consumption and Annual Ener gy Consumption We compute the energy consumption by multiplying the time a PC spends in each power mode by the average power draw in that mode. Figure 3

- 19 shows the energy consumption for each day period due
to the time in variou s operational modes. Active usage accounts for a considerable amount of energy consumption (57%), followed by long idle (15%), then short idle (8.2%). Lower power modes account for 6.6% and 5.5% of UEC, for sleep and off modes, respectively. Charging accou nts for 7.7% of UEC.

Netbook PCs have considerably lower power draw values than notebook PCs for the active, short idle, and long idle modes (19 vs. 30W, 15 vs. 23W, 10 vs. 15W, respectively) , resulting in a 33% lower UEC for
netbooks. 0

4 8 12 16 20 24

Whole Day PreEvening Evening Night‡

Charging(Active)* 1.5 0.7 0.4 0.3 Charging (Off)* 0.5 0.2 0.1 0.2
Off 9.9 3.7 2.1 4.1 Sleep 6.0 2.7 1.5 1.9 LongIdle 1.4 0.6 0.3 0.5

ShortIdle 0.5 0.3 0.2 0.1

Active 2.9 1.6 1.3 0.0 Total Plugged In 21 8.8 5.3 6.5 h/day

0 2,000 4,000 6,000 8,000

All Days Weekdays Weekends Charging(Active)* 538 402 133 Charging (Off)* 184 126 58
Off 3,417 2,347 1,082 Sleep 2,202 1,561 645 LongIdle 452 385 58

ShortIdle 168 123 45

Active 900 702 189 Total Plugged In 7,861 5,647 2,210 h/yrFraunhofer USA Center for Sustainable Energy Systems 

### 42 ‡ Our model defines night as when the household has gone to sleep, so we assume no active usage then. * Only accounting for energy sole due to charging while in active and off modes. Figure 3

- 19 : Total energy consumed in various operational modes in one day and in one year for portable PCs . W eighted average across primary and secondary notebook and netbook portable PCs. 

### Our calculations yield a UEC of 53 kWh/year for a typical portable PC and an AEC of 4.9 TWh/year. Th is reflects a conservative estimate that the same proportion of netbooks of all portable PCs is plugged in and used as the proportion owned. However, declining netbook sales ( CEA 2013b ) suggest a decrease in
their use. If we assumed that the installed base of portable PCs consisted entirely of notebooks, i.e., included no netbooks, this would yield an AEC of 5.1 TWh/year. Furthermore, w hile the installed base for portable PCs exceeds that of desktop PCs (93 vs. 88 million), their AEC is lower ( 4

. 9 vs. 1 6 TW h/year),
because they have a 72% lower UEC (5 3 vs. 1 86 kWh/year).

Table 3

- 23 : U nit energy consumption (UEC), installed base, and annual energy consumption (AEC) of portable PCs.

Type UEC [kWh/yr] Installed Ba se [millions] AEC

[TWh/yr] Charging Active Short Idle Long Idle Sleep Off Total Notebook 4.3 31 4.5 8.1 3.6 3.0 55 78 4.3 Netbook 2.9 20 2.9 5.2 2.7 2.5 37 15 0.6 Total /Wt.Avg. 4.1 30 4.4 7.8 3.5 2.9 53 93 4.9



### 3.5.2 Comparison with Prior Energy Consumpti on Estimates We found a decrease in the both portable PC UEC and AEC from 2010. A major reason is the drop in plugged

- in installed base (132 to 93 million) driven by a sharp decrease in the market share of portable PCs in the overall market for desktop PCs , portable PCs, and tablet computers (from 57% in 2010 to about 21% in 2013, CEA 2013b). To a large extent, this reflects around a ten

- fold increase in the household ownership penetration of tablets, from 4% (Fraunhofer 2011) to 39% (CEA 2013a). This same trend could also explain the decrease in active use time that we found.

We refined our computer usage survey from 2010, and believe that it increases the accuracy of our estimates for time in operational modes for portable PCs. See Section 3.5.2 for a discussion on various refinements. In addition, for portable PCs our model explicitly calculates the power draw, time in modes, and energy consumption due to the external power supply (charging, unplugged, etc.).

0 25 50 75 100 125 150

Whole Day PreEvening Evening Night‡

Charging* 11.2 5.1 3.1 3.0
Off 7.9 3.0 1.7 3.3 Sleep 9.6 4.3 2.3 3.0 Long Idle 21 9.2 4.8 7
Short Idle 12 5.6 4.0 2.4

Active 83 46 37 0.0

ALL 145 73 53 19 Wh/day



### 0 15 30 45 60

All Days Weekdays Weekends Charging* 4.1 3.0 1.1
Off 2.9 2.0 0.9 Sleep 3.5 2.5 1.0 Long Idle 7.8 6.7 1.0

Short Idle 4.4 3.2 1.2

Active 30 24 6.4

ALL 53 41 12 kWh/yrFraunhofer USA Center for Sustainable Energy Systems 

### 43

Table 3

- 24 : Current and prior energy consumption estimates for portable PCs.

Year Units [millions] Power Draw [W] Time in Mode [hr/yr] PM *
Enabled UEC

[kWh/yr] AEC

[TWh/yr] Source Active Sleep Off Active + Idle Sleep Off
2013 93 29 a 1.6 0.8 b 1,770 ‡ 2,190 3,602 § 64% 53 4.9 Current
2010 128 19 2 1 2,915 2,210 3,635 69% 63 8.3 Fraunhofer 2011 2009 76

- - - - - - - 43 3.1 CCAP 2009 ††

2006 39 25 2 2 2,368 935 5,457 40% 72 2.8 TIAX 2007 2005 36 25 2 2 2,368 935 5,457 40% 72 2.6 TIAX 2006 2001 16.6

- - - - - - - 77 1.3 RECS 2001 2001 17.3 15 3 0 ‡‡ 1,007 651 7,102

- - - LBNL 2004 1999 16 15 3 2 521 261 7,978 100% 9 0.14 LBNL 2001
* Percent of computers with power management enabled (auto

- sleep or auto

- hibernate, not inc luding auto

- screen off). † Weighed average of power draw for active, short idle, and long idle modes. § Estimate for time in off mode excludes time unplugged from EPS. ‡ Combined time in active, short idle, and long idle modes.
†† Data for office equip ment only. ‡‡ Disconnected.

a 30 W weighted average if charging included. b 1.1 W weighted average if charging included

.


### 3.5.3 References
ATUS. 2012. “ American Time Use Survey

— 2012 Microdata Files .” Jun. 20, 2013. United States Department of Labor. http://www.bls.gov/tus/datafiles_2012.htm . Retrieved Oct. 30, 2013.

CEA

. 2010

. “12 th 

### Annual hou sehold CE Ownership and Market P otential.” CEA Market Research Report

. Consumer Electronics Association

. May , 201 0. Consumer Electronics Association.

CEA . 2013a. “1 5 th 

### Annual CE Ownership and Market P otential Study .” CEA Market Research Report

, April, 2013. Consumer Electronics Association

. CEA . 2013b. “ U.S. Consumer Electronics Sales & Forecasts 2009

- 2014. ” CEA Mark et Research Report

, July, 2013. Consumer Electronics Association

. Digitimes. 2012. Chen, M. and J. Tsai. “Intel may need to adjust roadmap for PC

- use Atom Processors.” Sept. 3, 2012. http://w ww.digitimes.com/news/a20120903PD208.html

. Retrieved Feb. 6 , 2014.

DOE. 2012. “ Rulemaking for Battery Chargers and External Power Supplies Energy Conservation Standard

. Energy Use Analysis Spreadsheet .” Feb. 17, 2012. http://www.regulations.gov/#!documentDetail;D=EERE

- 2008

- BT

- STD

- 0005

- 0084 . Retrieved Feb. 6, 2014.

EPA. 2012. “ ENERGY STAR Unit Shipment and Market Penetration Report 2012 .” December, 2012. http://www.energystar.gov/ia/partners/downloads/unit_shipment_data/2012_USD_Summary_Repo rt.pdf . Retrieved Sept. 16, 2013.

EPA. 20 13a. “ENERGY STAR Pr ogram Computer Specification Version 6.0.” Sept. 12, 2013. http://www.energystar.gov/products/specs/computer_specification_version_6_0_pd . Retrieved Dec. 12, 2013.

EPA . 2013b. “ ENERGY STAR Computers Draft 2 Version 6.0 Dataset .” May 15, 2012. https://www.energystar.gov/products/specs/system/files/Computers_Draft_2 _Dataset_masked.xlsx

. Retrieved Sept. 16, 2013.

FhCSE. Urban, Bryan, K urt Roth, and Verena Tiefenbeck. 2011. “Energy C onsumption of C onsumer E lectronics in U.S. H omes in 2010.” Final Report to the Consumer Electronics Association.Fraunhofer USA Center for Sustainable Energy Systems 

### 44



### http://www.ce.org/CorporateSite/media/Government

- Media/Green/Energy

- Consumption

- of

- CE

- in

U

- S

- Homes

- in

- 2010.pdf . Dec.

LBNL. 2013. Greenblatt, J. B. 2013. “ Field data collection of miscellaneous electrical loads in North ern California: Initial results

. ” Lawrence Berkeley National Laboratory. LBNL Paper LBNL

- 6115E. Jul. 22, 2013. http://escholarship.org/ uc/item/5cq425kt . Retrieved Sept. 16, 2013.
NRDC. 2013. “NRDC’s Response to CEC’s Invitation to Participate in the Development of Appliance Energy Efficiency Measures. NRDC Computers Attachment 2

. ENERGY STAR v6.0 Dataset v2 with additions from NRDC.” May 9, 2013. http://www.energy.ca.gov/appliances/2013rulemaking/documents/responses/Consumer_Electronic s_12

- AAER

2A/NRDC_Response_to_CEC_Invitation_to_Participate_with_Excel_Spreadsheets_REFERENCES/NRD C_Computers_2_ESTAR

- NRDC_v6.0_Dataset_v2.xlsx . Retrieved Dec. 12 , 2013.
Pew. 2012. “Adult gadget ownership over time.” Pew Internet surveys 2006

- 2013. April, 2012. http://www.pewinternet.org/Trend

- Data

- (Adults)/Device

- Ownership.aspx

. Retrieved 30 Oct. 2013.Fraunhofer USA Center for Sustainable Energy Systems 

### 45



## 3.6 Home Audio: Shelf/Compact Audio and Speaker Docks The home audio products evaluated in further detail include speaker docks and shelf stereo systems, also called Mini or Compact stereo systems. A speaker dock has a plug

- in connect ion for an MP3 player, smartphone, or tablet. An ordinary speaker dock includes two speakers rated at about 5 W each, a docking station, and sometimes a clock and a tuner ( see Figure 3

- 20 , left ). Some speaker dock models include more than two speakers and a subwoofer, and may draw about 100 W in active mode. 7



### A shelf stereo system consists of a central component with one or more media players (e.g., CD/DVD, radio tuner, and docking station for an MP3 player, smartp hone or tablet), two or more detached speakers, and sometimes a subwoofer ( see Figure 3

- 20 , right).

Figure 3

- 20 : Example of a speaker dock ( left ) , and shelf stereo system ( right ), s ource: iHome , Sony

.


### 3.6.1 Current Energy C o nsumption
3.6.1.1 Installed Base According to the CE Usage Survey data, 45% of house holds have a speaker dock and 46 % have a shelf stereo system. Multiplied by the average number of devices per househo ld, this yields installed bases of
98 and 6 4 million respectively (see Table 3

- 25 ). We were unable to find data on the installed base of speaker docks and shelf stereo systems by rated power draw levels.

Table 3

- 25 : Installed base of speaker docks and shelf stereo systems (CE Usage Survey)

.

Home Audio System Installed Base [millions] Household

Penetration Number of devices

per Household Source
Speaker d ock 98 45% 1. 8 CE Usage Survey Shelf stereo system 6 4 46 % 1.2 CE Usage Survey



### 3.6.1.2 Unit Energy Consumption
3.6.1.2.1 Power Draw 

### Speaker dock and shelf stereo systems can be characterized by the following three operating modes:

 Active

– Device is actively being used, playing music o r other audio content

 Active standby

– Device is neither playing audio content, nor turned off manually

7 Examples include the B&W Zepp elin Air (B&W Zeppelin Air

- Specifications 2013) and JBL OnBEAT Xtreme (JBL OnBEAT Xtreme Owner’s Manual 2011).Fraunhofer USA Center for Sustainable Energy Systems 

### 46



###  Standby

– Device is turned off manually but remains plugged in. Some devices have Auto

power down (APD) function and automatically enter a standby mode after a defined period of time (usually between 15 and 30 minutes).

Audio manufacturers use several terms to quantify the power of audio systems, such as peak power, total system output power, and continuous power. All of these usually quantify the maximu m or peak power output, and do not accurately characterize the average active power draw of an audio system, which is much lower than the values in audio system specifications. Many product specifications also include a “power consumption” value; the test procedure to determine these values is not stated. Based

on measurements 8 

### of three best

- selling 9 

### speaker docks, we found that the actual operating power draw (~5W) equals approximately half of the “power consumption” values provided in product specificatio ns. We did not measure speaker docks with high total output, as they were not sold in the store where we performed the measurements. Instead, we scaled the total output power to actual power by applying the same scaling factor (8) found for three shelf ste reo systems that we measured. This suggests that speaker docks with a total output power of 100 and 120W would draw approximately 13 and 15 W, respectively, in active mode.

Unfortunately, we could not find data for the portion of the installed base of spea ker docks with higher power draw. Nevertheless, we expect that the penetration of these speaker dock systems is likely very low. Notably, these speaker docks are not among “best selling” products listed o n leading CE retailers
such as A mazon.com and BestBu y.com. Second, these audio systems often cost much more than most speaker docks, typically between $300 and $600

. 10 

### For these reasons, we did not include these models in the final power draw calculations. Nonetheless, the large difference in power draws bet ween typical and high

- power speaker docks makes the average power draw of speaker docks somewhat sensitive to the penetration of high

- power devices. For example, if 5% of the speaker dock installed base drew 15W (total output system power 100

- 120W) in act ive mode, that would increase the UEC in active mode by about 7%. The market share of high

- power speaker docks and their actual power draw levels warrant further study.

After reviewing product documentation (e.g. owner’s manual, product specification, etc. ) for shelf
stereo systems 11 

### , we found that these products have total system power outputs from 40 to 700 W. To estimate the typical power draw of shelf stereo systems, we measured the power draw of three of the most popular mini

- shelf stereo systems with t otal output powers of 220, 500, and 700 W while playing a CD with the volume set at minimum, medium and maximum levels. We found that the average active

mode power draw of three mini

- shelf stereo systems with a total output power exceeding 200 W was
less t han 20 W for all systems except for one that exceeded that level at maximum volume (see Figure
3

- 21 ).

8 We measured the average power draw at min., middle, and max. volume while playing music and took the average.

9 Top 10 best

- selling models on A mazon.com and bestbuy.com.

10 The price for speaker docks we measure d varies between 60 and 80 US dollars

. 11 Based upon reviews of products from LG, Panasonic, Samsung, Sony, and Yamaha.Fraunhofer USA Center for Sustainable Energy Systems 

### 47

Figure 3

- 21 : Active power draws of different mini

- shelf ster eo systems (Fraunhofer measurements)

. 

### Our measurements of standby power draw for speaker docks averaged 1.3 W, while those for mini

- shelf stereo systems did not exceed 0.5W. We found different ways of putting stereo systems into standby mode. First of all, it can be achieved by using the “sleep” function which allows system to enter standby mode after defined period of time. This defined period of time usually vary from 10 to 90 minutes and set up by default to the maximum. Secondly, switching a stereo sys tem off manually will also allow it to enter the standby mode. Lastly, two of three systems we measured had auto

- power down, which puts the system into standby mode after a defined period of time 12



### . We did not find a correlation between total output power d raw and standby power draw.

Based on these data, we estimate the average power draw by mode values shown in Table 3

- 26

. The power draw values in both active

- and standby

- modes were calculated using a weighted aver age of pre

2010 (92%) and post

- 2010 systems (8%

, CEA 2013 ). The active power draw for pre

- 2010 systems comes
from Bensch et al. (2010 ) and the active power draw for post

- 2010 system were calculated based on our measurements 2013 as weighted average based o n the system’s popularity on the market. Since w e did not find active standby power draw measurements for post

- 2010 shelf stereo systems, we used the average of our power measurement s of post

- 2010 systems.

Table 3

- 26 : Power draw by mode for audio systems

Audio System Power [W] Sources Active Active Standby Standby Speaker dock 5 3 1.3 Fraunhofer m easurements Shelf stereo system 30 12 4.0 FhCSE 2011, Fraunhofer m easurements



### 3.6.1.2.2 Usage 

### We evaluated speaker doc k and shelf stereo system usage through the CE Usage Survey ( see Figure
3

- 22 , left ). 

### Based on all responses, we estimated that the average speaker dock spends 3.3 hours per day in active mode ( see Table 3

- 27 ). The data also indicate that 66% of U.S. adult s turn their speaker dock off with a power switch or remote control after they finish using it. Only 6% leave their speaker dock always on and 11% responded that their speaker dock does no t have a power switch 13



### .

12 Usually between 15 and 25 minutes.

13 We treat ed these responses as people who never turn off their speaker docks 0 20 40 60

System A 700 W System B

500 W System C

220 W System A

700 W System B

500 W System C

220 W

Active CD Active Tuner Max Min Mean WFraunhofer USA Center for Sustainable Energy Systems 

### 48

Figure 3

- 22 : Frequencies of responses regarding the active daily usage of speaker systems

.



### A review of product documentation revealed that some speaker dock systems have an auto p ower

shutdown (APD) feature that automatically places the system into standby mode after about 20 minutes of inactivity (e.g. Sony 2013a, Samsung 2013, Sony 2013b). The U.S. adult s’ replies indicate that nine percent of speaker docks have the APD feature a nd eight percent answered “don’t know”.

The CE Usage Survey found similar usage for mini

- shelf stereo systems (see Figure 3

- 22
, right), and the average time spent listening to music or other audio is 3.4 hours a day. Eighty

- six pe rcent of U.S. adult s answered that they turn their shelf stereo system off manually using a power switch or remote control. Only four percent of mini

- shelf stereo systems reported having APD. This is generally consistent with the portion of the installed b ase accounted for by post

- 2010 shelf stereo models (8%), which would be the units most likely to have APD functionality.

Table 3

- 27 : Annual usage by mode of speaker dock and shelf stereo systems

Home Audio Sy stem Usage [h/year]
Sources Active Active standby Standby Speaker dock 1,205 2,007 5,548 CE Usage Survey Shelf stereo system 1,241 949 6,570 CE Usage Survey



### The ENERGY STAR specification version 3.0 for Audio Products that came into effect in May, 2013 requires qualifying devices to have a default APD setting of two hours, maximum. Thus, the time spent in active standby mode by very new ENERGY STAR devices might be smaller. We do not, however, have data on the market penetration of ENERGY STAR speak er dock and shelf stereo systems for 2013.

3.6.1.2.3 Unit Energy Consumption 

### Our calculation for speaker dock system UEC yields 19 kWh/year, with no mode accounting for a majority of the UEC. The UEC of a mini

- shelf stereo system equals 75 kWh/year, with 51% and 34 % of UEC occurring in active and standby mode, respectively. See Table 3

- 28 and Figure 3

- 23 . Although the
newer mini

- shelf stereo systems draw less than 0.5 W in standby mode, a large inst alled base of pre

2010 unit (92% of units) results in an average 4 W power draw in standby mode. 0% 10% 20% 30% 40% 50%

0 1 2 3 4 5 6 7 8 9 10+

Hours in Active Mode per Day Speaker Dock

0% 10% 20% 30% 40% 50%

0 1 2 3 4 5 6 7 8 9 10+

Hours in Active Mode per Day Shelf StereoFraunhofer USA Center for Sustainable Energy Systems 

### 49

Table 3

- 28 : UEC calculation for speaker systems

. Speaker Dock Shelf Stereo
Power [W] Usage [hr/yr] UEC [k Wh/yr] Power

[W] Usage [hr/yr] UEC

[kWh/yr]
Active 5 1,205 6.0 30 1,241 38 Active Standby 3 2,007 6.0 12 949 11 Standby 1.3 5,548 7.2 4.0 6,570 26 Total

- 8,760 19.2

- 8,760 75

Figure 3

- 23 : Spe aker dock UEC distribution among different modes



### 3.6.1.3 Annual Energy Consumption Speaker dock and mini

- shelf stereo systems consumed approximately 2.0 and 5.0 TWh respectively, in 2013 ( Table 3

- 29 ).

Table 3

- 29 : AEC summary for speaker systems

.

Audio System UEC [kWh/yr] Installed Base

[millions] AEC

[TWh] Speaker dock 19 98 1.9 Shelf stereo system 75 6 4 4.8



### 3.6.2 Comparison w ith Prior Energy Consumption Estimates Our prior s tudy (FhCSE 2011) estimated that speaker docks consumed 1.2 TWh in 2010 (see Table 3

- 30 ). Thus, our current estimate for speaker dock AEC is more than 50 percent higher despite a decrease in

average active

- mode power draw. This lar gely reflects that the installed base has more than doubled since 2010. Although the active

- mode usage estimate has increased by about 50 percent, it is not clear how real this effect is, since the current usage estimates are more refined than those for 20 10

.
In contrast, the estimated AEC of mini

- shelf stereo systems has decreased 2 7 % since 2010. This primarily reflects about a 50 percent decrease in estimated active usage in 2013 relative to 2010. We believe that the 2013 usage estimates are more accurat e, as they are based on several hundred survey responses
and closer to survey

- based usage estimates for 2006. In contrast, the 2010 usage estimates comes from field monitoring of a small number (15) of systems.

31% 50%
31% 15%

37% 35%

0 20 40 60 80

Speaker Dock Shelf Stereo Off Standby

Active kWh/yearFraunhofer USA Center for Sustainable Energy Systems 

### 50

Table 3

- 30 : Prior energy consumption estimates for speaker docks

. Power [W] Usage [h/yr]

Year Units [millions] Active Active

S tandby Standby Active Active S tandby Standby UEC

[kWh/yr] AEC

[TWh/yr] Source

2013 98 5 3 1.3 1,205 2,007 5,548 19 1.9 Current
2010 48 10 3 NA 800 100 7,860 25 1.2 FhCSE 2011

Table 3

- 31 : Prior energy consumption estimates for mini

- shelf stereo system

. Power [W] Usage [h/yr]

Year Units [millions] Active Active

S tandby Standby Active Active S tandby Standby UEC

[kWh/yr] AEC

[TWh/yr] Source

2013 6 4 30 12 4.0 1,241 949 6,570 75 4.8 Current
2010 63 32 NA 4.3 2,482 NA 6,278 105 6.6 Bensch et al. 2010
2006 76 23 16 7.0 840 730 7,190 81 6.2 TIAX 2007



### 3.6.3 References Bensch, I., S. Pigg, K . Koski and R. Belshe. 2010 . “Electricity Savings Opportunities for Home Electronics and Other Plug

- In Devices in Minnesota Homes

– A technical and behavioral field assessment.” Final Report by the Energy Center of Wisconsin

. ECW R eport 257

- 1

. http://www.state.mn.us/mn/ externalDocs/Commerce/CARD_Plugging_into_Savings_Study_052710014507_MN_Home_Elect_Dev
ice s.pdf

. May.
Bowers & Wilkins. 2013. “Zeppelin Air

- Specifications.” http://www.bowers

- wilkins.com/Wireless

- Music

S ystems/Wireless

- Music

- Systems/Zeppelin

- Air/product

- details.html#productSpec

. CEA S&F. 2013. “U.S. Consumer Electronics Sales & Forecasts 20 09

- 2014.” CEA Market Research Report. Consumer Electronics Association. Jul.
EPA. 2013. ENERGY STAR program requirements Audio/Video. Version 3.0. Environmental Protection Agency. http://www.energystar.gov/ia/partners/prod_development/revisions/downloads/ audio_video/Final_Version_3_AV_Program_Requirements.pdf?5c24

- 7fe5 May.

FhCSE. Urban, Bryan, K urt Roth, and Verena Tiefenbeck. 2011. “Energy C onsumption of C onsumer E lectronics in U.S. H omes in 2010.” Final Report to the Consumer Electronics Association. http://www.ce.org/CorporateSite/media/Government

- Media/Green/Energy

- Consumption

- of

- CE

- in

U

- S

- Homes

- in

- 2010.pdf . Dec.

JBL. 2011. “OnBEAT Xtreme Owner’s Manual.” h ttp://www.jbl.com/images/media/ONBEATXT_OM_EN.pdf
Roth, K. and K. McKenney. 2007. “Energy Consumption by Consu m er Electronics (CE) in U.S. Residences.” Final Report by TIAX LLC to the Consumer Electronics Association. Dec.
Samsung 2013. Wireless Audio wi th Dock. User Manual for DA

- E570.
Sony. 2013a. Reference Guide for ICFCS515IP personal audio docking system. Ref. 4

- 286

- 722

- 15 (1)
Sony. 2013b. Reference Guide for RDPM15IP personal audio docking system. Ref. 4

- 274

- 302

- 22 (1)Fraunhofer USA Center for Sustainable Energy Systems 

### 51



## 3.7 Monitor s

3.7.1 Current Energy Cons umption The computer monitors category includes displays that must be plugged into a computer, such as
external or stand

- alone monitors. It excludes integrated displays, such as those built into laptop computers or all

- in

- one PCs, as well as multimedia pro jectors.

3.7.1.1 Installed Base
We es timate an installed base of 97 m illion monitors in 2013 (see Table 3

- 32 ) based on the CE Usage Survey (Appendix A). U.S. adults were asked how many monitors were plugged into the two mos t

- used desktop and portable computers, producing the distributions in Figure 3

- 24

. We estimate that 42% of all households had at least one monitor (68% of households with a computer).

Table 3

- 32 : Installed base of monitors

. Computers [millions] Monitors per

Computer Monitors

[millions] Desktop primary 53 0. 9 47 Desktop secondary 10 0. 8 8 Portable primary 53 0.2 1 3 Portable secondary 15 0.1 2 Other * 50 0.5 27 Total/Average 181 0. 5 9 7

* Refers to desktop and portable computers that are not primary an d secondary, i.e. tertiary, quaternary, etc.

Figure 3

- 24 : Installed base of m onitors and computers

.



### We found a 2 6 percent decline in the installed base of external monitors since 2010 (FhCSE 2011). Similarly, monitor sales decreased 24% from 2010 to 2013 (Display Search 2014). As shown in Figure
3

- 25 , 27% of desktop computers in 2013 had no external monitor , about 10% higher than in 2010. The portion of desktop and portable computers with at least one external monitor decreased by 13 % and 9 % (absolute), respectively, from 2010 to 2013. One reason for the decrease in the number of external
monitors associated with desktop PCs is the increase in the installed base of all

- in

- one PCs, i.e., those with integrated displays. Their cumulative sales 14 

### equaled about 18 million from 2007 to mid

- 2013 (FhCSE 2011, Display Search 2013, 2013 CE Usage Survey ), or about 21% of all plugged

- in desktop computers in 2013 15 

### relative to 14% of desktops circa 2010.

14 We did not find estimates for the fraction of all

- in

- one PCs sold to consumers; however, we assumed that AIO computers were mostly purchased for in

- home use.

15 We estimate an installed base of 88 Million des ktop computers plugged in 2013 (see Section 3.4 ).

88 93
78

20

0 20 40 60 80 100

Desktop PC Portable PC Millions Computers MonitorsFraunhofer USA Center for Sustainable Energy Systems 

### 52

Figure 3

- 25 : D istribution of monitors per desktop and portable computer

. 

### 3.7.1.2 Unit Energy Consumption
3.7.1.2.1 Power Draw 

### Monitors have three primary power modes: active, sleep, and off. Active mode occurs whenever the monitor is on and displays an image. Monitor active

- mode power draw depends most strongly on display technology, screen size, and default settings from manufacturer (e.g.

, brightness and contrast). In addition, display resolution can also affect active

- mode power draw. Sleep mode is a low

- power state entered after a period of inactivity, typically 15 minutes, when power management (PM) is enabled (see Appendix B.1.2 ). Us er input from a keyboard or mouse awakens a sleeping monitor to active mode. Off mode is the lowest plugged

- in power mode and is entered when the user powers down the monitor by manually switching it off or the comp uter’s power settings are set for auto turn off the display.

The CE Usage Survey ( see Appendix A ) shows that LCDs dominate the installed base of monitors, accounting for 83 percent of the installed base. 16 

### Thus, the portion of CRT monitors has not changed appreciably since 2010 ( Table 3

- 33 ). The average display size of the installed base has increased to 20.9
inches 17 

### in 2013 (NPD DisplaySearch 2012), compared to 18 inches in 2010 (FhCSE 2011) and 17 inches in 2006 (TIAX 2007). Figure 3

- 26 shows the estimated size distribution of the installed base of LCDs.

Figure 3

- 26 : Distribution of LCD monitors installed base in 2013 by d iagonal screen size (FhCSE 2011 , DisplaySearch 2014)

. 

### We also found about a seven

- fold increase in the installed base portion of LCD monitors with LED backlights, from 10% in 2010 (Kim & Semenza 2012) to 2013 69% (IDC 2013; This change also influences

16 Since monitor responses were given only for up to two desktop and portable computers, we assumed the proportions of LCD and CRTs were the same for less

- used computers

. In the limiting case , i.e., if all monitors for computers three and beyond were CRTs, the split would shift to
60 % LCD and 40 % CRT

. For reference

, CEA (2014) estimate d there were 35 million CRT monitors in U.S. households in February 2014, including unit s not plugged in (e.g., in storage)

. 17 Projected screen size for 2013

.

27% 64%

8% 1% 1% 0% 20% 40% 60% 80% 100%

0 1 2 3 4+ Monitors per Computer Desktop PC 2010 2013 85%

13%
2% 0% 0% 0% 20% 40% 60% 80% 100%

0 1 2 3 4+

Monitors per Computer Portable PC 2010 2013

59%

18% 22%

2% 0.1% 0% 20% 40% 60% 80% 100%

15"-19" 20"-21" 22"-24" 25"-29" 30"-34" 2010 2013 LCD Monitors by screen size

Average Size: 20.9"Fraunhofer USA Center for Sustainable Energy Systems 

### 5 3



### the average active

- mode power draw ( see Figure 3

- 28 ). On average, an LCD monitor with LED backlight draws about 30% less power than one with a CCFL backlight, and this difference increases with diagonal size ( ENERGY STAR 2013, Fraunhofer measurements 2013, Dell 201 3, Cnet 2010a, Cnet 2010b). For this study, we assume that all monitors purchased before 2006 have been retired. Since monitors with LED backlights only began to have a significant market share in 2011, we divide the installed base into pre

- and post

- 2010 models. Adjusted 18 

### industry sales data (Display Search 2014) show that 27 million LCD displays were shipped to U.S. consumers between 2011 to mid

- 2013, and that 63% of these monitors have LED backlights (see Figur e 3

- 27 ).

Figur e 3

- 27 : Portion of monitor sales by backlight technology (DisplaySearch 2014)

.



### For all CRT monitors and 2006

- 2010 LCDs, we use d power draw characteristics from the previous CE study ( FhCSE 2011 ). For post

- 20 10 LCDs , we assumed that all LCD

- LED monitors met the ENERGY STAR specification and used the average power draw values for each size range from the ENERGY STAR Displays Product List (2013). For LCD

- CCFLs , we divided them among ENERGY STAR and non

- ENERGY
S TAR units. Since LCD

- LEDs account for 69% of the market and 83% of monitor products sold met

ENERGY STAR performance requirements in 2012 ( ENERGY STAR 2012), we estimate that approximately 55% (=17%/(14%+17%)) of post

- 2010 LCD

- CCFL m onitors did not meet EN ERGY STAR and 45% did. Then,
we used 2006

- 10 LCD

- CCFL power draw characteristics to model the power draw of the non

- ENERGY
STAR LCD

- CCFLs and data from the ENERGY STAR Displays Product List (2013) for the ENERGY STAR
units. For most ENERGY STAR LCD

- CCFL mo nitors, we used the average LCD

- CCFL power draw value from the database for each size bin. Since the list had no power measurements for 28

- and 29

- inch LCD

- CCFL monitors, we estimated the power draw in that size range using correlations between power draw and screen area ( see Figure 3

- 28 ).

Although the average screen size of installed monitors in homes increased, which tends to increase
active

- mode power draw, we estimate that post

- 2010 LCDs draw 22W 19 

### in active mode as compared to
33 W for 2006

- 2010

. This reflects improvements in display technology over that period, most notably from LED backlights. Average power draw in sleep and off modes also have decreased since 2010, as the
ENERGY STAR specification allows a 0. 5W maximum power draw for monitors in both modes (EPA 2013). Table 3

- 33 shows our power draw estimates by display type and screen size.

18 We scaled the total North American unit shipment data (commercial and consumer) by the U.S

. population fraction (90%)

– ba sed on 3 5 million people in Canada (Statistics Canada 20 13 ) and 3 17 million in the U.S

. ( U.S. Census Bureau 201 3 )

– and by the average consumer fraction (38% ; Display Search 2011

- 2013).

19 We estimated power draw for post

- 2010 mo nitors based on a 69% share of the installed base for monitors with LED backlight. 0% 20% 40% 60% 80% 100%

2010 2011 2012 2013 All-in-One Desktop PC Display Any Backlight

LCD Monitor with LED backlight

LCD Monitor with CCFL backlightFraunhofer USA Center for Sustainable Energy Systems 

### 54

Table 3

- 33 : Average power draw estimates for monitors

.

Year S creen

Size % of

installed base Units Power [W] [inches] [millions] Active Sleep Off
LCD 2010

- 2013 15

- 19 35 % 9.5 15 0.4 0.3

2010

- 2013 20

- 21 29 % 7.8 22 0.4 0.3 2010

- 2013 22

- 24 33 % 8.9 26 0.5 0.3 2010

- 2013 25

- 29 4 % 1.1 38 * 0. 7 * 0. 4 *

2010

- 2013 30

- 34 0.2 % 0.1 72 0.7 0.6 Subtotal/ Wt. Avg. 20.9 28 % 27.5 22 0.4 0.3
LCD 2006

- 2010 19.1 55 % 5 3 .5 33 0.9 0.6
LCD Wt. Avg. 20.9 83 % 8 1 30 0.8 0.5 CRT Wt. Avg. 17 17 % 16 61 2.0 1.0 Total/Avg.

- 17.7 100 % 9 7 34 0.9 0.6
* Values have higher un certainty th an other values in t able.

Figure 3

- 28 : Active

- mode p ower draw measurements for ENERGY STAR LCD monitors by backlight technology ( EPA 2013)

.



### 3.7.1.2.2 Usage 

### Although we did not ask about monitor usage in the curren t study we did adjust the usage estimates from our prior study according to the computer usage estimates developed from the 2013 CE Usage Survey (see discussion below). This showed a decrease in active usage of external monitors in 2013 (see
Table 3

- 34 ). The time an external monitor spends in sleep mode is very similar to the findings of an LBNL
field

- monitoring study 20 

### (LBNL 2013). Furthermore, the time in off mode in 2013 is similar to our 2010 study, mainly because we assumed that the same percentage of monitors are manually switched off in 2010 and 2013 (Desktop: 36%, Portable: 40%; FhCSE 2011).

20 LBNL (2013) measured 23 monitors using Watts Up? And Kill

- A

- Watt power meters for between three and ten (or more) weeks. It divided the time spent in each mode into High Power, Low Power and Off. Hou rs were assigned to Off mode if the power meter reported 0 W power draw. This assumption may create error s in dividing time between off and sleep modes, because most monitors draw more than 0W in off mode, in which case those hours were attributed to sleep mode. Because
active

- mode power draw dominates monitor energy consumption, this effect has a very small impact on monitor UEC.

P LED = 0.0342x 2 + 0.096x + 0.5

R2 = 0.50 P CCFL = 0.122x 2

- 1.57x + 1.5 R2 = 0.72

0 50 100 150

10 12 14 16 18 20 22 24 26 28 30 32 34

Screen Size [inches] LED backlight CCFL backlight
WFraunhofer USA Center for Sustainable Energy Systems 

### 55

Table 3

- 34 : Daily usage of monitors by mode

.

Year Monitor Usage [h/day] Source

Active Sleep O ff
2013 4.2 12.2 7.7 Current study
2013 6.6 12.4 5 LBNL 2013 2010 6.9 9.7 7.4 FhCSE 2011



### The main reason for decrease in the active usage of monitors in 2013 is that we changed some aspects of the monitor usage model. In the current model, active

- mod e usage equals the sum of computer active usage and computer time in short idle mode, with the time to auto

- screen off assumed to be 15 minutes in 2013 and 20 minutes in 2010. After these 15 minutes the computer monitor turns off automatically even if the computer remains on. This yields active

- mode usage estimates of 4.7 hours/day for desktop computers and 3.5 for portable computers (see Computer Section s 3.4.1.2.2 and
3.5.1.2.2 ). To estimate monitor usage for the remaining hours (Desktop: 19.3 h/day; Portable: 20.5 h/day), we first identified the portion of monitors that are always on. This was calcula t e d based on the following assumptions , including the c omputer auto

- power management ( A PM) state ( Figure 3

- 29 ):

 If a computer has APM enabled, i.e., if a computer is sleeping, hibernating, turned off automatically, or has auto

- screen off, then the monitor enters either a sleep or off mode.

 If a computer has APM disabled but was m anually put into sleep mode or was manually switched off, then the monitor is either in sleep or off mode.

 If a computer has APM disabled and was not manually put into sleep mode or manually switched off, then the monitor remains on the whole day.

Figure 3

- 29 : Decision diagram for determining monitor operational mode.



### Following this methodology, we found a much lower portion of monitors left on for 24 hours a day in 2010 than 2013, i.e., 3.2%and 1.8% of tho se associated with desktops and portable computers, respectively, as compared to 15% and 10% in 2010. The amount of monitors that were 24 hours on is much higher in 2010 compared to 2013 because the 2010 methodology assumed that if a computer
does not have APM enabled and the monitor was not turned off manually then the monitor is alwaysFraunhofer USA Center for Sustainable Energy Systems 

### 56



### on. Based on monitor power

- draw measurements in 2013, we changed this so that a monitor associated with a computer in sleep or switched off manually is either in sleep or o ff mode.

3.7.1.3 Unit and Annual Energy Consumption Monitor AEC equals 5.7 TWh in 2013, with most of the energy consumption occurring in active mode (about 5. 2 TWh). Sleep and off modes account for a very small portion of AEC (0.4 TWh and 0.1 TWh, respectively). Table 3

- 35 shows UEC and AEC breakdowns by display technology and screen size. LCD monitors with CCFL backlight technology account for a majority of monitor AEC.

Table 3

- 35 : UEC and AEC estimates for monitors.

Year Screen Size

[inches] Units UEC [kWh/yr] AEC

[millions] Active Sleep Off Total [TWh/yr]
LCD 2010

- 2013 15

- 19 9.5 23 1.6 0.7 25 0.2

2010

- 2013 20

- 21 7.8 34 1.8 0.8 36 0.3 2010

- 2013 22

- 24 8.9 40 2.2 0.8 43 0.4 2010

- 2 013 25

- 29 1.1 58 3.0 1.2 62 0.1 2010

- 2013 30

- 34 0.1 110 3.1 1.7 115 <0.05 Subtotal/Wt. Avg. 20.9 27.5 33 1.9 0.8 36 1.0
LCD 2006

- 2010 19.1 5 3 .5 51 4.0 1.7 56 3.0
LCD Wt. Avg. 19.7 8 1 46 3 1 51 4.0 CRT Wt. Avg. 17 16 94 8.9 2.8 105 1.7 Total/Avg.

- 19.3 9 7 53 4 2 58 5. 7



### 3.7.2 Comparison with Prior Energy Consumption Estimates
Table 3

- 36 s ummarizes prior estimates for residential monitor energy consumption. Our estimated UEC (58 kWh/yr) is lower than both FhCSE (2011) and LBNL ( 2013). Unfortunately, we do not know the screen size and technology of monitors metered by LBNL (2013), and therefore cannot readily evaluate
the difference in UEC.

Table 3

- 36 : Prior energy consumption estima tes for monitors

.

Year Units

[millions] Power [W] Usage [h/yr] UEC AEC Source

Active Sleep Off Active Sleep Off [kWh/yr] [TWh/yr]
2013 9 7 33 0.9 0.6 1,533 4,453 2,774 58 5. 7 Current
2013

- 26 1.0 0.0 2,409 4,526 1,825 67

- LBNL 2013 2010 131 39 1.2 0.9 2,519 3,541 2,701 97 12.7 FhCSE 2011
2010

- 43 1.2

- 1,935 6,825

- 84

- Bensch et al. 2010
2008

- CRT

- 71 46 3

- - - - - ECOS 2011 2008

- LCD

- 34 6 0.9

- - - - - ECOS 2011 2006 90 42 1 1 1,865 875 6,020 85 7.6 TIAX 2007 2005 89 45 2 1 1,860 880 6,02 0 101 9 TIAX 2006



### Overall , our AEC estimate in 2013 is 54 % lower than in 2010 (FhCSE 2011). Decreases in the installed
base accounts for the largest portion of this change (51%), followed by decrease in active

- mode usage (34%), and improvements in the te chnology (15%). As discussed in the installed base subsection, the decrease in the installed base of desktop PCs and an increase in the installed base of all

- in

- one PCs are primarily responsible for the 27% decrease in the installed base of external monito rs. The decrease in
active

- mode usage reflects an updated model for both PC and monitor usage that we believe yields more accurate usage estimates (see above).Fraunhofer USA Center for Sustainable Energy Systems 

### 57



### 3.7.3 References
CEA. 2014. “ 2014 CRT Television and Monitors per U.S. Household ” . CEA Market Research Report. April.
Cnet. 2010a. ASUS VE276Q 27

- inch Review. Oct. http://reviews.cnet.com/lcd

- monitors/asus

ve276q/4507

- 3174_7

- 34139489.html
Cnet. 2010b. BenQ M2700HD 27

- inch Review. Sep. http://reviews.cnet.com/lcd

- monitors/benq

m2700hd/4507

- 3174_7

- 34069077.html Dell. 2013. Dell UltraSharp 30 PremierColor Monitor

– U3014. Technical specifications. http://accessories.us.dell.com/sna/productdetail.aspx?c=us&l=en&cs=04&sku=225

- 4429 DisplaySearch. 2014. “Quarterly Desktop Monitor Shipment and Forecast Report, 2011

- 13” Energie

- Atlas Bayern 2.0. Computer, TV & Co. http://www.energieatlas.bayern.de/buerger/konsum/computer.html

ENERGY STAR . 2013. Displays Product List. Jun.

ENERGY STAR . 2012. Unit Shipment and Market Penetration Report Calendar Year 2012 Summary

. http://www.energystar.gov/ia/partners/downloads/unit_shipment_data/2012_USD_Summary_Repo rt.pdf

ENERGY STAR . 2013. Displays Product List. http://downloads.energystar.gov/bi/qplist/displays_prod_list.xls . Jun. EPA. 2008. Displays Specification. Draft Final Dataset & Analysis. Environmental Protection Agency. Dec. http://www.energystar.gov/ia/partners/prod_development/revisions/downloads/monitors/Draft2_ Dataset_Analysis.xls

. EPA. 2013. ENERGY STAR program requirements for displays. Version 6.0. Environmental Protection Agency. Jan. http://www.energystar.gov/produ cts/specs/sites/products/files/ Final_Version_6%200_Displays_Program_Requirements.pdf
FhCSE. Urban, Bryan, K urt Roth, and Verena Tiefenbeck. 2011. “Energy C onsumption of C onsumer E lectronics in U.S. H omes in 2010.” Final Report to the Consumer Electronics Association. http://www.ce.org/CorporateSite/media/Government

- Media/Green/Energy

- Consumption

- of

- CE

- in

U

- S

- Homes

- in

- 2010.pdf . Dec

. IDC. 2013. IDC Lowers Forecast Growth for PC Monitors While Average Screen Size Increases. Jun. http://www.idc.com/getdoc.jsp?containerId=prUS24163113 LBNL. Greenblatt, J. 2013. “Fiel d data collection of miscellaneous electrical loads in Northern California: initial results.” Lawrence Berkeley National Laboratory Final Report, LBNL

- 6115E. Jul. NPD DisplaySearch. 2012. Quarterly Worldwide FPD Shipment and Forecast Report. h ttp://techcrunch. com/2012/10/16/study

- average

- display

- size

- climbing

- on

- all

- devices

- except

- for

- mobile

- pcs/ SID. Kim, J. and P. Semenza. 2012. How LEDs Have Changed the LCD Industry. Technical Paper. Apr. Statistics Canada. 2013. “Canada Population Estimat es.” http://www.statcan.gc.ca/start

- debut

- eng.html TIAX. Roth, K., R. Ponoum, and F. Goldstein. 2006. “U.S. Residential Information Technology Energy Consumption in 2005 and 2010.” Final Report by TIAX LLC to the U.S. Department of Energy, Building Technology Program. Mar. TIAX. Roth, K., K. McKenny. 2007. “Energy consumption by consumer electronics in U.S. Residences.” Final report to the Consumer Electronics Association (CEA). Jan.

U.S. Census Bureau. 2013. “U.S. Population.” http://www.census.gov/#Fraunhofer USA Center for Sustainable Energy Systems 

### 58



## 3.8 Network Equipment

3.8.1 Current Energy Consumption Residential network equipment can be classified in three categories: (1) broadband modems without integrated rout ers; (2) broadband modems with integrated routers called Integrated Access Devices (IADs) or Broadband Gateways ; and (3) routers and other devices . Devices from all categories may support wired connections, wireless connections (Wi

- Fi), or both.

Broadband modems and IADs are collectively known as broadband access devices, and subscribers use these to connect to a high

- speed Internet service provider (ISP). Our installed base estimates include cable, digital subscriber line (DSL) (including a symmetric digita l subscriber line (ADSL) and v ery

- high

- bit

rate digital subscriber line (VDSL)), fiber optic, and satellite modems in the broadband modem and IAD categories. Less common modems, including stationary WiMAX, 3G, 4G modems and wireless mobile hotspot devices, are included in the routers and other devices category.

Devices listed in the routers and other category are used to establish a local area network (LAN) for communication between household consumer electronics. Routers, the most common and feature

- rich devices, can manage data transfer between multiple computer networks and can provide security,

Internet connection sharing, and other advanced features. We did not include switches and hubs in the routers and other devices category in 2013 because of their very low initial estimated AEC of 0.01 TWh
for less than 1 million units.

3.8.1.1 Installed Base Broadband subscription penetration in 201 3 was 75 % according to the CE Sales and Forecasts (2013), an 8% increase from 2010 (FhCSE 2011). This estimate generally agre e s with the 70% from another survey

based estimate, PEW (2013). Growth in broadband penetration has slowed since 2010
, while in

- home network penetration has grown steadily (see Figure 3

- 30 ), i.e., from between 40 and 54 percent of
households in 2010 ( FhCSE 2011 ) to 62% in 2013. Internet access penetration has remained constant at 78% of households over the past three years (CEA 2013a).

Figure 3

- 30 : Portion of h ousehold s with broadb and Internet subscri ptions and home networks (CEA 2013b)

.



### Among the estimated 207 million network devices installed in 2013, 49 million were modem

- only, 64 IAD, and 94 routers and other (NRDC 2013, LBNL 2010, CEA 2013a; see Table 3

- 37 ). In the modem

58 61 69 70 74 75

30 34 40 48 54 62

0% 20% 40% 60% 80% 100%

2008 2009 2010 2011 2012 2013 broadband internet subscriptions network penetrationFraunhofer USA Center for Sustainable Energy Systems 

### 59



### category, the installed base of cable modems decreased by 49% from 2010, whereas the installed base of DSL modems increased by 11%. The installed base of fiber and satellite modem installed base
increased three

- fold and nine

- fold, resp ectively. We estimate that the installed base of cable IADs tripled from 2010 to 2013, while there are 13% fewer DSL IAD devices in 2013 than in 2010.

Of the network equipment studied in less detail, mobile wireless hotspots underwent the largest growth
in household penetration from 2011, reaching 21% in 2013. The installed base of wireless mobile hotspots together with 3G and 4G modems totaled 35 million devices in 2013 (CEA 2013a) .The installed base of wireless routers comes from NRDC (2013), a 15% increa se from 2010. Finally, we estimate that the installed base of WiMAX devices remains low (approximately 2% of households 21 

### ).

Table 3

- 37 : Installed base of network devices (LBNL 2010, CEA 2013a, NRDC 2013)

.

Ins talled Base [millions] Category 2010 2011 2012 2013 * [%] Modem

- only Cable modem 35 32 27 18 37% DSL modem 5.4 4 4 6 12% Fiber optic terminal (all) 5.4 7 10 16 33% Satellite modem 1.0

- - 9 18% Subtotal/Wt. Avg. 46

- - 49 100% IAD (Modem + Rou ter) Cable IAD 12 17 27 37 58% DSL IAD 31 35 37 27 42% Subtotal/Wt. Avg. 42

- - 64 100% Router and Other Wireless router 46 45 42 53 56% Wired

- only router/ other 1.7

- - 1.7 2% WiMAX 1

- - 2.4 3% Access point †

- - - 2 2% Wireless mobile h otspot ‡

- - - 35 37% Subtotal/Wt. Avg. 49 §

- - 94 100% Total/ Weighted Avg. 139

- - 207

-

* Adjusted based on projections from LBNL (2010) and internet subscriptions (CEA 2013a).
† Hardy et al. ( 2013) defines an access point as “a device that provides I nstitute of Electrical and Electronics Engineers (IEEE) 802.11 (Wi

- Fi) connectivity to multiple clients as its primary function. An access point ...extends the range of a wireless signal but does not assign IP addresses to networked devices and therefore cannot be used to connect multiple edge devices in the absence of a wired or wireless router.” ‡ This category includes 3G and 4G CPE and wireless mobile hotspots devices. § Fraunhofer (2011) did not include wireless mobile hotspot devices in the install ed base; their penetration started to grow rapidly in 2011.


### The installed base estimates for network equipment in Table 3

- 37 show a higher penetration of network equipment for cable than for DSL or fiber

- optic. This agrees with the results from a recent CEA s urvey (CEA 2013a) shown in Figure 3

- 31 (left). Our estimates of installed base of routers indicate that 96% had wireless functionality. According to the CEA ownership survey (CEA 2013a), 51% of hou seholds had a
wireless connection at their homes in 2013.

21 Assuming that 2% of US households who answered “some other way” on the question “What type of Internet service do you have at home?” in CEA Ownership Survey (2013a) have WiMAX internet service.Fraunhofer USA Center for Sustainable Energy Systems 

### 60

Figure 3

- 31 : Type of Internet service at home (CEA 2013a)

.



### 3.8.1.2 Unit Energy Consumption
3.8.1.2.1 Power Draw 

### Our evaluation of the power draw of network equipment is based upon the ENERGY STAR dataset of measurements for 198 small network equipment devices (EPA 2013b) and measurements from laboratory testing and in

- home monitoring using the ENERGY STAR test procedures (NRDC 2013, Hardy et al. 2013). Together, these studies provided a larger measurements data set than we used in the 2010 study. Generally, the active power draw measurements for cable and DSL network equipment by NRDC (2013) and EPA (2013b) are higher than the FhCSE (2011) estimates for 2010. For fiber optic terminals (ONTs), we relied on EPA measurements of 19 ONTs that draw, on average, 6.7 W. To evaluate the active power draw of wired routers, we took the average power draw of 19 wired routers measured by ECCJ (2008). 22 

### Active power draws for wireless routers and access points we took as average power of measured devices by EPA (wireless routers: n=50, access point: n=13). We could not find new measurements for satellite modems, WiMAX network equipment and w ireless mobile hotspot devices in 2013; there fore we used the active power draw values from our previous study (FhCSE 2011) and values from manufacturers’ specifications (Motorola 2013, Greenpacket 2013, Fritzbox 2013, CMAX 2013).

Standby power draw estimates are based on values from the previous Fr aunhofer CSE study (FhCSE 2011) because neither NRDC nor EPA measured power draw in standby mode. We assumed that standby power draws have not changed appreciable since 2010. In practice, the standby mode has a small impact on network equipment UEC since t hese devices spend most of the time in on mode. Table

3

- 38 presents active mode and standby mode power draw values.

The first ENERGY STAR specification for small network equipment took effect in Sept. 2013. Thus, this may have sh aped the energy consumption characteristics of network equipment sold right before the point in time for this analysis (i.e., mid

- 2013) (EPA 2013a).

22 We were unable to find shipment data for wired routers between 2010. We expect, however, that the installed base of wired rou ters has not changed from 2010 due to growing wireless connections in US homes. Therefore, power draws estimates from ECCJ (2008) represent most of the installed base. Cable 43%

DSL 26% Fiber 14% Satellite 8% Dial

- up 7% Other 2%Fraunhofer USA Center for Sustainable Energy Systems 

### 61

Table 3

- 38 : Power draws for n etwork equipment (NRDC 2013, EPA 2013b)

Devices Overall Power [W] [millions] [ % ] Active Standby Modem

- only Cable modem 18 9% 6.7 0.1 DSL modem 6 3% 5.4 0.1 Fiber optic terminal (all) 16 8% 6.7 * 0.1 Satellite modem 9 4% 9.5 0.1 Subtotal/Wt. Avg. 49 24% 7.1 0.1 IAD (Mode m + Router) Cable IAD 37 18% 8.0 1.5 DSL IAD 27 13% 7.3 1.5 Subtotal/Wt. Avg. 64 31% 7.7 1.5 Router and Other Wireless router 53 26% 7.5 1.8 Wired

- only router / other 1.7 <1% 6.7 0.0 WiMAX 2.4 1% 12 † 0.0 ‡ Access point 2 1% 5.5 0.0 ‡
Wireles s mobile hotspot devices 35 17% 7.0 † 0.0 ‡

Subtotal/Wt. Avg. 94 45% 7.4 1.0 Total/ Weighted Average 207 100% 7.4 0.9
* The active power draw of a fiber optic terminal varies significantly and depends on the data transmitting by device. Some in

- home fib er network equipment also provides TV contents in addition to internet and phone service (NRDC 2013).
† These values have a high uncertainty. ‡ We were unable to find these data

.



### 3.8.1.2.2 Usage 

### Field monitoring studies indicate that b roadband Internet modems an d network devices are normally always on and ready to use, and most units automatically turn and remain on when plugged in . The

2010 CE Usage Survey found that 12% of U.S. adult s reported that their modems were switched off
when not in us e, 86% reported always on

, and 2% didn’t know . Thus, we estimate that an average modem is on 21.4 hours per day, or 7

, 826 hours per year and turned off the remaining hours (FhCSE 2011). We assume that the time spend in active mode has not changed significa ntly from 2010 and did not perform an updated usage survey for small network equipment. In the case of wireless mobile hotspot devices, this almost certainly overestimated their active

- mode usage.

3.8.1.3 Unit and Annual Energy Consumption
We estimate that network equipment consumed 12 TWh in 2013: 2.7 TWh from modems, 3.9 TWh from IADs, and 5.5 TWh from routers and other (see Table 3

- 39 ). In 2013, cable, satellite modems and fiber optic terminals consumed the largest portion of modem ener gy consumption. Among IAD devices, cable modems with integrated routers consumed more energy than DSL IADs due to a higher installed base. Wireless routers accounted for a majority (58%) of router and other energy consumption due to their high penetration, with increasingly common wireless mobile hotspot devices accounting for much of the remaining energy in this category (see Figure 3

- 32 ).Fraunhofer USA Center for Sustainable Energy Systems 

### 62

Table 3

- 39 : UEC and AEC calculations for n e twork equipment

.
Devices Overall UEC [kWh/yr] AEC [millions] [ % ] Active Standby Total [TWh/yr]
Modem

- only Cable modem 18 9% 52 0.1 53 0.9 DSL modem 6 3% 42 0.1 42 0.3 Fiber optic terminal (all) 16 8% 52 0.1 53 0.8 Satellite modem 9 4% 74 0.1 74 0.7 Subtotal/Wt. Avg. 49 24% 55 0.1 55 2.7 IAD (Modem + Router) Cable IAD 37 18% 63 1.4 64 2.4 DSL IAD 27 13% 57 1.4 59 1.6 Subtotal/Wt. Avg. 64 31% 60 1.4 62 3.9 Router and Other Wireless router 53 26% 59 1.7 60 3.2 Wired

- only rout er / other 1.7 <1% 52 0.0 52 0.1 WiMAX 2.4 1% 94 0.0 94 0.2 Access point 2 1% 43 0.0 43 0.1 Wireless mobile hotspot devices 35 17% 55 0.0 55 1.9 Subtotal/Wt. Avg. 94 45% 58 0.9 59 5.5 Total/ Weighted Average 209 100% 58 0.9 58 12

Figure 3

- 32 : AEC for small network equipment

.



### 3.8.2 Comparison with Prior Energy Consumption Estimates
Table 3

- 40 and Table 3

- 41 summarize p rior estimates for broadband modems and network device energy consumption. Our current estimates are higher than our previous study (FhCSE 2011), primarily due to significant growth in the installed base of fiber optic terminals, wireless routers and wireless mobile hotspot devices. 0 0.5 1 1.5 2 2.5 3 3.5 Cable modem
DSL modem Fiber modem (all)
Satellite modem
Cable IAD

DSL IAD
Wireless router Wired-only router / other

Hub or switch Access point Wireless mobile hotspot (LTE)

WiMAX Modem-only

IAD Router and Other

AEC [TWh]Fraunhofer USA Center for Sustainable Energy Systems 

### 63

Table 3

- 40 : Prior energy consumption estimates for broadband access devices (modems and IADs)

Units Power [W] Usage [h/yr] UEC AEC Year [millions] Active Standby Active Standby [kWh/yr] [TWh/yr] Source
2013 113 7.4 0.9 7,826 934 59 6.7 Current 2012 88 7.5

- 8,760 0 65 5.7 NRDC 2013 2010 88 6.1 0.8 7,826 934 48 4.3 FhCSE 2011
2010 87 6.0

- 8,760 0 53 4.6 LBNL 2010 2008 71 5.8

- 8,760 0 51 3.6 LBNL 2010 2006 46 6.0

- 8,760 0 53 2.4 TIAX 2007 2005 32 6.0

- 8,760 0 53 2.6 TIAX 2006

Table 3

- 41 : Prior energy consumption estimates for routers and other devices (non

- modem)

Units Power [W] Usage [h/yr] UEC AEC Year [millions] Active Standby Active Standby [kWh/yr] [TWh/ yr] Source
2013 57 7.4 1.0 7,826 934 57 3.4 * Current 2012 56 5.5

- 8,760 0 48 2.8 NRDC 2013 2010 49 5.4 1.7 7,826 934 44 2.1 FhCSE 2011
2010 50 5.5

- 8,760 0 48 2.4 LBNL 2010 2008 45 5.5

- 8,760 0 48 2.2 LBNL 2010 2005 15 6.0

- 8,760 0 53 0.8 TIAX 20 06 * AEC does not include wireless mobile hotspot devices and WiMAX modems, but does include hubs and switches (not shown in prior tables).

Figure 3

- 33 : U.S. broadband household subscribers by technolog y type (LBNL 2010, TIA 2013, CEA 2013a)

.


### 3.8.3 References
CEA. 2013a. “15 th 

### Annual CE Ownership and Market Potential Study.” CEA Market Research Report, April, 2013. Consumer Electronics Association.
CEA. 2013b. “U.S. Consumer Electronics Sales & Forecasts 2009

- 2014.” CEA Market Research Report, July, 2013. Consumer Electronics Association. Cisco. 2011.” IEEE 802.3az Energy Efficient Ethernet: Build Greener Networks.” White paper. http://www.cisco.com/en/US/prod/collateral/switches/ps5718/ps4324/white_paper_c11

- 676336.pdf CMAX. 2013. Technical specifications CMC

- 100Li. http://www.cmaxwireless. co.kr/pro0104.html?part=4 DisplaySearch. 2014. “Quarterly Desktop Monitor Shipment and Forecast Report, 2011

- 13” ECCJ. “Small Routers & L2 Switches.” Final report. The Energy Conservation Center Japan. Apr. 2008 https://www.eccj.or.jp/top_runner/pdf/tr_small_routers

- apr_2008.pdf

EPA. 2013 a . ENERGY STAR program requirements for Small Network Equipment. Version 1.0. Environmental Protection Agency. Nov. 0% 20% 40% 60% 80% 100%

2008 2009 2010 2011 2012 2013 2014 2015 2016 Satellite

WiMAX

FTTH

Cable

DSLFraunhofer USA Center for Sustainable Energy Systems 

### 64



### http://www.energystar.gov/products/specs/sites/products/files/SmallNetworkEquipment_V1_ENER GYSTAR_ProgramRequirements_Nov2013_0.pdf

EPA. 2013 b

. “SNE Version1.0 Draft 3 Dataset .”
FhCSE. Urban, Bryan, K urt Roth, and Verena Tiefenbeck. 2011. “Energy C onsumption of C onsumer E lectronics in U.S. H omes in 2010.” Final Report to the Consumer Electronics Association. http://www.ce.org/CorporateSite/media/Government

- Media/Green/Energy

- Consumption

- of

- CE

- in

U

- S

- Homes

- in

- 2010.pdf . Dec.
Fritzbox. 2013. Product description Fritz box 6810. http://www.4gltemall.com/fritz

- box

- 6810

- lte

cpe.html Greenpacket. 2013. Technical specifications EX 250. http://www.digicel4gbroadband.com/assets/uploads/WiMAX_CPE_Standard_Modem_____EX_250_ Technical_Spec.pdf Hardy, G., D. Denkenberger, J. Swofford, S. Foster Porter, A. Pawashe, K. Dayem, and D. Driscoll. 2 013. “Analysis of Standards Proposal for S ma ll Network E quipment”. Codes and Standards Enhancement (CASE) Initiative for PY 2013: Title 20 Standards Development. Ecova. Jul. http://www.energy.ca.gov/appliances/2013rulemaking/documents/proposals/12

- AAER

2A_Consumer_Electroni cs/California_IOUs_Response_to_the_Invitation_for_Standards_Proposals_f or_Small_Network_Equipment_2013

- 07

- 29_TN

- 71761.pdf LBNL. Lanzisera, S. and Nordman, B. 2010. EEDN Task 2.2.3: Network equipment scoping report. Lawrence Berkeley National Laboratory. Mar.

LBNL. Meier, A., Nordman, B., Busch, J., and Payne, C. 2008. “Low

- power mode energy consumption in California homes.” CEC

- 500

- 2008

- 035. Lawrence Berkeley National Laboratory. Sept. http://www.energy.ca.gov/2008publications/CEC

- 500

- 2008

- 035/CEC

- 500

- 2008

- 035.PDF

. Motorola. 2013. Datasheet for Motorola CPE i800. http://www.motorolasolutions.com/web/Business/Product%20Lines/Motowi4/CPEi_800/Images/Sta ticFiles/CPEi_800_DataSheet.pdf NRDC. 2013. “Small Network Equipment Energy Consumption in U.S. Homes.” NRDC Issue Paper. Jun. http://www.nrdc.org/energy/files/residential

- network

- IP.pdf Pew. Zickuhr,K., A. Smith. 2013. “Home Broadband 2013.” Aug. http://pewinternet.org/Reports/2013/Broadband/Findings.aspx Statistics Canada. 2013. “Canada Population Estimates.” http://www.statcan.gc.ca/start

- debut

- eng.html

U.S. Census Bu reau. 2013. “U.S. Population.” http://www.census.gov/#
TIA. 2013. “Market Review and Forecast.” Mar. TIAX. Roth, K., R. Ponoum, and F. Goldstein. 2006. “U.S. Residential Information Technology Energy Consumption in 20 05 and 2010.” Final Report by TIAX LLC to the U.S. Department of Energy, Building Technology Program. Mar. TIAX. Roth, K., K. McKenny. 2007. “Energy consumption by consumer electronics in U.S. Residences.” Final report to the Consumer Electronics Associati on (CEA). Jan.Fraunhofer USA Center for Sustainable Energy Systems 

### 65



## 3.9 Smart Phones

Smar tphones are mobile phones with I nternet connectivity. They include phones with operating systems running iOS, Android, Windows Mobile and BlackBerry.

3.9.1 Current Energy Consumption
3.9.1.1 Installed Base
We estimate an installed ba se of 166 million smartphones that have been used in the past month ( Nov. 2013). Some U.S. adult s indicated that their households owned smartphones, but that they personally did not use any. Given the nascence of smartphones, as a lower b ound, we assume that such households have one smartphones which is used by others. Our estimate from late 2013 is higher than
the estimate from early 2013 by CEA (2013a), due to the high sales volume of smartphones in 2013 (estimated 127 million by CEA 201 3b). Our installed base is consistent with other recent estimates (see
Table 3

- 42 ).

Table 3

- 42 : Installed base estimates for smartphones from different data sources.

Data Date Househo ld

penetration Households

[millions] Units / owner

household Installed Base

[millions] Source

Dec 2013 66% 79 2.1 166 * CE Usage Survey Feb 2013 58% 69 2.2 152 CEA 2013a Jun 2013

- - - 164 † Magid 2013
Jun 2013

- - - 151 ‡ Pew 2013b Q2 2013

- - - 142 § N ielsen 2013a
* Sum of our estimates for smartphones which U.S. adults personally used (152 million) and smartphones which are owned in their households, but not personally used by the U.S. adult , assuming one for each of those households (14 mil lion). † Lower bound estimate based on 61% of U.S. population (ages 8

- 65), 316.1 million U.S. population in 2013 (U.S. Census 2013), 85% of U.S. adults use the Internet (Pew 2013). ‡ Lower bound estimate based on 56% of U.S. adults. § Lower bound estim ate based on 53% of U.S. online users aged 13+.

Figure 3

- 34 : Distribution of households with smartphones used during the past month ( Nov

. 2013) vs. Ownership ( Feb

. 2013, CEA 2013)

. 

### Unlike for tablets, we as ked only about the (primary) smartphones most used by the U.S. adult , since they are personal devices; respondents are unlikely to know how other smartphones are used in the
household. 34% 47%

9.8%

4.0% 5.1%

0% 10% 20% 30% 40% 50%

0 1 2 3 ≥4 % of U.S. HouseholdsFraunhofer USA Center for Sustainable Energy Systems 

### 66

Table 3

- 43 : Plu gged

- In installed base estimates for smartphones from the CE Usage Survey.

Households [millions]

Smartphones Used per Owner Household
Device Not Owned 1 2 3 ≥ 4 Smartphones 40 42 12 4.8 6.1



### 3.9.1.2 Usage We estimate that smartphones are used for 4. 1 hours/day on average (Median=2.0 hours/day). Our median estimate is similar to other estimates of 2.6 hours for smartphones by DOE (2012) and the measured average of 2.6 hours/day for smartphones or tablets by Flurry Analytics (2013). However, our

estima te is higher than that of Experian (2013) of 58 minutes/day. Experian (2012) also found phone usage to vary with phone type, e.g., iPhones are used more than Android smartphones (1.25 vs. 0.82 hours/day).

3.9.1.3 Energy Consumption We use the same energy model to evaluate smart phone energy consumption as we did for tablets (see
Section 3.10.1.2 ). The model consider s energy consumption due to battery charging , including the impact of charger inefficiency and power draw when the smartpho ne is idle or unplugged from the charger but the charger remains plugged into the wall. Appendix B.2 presents additional details. We measured power draws by metering 5 smartphone units with Watts Up? .Net and Yokogawa WT210 power meters. Based on survey re sponses, we estimate that original chargers are used 82% of the time, and other chargers 18% of the time.

Table 3

- 44 : Representative battery capacity for smartphones, and power draw estimates for original and other chargers.

Charger Type Relative Usage Time Battery Capacity

[Wh] Charger Efficiency

[%] Power Draw [W]

Idle Unplugged Original 82% 6.5 76% 0.49 0.13 Others 18%

- 67% 0.55 0.19 Weighted Average

- 6.5 74% 0.50 0.14



### 3.9.1.3.1 Charging 

### We calculate th e energy consumption due to charging smartphones by multiplying the number of times the battery is charged in a day by the average increase in battery level (from pre

- charging to post

charging) for each charge session, and the additional energy consumed du e to charger inefficiency (see
Table 3

- 45 ). Our estimate of 0.92 charge cycles/day is similar to the estimate by DOE (2012) of 0.80 charges cycles/day and the assumption by OPower (2012) of one charge cycle/day.

Table 3

- 45 : Energy consumption estimates due to charging smartphones.

Device Battery Level Number Per Day Battery Capacity [Wh] Charger

Efficiency [%] Energy Consumption
Pre

Charge Post

Charge Charge

Sessions Charge

Cycles Full Charge [Wh] Per Day

[Wh/day] Smartphone 29% 95% 1.5 0.92 6.54 76% 8.8 7.7



### 3.9.1.3.2 Idle 

### We calculate the energy consumption in idle mode by multiplying the remaining time plugged in after charging to partial battery capacity in one day by the power draw while idle. As for tablets, for simplicityFraunhofer USA Center for Sustainable Energy Systems 

### 67



### we average the charging rates for <90% and ≥90% battery levels to estimate the average time for a full charge, and assume a linear relationship for the time to partial charging. Based on survey responses, we
estim ate that 64% of smartphones are charged only with the original charger and 11% are charged only with other chargers, and the remaining 25% of smartphones are charged with both the original and other chargers. DOE (2012) estimated higher time and power draw in idle mode, that yield a higher energy consumption estimate (3.6 vs. 2.5 Wh/day).

Table 3

- 46 : Energy consumption estimates due to smartphones being plugged into chargers after being fully charged (idle).

De vice Time [hr/day]
Power Draw Idle Mode [W] Energy

Consumption [Wh/day] Connected to Charger Charging Idle Original Charger Others All Chargers Full Charge [hr] Per Day

[hr/day] Smartphone 4.1 1.0 5.2 2.1 1.9 3.3 0.50 2.5 (DOE 2012)

- - 7.2

- 2.6 4.6 0.78 3.6



### 3.9.1.3.3 Unplugged 

### We estimate that on average smartphone chargers plugged into the wall socket for 15 hours/day, but 49% of users leave them plugged in all the time (24 hours/day). Averaged over all smartphones, including those that do not use another charger, “other” smartphone chargers are plugged into the wall
socket for 6 hours/day. The refore, for smartphones in the unplugged mode, the total energy consumption of their chargers is 3

. 6 Wh/day. DOE (2012) estimated that users leave their smar tphones plugged in for a shorter amount of time, and therefore have a higher unplugged time (6.6 vs. 11 hours/day). The DOE (2012) energy consumption is about half our estimate for the original charger (0.7 vs. 1.3 Wh/day).

Table 3

- 47 : Energy consumption estimate for smartphones in unplugged mode.

Charger Type Time [hr/day]
Power Draw [W] Energy

Consumption [Wh/day] Charger Plugged Into Wall Device

Unplugged Original Charger 15 11 0.13 1.3 Others * 6.0 4 .4 0.18 0.8 All Chargers

- - - 2.2 (DOE 2012) 14 6.6 0.11 0.7
* Since we did not ask about other chargers, we assume that if other chargers are used (>0 hours/day), then they are left plugged in the same amount of time as the original charger. Note th at mean estimates include responses indicating no use of other chargers (0 hours/day)

.



### 3.9.1.4 Unit and Annual Energy Consumption (UEC and AEC) Our calculations yield an average smartphone UEC of 4.5 kWh/year and an AEC of 0.75 TWh/year. Our
estimates show tha t non

- charging modes account for about one

- third of energy consumption (see Figure 3

- 35 ). Although the UEC of smartphones is 74% of that of tablets (see Section 3.10 ), smartphones have a 66% greater installed base, resulting in a somewhat (24%) higher AEC.Fraunhofer USA Center for Sustainable Energy Systems 

### 68

Figure 3

- 35 : Energy consumption of smartphones in different operational modes.

Table 3

- 48 : UEC and AEC values for smartphones.

Type Energy Consumption [Wh/day] UEC [kWh/year] Installed Base [millions] AEC

[TWh/yr] Charging Idle Unplugged Total iPhones 12 2.4 1.0 1.0 4.3 70 * 0.30 Android Samsung 13 3.7 0.8 0.4 4.9 22 * 0.11 All Smartphones 12 2.8 0.9 0.8 4.5 166 0.75
* Installe d base for various iPhone and Android Samsung smartphone models estimated by representative weights of selected most popular smartphones scaled to the total installed base of smartphones. Note that this does not sum to the estimate for total installed ba se, since there are other smartphone models.



### 3.9.2 Comparison with Prior Energy Consumption Estimates Our UEC estimates for smartphones are similar to those of other sources (see Table 3

- 49 ). Our estimates verify commonly held assumptio ns that smartphones are charged about once a day. OPower (2012) estimated slightly higher energy consumption for charging (indicating lower efficiencies compared to manufacturer specifications and product reviews, i.e., 57% for iPhone 5 and 65% for Samsung Galaxy S3). However, we account for additional modes that consume additional energy, specifically the idle and unplugged modes.

Table 3

- 49 : Current and prior energy consumption estimates for smartphones.

Yea r Units * [millions] UEC [kWh/yr] AEC [TWh/yr] Device Model Source Charging Idle Unplugged Total
2013 166 2.8 0.9 0.8 4.5 0.75 All smartphones Current
2013 26 2.4 1.3 1.1 4.8 0.12 iPhone 5 Current 2013 14 2.3 0.7 1.1 4.0 0.06 iPhone 4 Current 2013 13 3.4 0.8 0.4 4.5 0.06 Samsung Galaxy S3 Current
2012 2012 170 † 3.5 0 0 3.5 0.59 † iPhone 5 OPower 2012 OPower 2012

- 4.5 0 0 4.5

- Samsung Galaxy S3
2012 2012 - - - - 3.3

- iPhone 4 EPRI 2012 EPRI 2012

- - - - 2.2

- iPhone 3G
2012

- 5.3 ‡

- 0.3 5 .5

- Smartphones DOE 2012
* Installed base for select smartphones estimated by aggregated usage share and total installed base of smartphones. † Based on projected global sales in 2012. ‡ Combined UEC for charging and idle.



### 3.9.3 References
CEA

. 2010

. “12 th 

### Annual hou sehold CE Ownership and Market P otential.” CEA Market Research Report

. Consumer Electronics Association

. May , 2010. Consumer Electronics Association.
CEA. 2013a. “15 th 

### Annual CE Ownership and Market Potential Study.” CEA Market Research Report,
A pril, 2013. Consumer Electronics Association.

0 5 10 15

Any smartphone iPhones Android Samsung Unplugged 2.2 2.7 1.0

Idle 2.5 2.7 2.2 Charging 7.7 6 10

Total 12 12 13 Wh/dFraunhofer USA Center for Sustainable Energy Systems 

### 69



### CEA. 2013b. “U.S. Consumer Electronics Sales & Forecasts 2009

- 2014.” CEA Market Research Report, July, 2013. Consumer Electronics Association. CEA. 2013c. Steve Koenig. Private correspondence, Nov. 2013. Consum er Electronics Association.
CEA. 2014. “Consumer Outlook on Tablets

– Jan. 2014 Edition.” Jan. 2014.
DOE. 2012. “ Rulemaking for Battery Chargers and External Power Supplies Energy Conservation Standard

. Energy Use Analysis Spreadsheet .” Feb. 17, 2012. http://www.regulations.gov/#!documentDetail;D=EERE

- 2008

- BT

- STD

- 0005

- 0084 . Retrieved Feb. 6, 2014.
EPRI. 2012. “ iPad Electricity Consumption in Relation to Other Energ y Consuming Devices

- Executive Summary .” Jun. 21, 2013. http://www.epri.com/Our

Work/Documents/Energy%20Efficiency/iPadEnergyConsumeExecS ummary6

- 2012Final.pdf . Retrieved Sept. 20, 2013. Experian. 2013. Fetto, J. “ Americans spend 58 minutes a day on their smartphones ” May 28, 2013. http://www.experian.com/blogs/marketing

- forward/2013/05/28/americans

- spend

- 58

- minutes

- a

day

- on

- their

- smartphones/ . Retrieved Oct. 24, 2013. Flurry Analytics. 2013. Khalaf, S. “ Flurry Five

- Year Report: It’s an App World. The Web Just Liv es in It .” Apr. 3, 2013. http://blog.flurry.com/bid/95723/Flurry

- Five

- Year

- Report

- It

- s

- an

- App

- World

- The

- Web

Just

- Lives

- in

- It

. Retrieved Nov. 12, 2013. Magid

. 2013

. “ Tablets Find a Home in More U.S. Homes .” Jun. 9, 2013. http://www.magid.com/node/250 . Retrieved Sept. 20, 2013.
Nielsen. 2013. “ The Mobile User .” Feb. 25, 2013. http://www.nielseninsights.it/wp

content/uploads/2013/03/03.

- global_mobile_report_02_25.pdf

. Retrieved Aug. 6, 2013.
NPD. 2013. “ Internet Connected Devices Surpass Half a B illion in U.S. Homes, According to The NPD Group .” Mar. 18, 2013. https://www.npd.com/wps/po rtal/npd/us/news/press

- releases/internet

connected

- devices

- surpass

- half

- a

- billion

- in

- u

- s

- homes

- according

- to

- the

- npd

- group/ . Retrieved Jan. 24, 2014. OPower. 2012. Fischer, B. “ How much does it cost to charge an iPhone 5? ” Sept. 27, 2012. http://blog.opower.com/2012/09/how

- much

- does

- it

- cost

- to

- charge

- an

- iphone

- 5

- a

- thought

provokingly

- modest

- 0

- 41year

. Retrieved Oct. 17, 2013.

Pew. 2013b. Smith, A. “Smartphone Ownership 2013.” Jun. 5, 2013. http://pewinternet.org/Reports/2013/Smartphone

- Ownership

- 2013/Findings.aspx

. Retrieved Oct. 17, 2013.Fraunhofer USA Center for Sustainable Energy Systems 

### 70



## 3.10 Tablet Computers Tablets include the iPad, Android tablets, and Windows 8 tablets, but exclude notebook or ultra

portable PCs with touch screens. While individually these devices do not consume much energy, collectively their energy consumption is notable due to a large and rapidly growing install base.

3.10.1 Current Energy Consumption
3.10.1.1 Installed Base We estimate an installed base of 100 million tablets that have been used in the past month . Some U.S.
adult s indicated that thei r households owned tablets, but that they personally did not use any. Given the relatively recent market entry of tablets, as a lower bound, we assume that such households have one tablet which is used by others. Our estimate from late 2013 exceeds that fr om early 2013 by CEA (2013a), due to the high sales volume of tablets in 2013 (estimated at 113 million by CEA 2013b). Our installed base agrees with other recent estimates (see Table 3

- 50 ).

Table 3

- 50 : Recent i nstalled base estimates for tablets

.

Data Date Household

penetration Households

[millions] Units / owner

household Installed Base

[millions] Source

Dec 2013 57% 67 1.47 100 * CE Usage Survey Feb 2013 39% 46 1.50 70 CEA 2013a Jul 2013

- 41 †

- - Parks Associates 2013
Jun 2013

- - - 118 †† Magid 2013
Jun 2013

- - - 91 § Pew 2013b Q1 2013

- 49

- - NPD 2013
2013 100 Representative
* Sum of our estimates for tablets that U.S. adult s personally used (73 million) and tab lets owned by their households but not personally used by the respondent, assuming one for each of those households (26 million).
† Lower bound estimate based on 48% of U.S. broadband households, 119 million U.S. households in 2011 (U.S. Census 2011), 72 % of U.S.
Internet household penetration in 2011 (U.S. Census 2011). †† Lower bound estimate based on 44% of U.S. online population (ages 8

- 65), 316.1 million U.S. population in 2013 (U.S. Census 2013), 85% of U.S. adults use the Internet (Pew 2013). ‡ Lower bound estimate based on 57% of U.S. online households indicating they own at least one tablet

. § Lower bound estimate based on 35% of U.S. adults indicating they own at least one tablet , 75.6% adults in U.S. population in 2012 (U.S. Census 2012), 313.9 million U.S. population in 2012 (U.S. Census 2012).

Figure 3

- 36 : Percentage of households with tablets used during the past month ( Nov

. 2013) vs. Ownership ( Feb

. 2013 ) ( CEA 2013 )

. 

### Similar to portable PCs, we asked about the most used (primary) tablet and second most used (secondary) tablets. 43% 47%

6.2% 1.8% 1.9% 0% 10% 20% 30% 40% 50%

0 1 2 3 ≥4 % of U.S. HouseholdsFraunhofer USA Center for Sustainable Energy Systems 

### 71

Table 3

- 51 : Plugged

- In installed base estimates for tablets from the CE Usage Survey.

Device Type # Used [million h ouseholds] Usage Base [million units]

1 * 2 3 ≥4 All Primary Second + Tablets 56 7.3 2.2 2.3 100 68 32
* We include estimates where the U.S. adult indicated using 0 tablets, but whose household owns >0 tablets. Primary: number of primary, i.e. , most

- used, tablets. Second+: number of tablets that are not primary, i.e., secondary, tertiary, etc.; treated as secondary in energy model.



### 3.10.1.2 Usage We asked respondents how long their tablets were used yesterday. We estimate that tablets are used
2.5 hours a day on average (Median=1.5 hours). Our mean estimate is similar to the measured average of 2.6 hours for smartphones or tablets by Flurry Analytics (2013).

3.10.1.3 Energy Consumption Mobile devices are typically used while running on their batteries. Using the energy usage model described in Appendix B.2, we calculate the energy consumption for their usage by estimating the energy consumed to charge their batteries. Their battery chargers (BC) also consume energy while plugged into the wall outlets. Therefore, w e consider the energy consumption due to charging and the charger in the following modes:

 Charging: When recharging the battery of the mobile device to its full capacity with an additional energy loss due to charging inefficiencies. DOE’s battery charger r ulemaking refers to
this mode as “active.”

 Idle: When the mobile device screen is off and the device is connected to its charger but not charging. The power draw in this mode is higher than the power draw on the battery when the mobile device is running on its battery and disconnected from the charger. DOE’s battery charger rulemaking refers to this mode as “maintenance.”

 Unplugged: When the mobile device is unplugged from its charger, but the charger remains plugged into the wall socket. If the user uses m ultiple chargers, then the energy consumption is due to all these chargers. DOE’s battery charger rulemaking refers to this mode as “no battery.”

 BC Unplugged: When the charger is unplugged from the wall socket. The power draw is 0W.

To get representative estimates for power draw, we identified the 8 most popular tablets models and measured their power draw of 7 units using Watts Up? .Net and Yokogawa WT210 power meters. Measurements were taken after five seconds of the device entering the relevant operati onal mode and when the power draw has stabilized. Representative battery capacities and charger efficiencies were aggregated from review articles and manufacturer specifications of the selected device models. See Appendix Table B

- 8 for more details.

We consider that users charge their mobile devices using the original (OEM) charger that came purchased with the product, and other chargers, such as after

- market chargers, charging via the USB ports of PCs and speaker docks, and car chargers. Based on survey responses, we estimate that original chargers are used 90% of the time, and other chargers 10% of the time.Fraunhofer USA Center for Sustainable Energy Systems 

### 72

Table 3

- 52 : Representative capacity and efficiency of origin al and aftermarket batteries and chargers for tablets.

Charger Type Relative

Usage Time Battery Capacity

[Wh] Charger Efficiency

[%] Power Draw [W]

Idle * Unplugged Original 90% 25.6 79% 0.36 0.08 Aftermarket 10%

- 68% 0.40 0.13 Weighted Average

- 25.6 78% 0.36 0.09
* Based on average measurements of several metered devices.



### 3.10.1.3.1 Charging 

### We calculate the energy consumption due to charging tablets by calculating the number of charge cycles per day, i.e., the number of full battery charges per day. Thi s equals the product of the number of charge sessions per day, i.e., the number times the battery is charged in a day, and the average increase in battery charge level (from pre

- charging to post

- charging) for each charge session plus the added

energy consu med due to charger losses (see Table 3

- 5 3 ). Our estimate of 0.44 charge cycles/day is higher than the estimate by DOE (2012) of 0.29 charges cycles/day, but similar to that of EPRI (2012) of 0.5 charge cycles/day (every other day)

.

Table 3

- 5 3 : Energy consumption estimates due to charging tablets.

Device Type Battery Level Number Per Day Battery Capacity [Wh] Charger

Efficiency [%] Energy Consumption
Pre

Charge Post

Charge Charge

Sess ions Charge

Cycles Full Charge [Wh] Per Day

[Wh/day] Primary 29% 95% 0.81 0.53 25.6 78% 33 16 Secondary * 0.49 0.32 11 Weighted Average 29% 95% 0.67 0.44 25.6 78% 33 14

* Energy consumption and amount of charging estimated by the relative (weight ed) usage between primary and secondary tablets (2.2 vs. 1.4 hours). For example, the number of charge sessions = 2.2h×0.81 + 1.4h×0.49 / (2.2h + 1.4h) = 0.67.



### 3.10.1.3.2 Idle 

### We calculate the energy consumption due to the tablet being idle while plugged into the c harger by multiplying the remaining time plugged in after charging to partial battery capacity in one day, and the power draw while idle. Tablet chargers do not charge at a constant rate for different battery levels; e.g., fast chargers charge faster at lo wer battery levels than higher levels. For simplicity we average the charging rates for <90% and ≥90% battery levels to estimate the average time to for a full charge, and assume a linear relationship for the time to partial charging.

We estimate that 84% of tablets are charged only with the original charger, 11% are charged only with other chargers, and the remaining 5% of tablets are charged with both the original and other chargers. Our energy consumption estimate is lower than the 2010 estimate by DOE (2012) (0.9 vs. 5.3 Wh/day) because of our lower estimate for the time in idle mode (3.9 vs. 6.1 hours) and lower power draw (0.36 vs. 0.87W).Fraunhofer USA Center for Sustainable Energy Systems 

### 73

Table 3

- 54 : Energy consumption estimates of tablets in idle mode.

Device Type Time [hr/day]

Power Draw [W] Energy

Consumption [Wh/day] Connected to Charger Charging

Idle Original Charger Others All Chargers 0 to 100% Full [hr] Per Day

[hr/day] Primary 5.3 0.8 6.0 4.2 2.0 3.9 0.36 1.1 Secondary * 3.2 0.5 3 .6 1.4 2.8 0.8 Wt. Avg. 4.4 0.6 5.0 4.2 1.8 3.4 0.36 0.9 (DOE 2012)

- - 7.5

- 1.4 6.1 0.87 5.3

* Energy consumption and amount of charging estimated by the relative usage between primary and secondary tablets (2.2 vs. 1.4 hours).



### 3.10.1.3.3 Unplugged 

### Tablets sti ll contribute to energy consumption even when unplugged from the wall socket, because their chargers may still be plugged in. We estimate that

, on average , original tablet chargers are plugged into the wall socket for 14 hours/day, but 49% of users leave t he charger plugged in all of the time (24 hours/day). Averaged over all tablets, including those that do not use another charger, “other” tablet chargers are plugged into the wall socket for 3 hours/day. The refore, for tablets in the unplugged mode,
the to tal energy consumption of their chargers is 0

. 9 Wh/day. Our estimates for time spent and the energy consumption for tablets in the unplugged mode are similar estimates by DOE (2012). Since we did not ask about secondary tablets, we assume that both primary and secondary tablet chargers are plugged into the wall socket for the same amount of time.

Table 3

- 55 : Energy consumption estimate for tablets in unplugged mode.

Charger Type Time [hr/day]
Power Draw [W] E nergy

Consumption [Wh/day] Charger Plugged Into Wall Device

Unplugged Original Charger 14 8.5 0.08 0.7 Others * 2.9 1.2 0.13 0.2 All Chargers 17 10

- 0.9 (DOE 2012) 16 8.5 0.13 1.1
* Since we did not ask about other chargers, we assume that if oth er chargers are used (>0 hours/day), then they are left plugged in the same amount of time as the original charger.



### 3.10.1.4 Unit and Annual Energy Consumption (UEC and AEC) Our calculations yield a UEC of 6.1 kWh/year for a typical tablet and an AEC of 0.61 TWh /year. Charging accounts for 86% of tablet UEC. Tablets with smaller screens (<8.9”) have a lower UEC, installed base, and AEC than tablets with larger screens (≥8.9”). Our estimates show that non

- charging operational modes account for a notable portion of energy consumption (13%). Compared to portable PCs (see
Section 3.5 ), we estimate that tablets have a UEC that is 8.8 times lower, a 11% higher installed base, and an AEC 8.2 times lower. If we assume that secondary tablets have the same usage and energy consumption as primary tablets, the UEC and AEC estimates would be 6.7 kWh/year and 0.67 TWh/year, respectively.Fraunhofer USA Center for Sustainable Energy Systems 

### 74

Figure 3

- 37 : Energy consumption of tablets in different operational modes.

Table 3

- 56 : UEC and AEC values for tablets.

Device Type Energy

Consumption [Wh/day] UEC [kWh/year] Installed
Base * [millions] AEC

[TWh/yr] Charging Idle Unplugged Total

Small screen 12 3.6 0.4 0.3 4.2 32 0.14 Large scree n 19 6.2 0.5 0.3 7.0 68 0.48 All Tablets 17 5.3 0.5 0.3 6.1 100 0.61
* Installed base for small and large screen tablets estimated by representative weights of selected most popular tablets scaled to the total installed base of tablets.



### 3.10.2 Comparison wi th Prior Energy Consumption Estimates Our UEC estimates for several specific tablet models are slightly lower than estimates from other sources. Referring to our UEC and AEC estimates for desktop and portable PCs (see Sections 3.4 and 3.5, respectively), w e discuss some comparisons with those for tablets. While the plugged

- in installed base of desktop and portable PCs have decreased since 2010 (by 13 and 39 million, respectively), the installed
base for tablets has increased about 30

- fold since 2010, i.e., from 4 million to 100 million. Thus, it appears that tablets are, to some extent, displacing some of the usage of desktop and portable PCs.

Applying our current UEC for desktop and portable PCs for our 2010 installed base estimates (Fraunhofer 2011), the A EC for desktop and portable PCs decreased by 2.5 and 1.9 TWh/year, respectively. On the other hand, applying our current UEC estimate for tablets, the AEC for tablets increased from 0.02 TWh/year to 0.6 TWh/year. This represents a net decrease in the total AEC of 3.7 TWh/year for all computing devices, excluding smartphones.

Table 3

- 57 : Current and prior energy consumption estimates for tablets.

Year Units

[millions] UEC

[kWh/yr] AEC

[TWh/yr] Device Model Sourc e

2013 100 6.1 0.6 All tablets Current
2012 67 † 11.9 0.6† iPad 3 EPRI 2012 2012

- 7.2

- iPad 2 EPRI 2012 2012

- 7.1

- iPad 1 EPRI 2012 2012

- 8

- iPad 2 NRDC 2012 2010 2.5

- - iPad 1 Forrester 2010
† Based on sale reports of all iPads since Q2 2010 with no device retirement.



### 3.10.3 References
CEA

. 2010

. “12 th 

### Annual hou sehold CE Ownership and Market P otential.” CEA Market Research Report

. Consumer Electronics Association

. May , 2010. Consumer Electronics Association.
CEA. 2013a. “15 th 

### Annual CE Owner ship and Market Potential Study.” CEA Market Research Report, April, 2013. Consumer Electronics Association. 0 5 10 15 20

Any tablet Small screen Large screen Unplugged

Idle Charging Wh/dFraunhofer USA Center for Sustainable Energy Systems 

### 75



### CEA. 2013b. “U.S. Consumer Electronics Sales & Forecasts 2009

- 2014.” CEA Market Research Report, July, 2013. Consumer Electronics Association.

CEA. 2013c. Steve Koenig. Private correspondence, Nov. 2013. Consumer Electronics Association.
CEA. 2014. “Consumer Outlook on Tablets

– Jan. 2014 Edition.” Jan. 2014. Consumer Electronics Association.
DRG. 2013. “ United States PC, Tablet, & Mobile Phone Marke t Size and Forecast, Jul. 2013 .” Daniel Research Group. http://www.danielresearchgroup.com/LinkClick.aspx?fileticket=1ejALRMAUbk%3D&tabid=122&mid=
5 22 . Rerieved Oct. 30, 2013.
EPRI. 2012. “ iPad Electricity Consumption in Relation to Other Energy Consuming Devices

- Executive Summary .” Jun. 21, 2013. http://www.epri.com/Our

Work/Documents/Energy%20Efficiency/iPadEnergyConsumeExecSummary6

- 2012Final.pdf . Retrieved Sept. 20, 2013. Flurry Analytics. 2013. Khalaf, S. “ Flurry Five

- Year Report: It’s an App World. The Web Just Lives in It .” Ap r. 3, 2013. http://blog.flurry.com/bid/95723/Flurry

- Five

- Year

- Report

- It

- s

- an

- App

- World

- The

- Web

Just

- Lives

- in

- It

. Retrieved Nov. 12, 2013.

Fo rrester . 2010. Rotmann Epps, S. “ U

. S

. Tablet Buyers Are Multi

- PC Consumers .” Aug. 19, 2010. http://www.wired.com/images_blogs/gadgetlab/2010/08/ US

- Tablet

- Buyers

- Are

- Multi

- PC

Consumers.pdf

. FhCSE. Urban, Bryan, K urt Roth, and Verena Tiefenbeck. 2011. “Energy C onsumption of C onsumer E lectronics in U.S. H omes in 2010.” Final Report to the Consumer Electronics Association. http://www.ce.org/CorporateSite/media/Government

- Media/Green/Energy

- Consumption

- of

- CE

- in

U

- S

- Homes

- in

- 2010.pdf . Dec.
Magid

. 2013

. “ Tablets Find a Home in M ore U.S. Homes .” Jun. 9, 2013. http://www.magid.com/node/250 . Retrieved Sept. 20, 2013.
Nielsen

. 2013. “Q2 2013 Cross

- platform report : viewing on demand.” Sept. 9, 2013. http://www.nielsen.com/us/en/reports/2013/q2

- 2013

- cross

- platform

- report.html

. Retrieved Oct. 17, 2013.
NPD. 2013. “ Internet Connected Devices Surpass Half a Billion in U.S. Homes, According to The NPD
Gr oup .” Mar. 18, 2013. NPD Group. https://www.npd.com/wps/portal/npd/us/news/press

releases/in ternet

- connected

- devices

- surpass

- half

- a

- billion

- in

- u

- s

- homes

- according

- to

- the

- npd

group/ . Retrieved Jan. 24, 2014. NRDC. 2012. Sullivan, D. “Consumer electronics programs: what can the Midwest do?” Jan. 12, 2012. Midwest Energy Solutions Conference 2012 p resentation. http://mwalliance.org/sites/ default/files/uploads/meeaconference/MES

- 2012_presentations_Sullivan.pdf . Retrieved Feb. 2014.
Parks Associates. 2013. “ Tablets: Disrupting Mobile Computing and the Digital Home .” Park’s Associates. Jul. 25, 2013. http://www.parksassociates.com/blog/article/pr

- jul2013

- ta blets . Retrieved Sept. 2013.
Pew. 2013a. “ Tablet Ownership 2013 .” Jun. 10, 2013. http://www.pewinternet.org/~/media//Files/Reports/2013/PIP_Tablet%20ow nership%202013.pdf

. Retrieved 18 Sept. 2013.
Pew. 2013b. “ Tablet and E

- reader Ownership Update .” Jun. 10, 2013. http://www.pewinternet.o rg/~/media/Files/Reports/2013/PIP_Tablets%20and%20e

readers%20update_101813.pdf . Retrieved 18 Sept. 2013.Fraunhofer USA Center for Sustainable Energy Systems 

### 76



## 3.11 Set

- top Boxes

3.11.1 Current Energy Consumption
Set

- T op B oxes (STBs) receive and decode signals for playback on televisions . Features and services can

var y according to service provider , subscription package, and device hardware, and may include high definition (HD) or standard definition (SD) tuners

, video

- on

- demand, digital video recording ( DVR ) capabilities, multiple tuners

, format conversion, and more. We divide STBs into two major categories: pay TV STBs and standalone STBs. Pay TV STBs are generally leased to consumers by multichannel (cable, satellite, and telco 23 

### ) TV providers and enable a variety of services and features. On the other hand, standalon e STBs may be purchased directly by consumers, and generally provide alternative services to those of pay TV STBs. Standalone STBs include digital media streaming devices 24 

### , standalone DVRs, and OTA

- DTAs. Digital media streaming adapters stream digital medi a from computer servers or
the Internet to a television or audio system. DTAs are STBs that decode digital signals for TV viewing, and these exist in two forms: (1) cable digital transport adapters 3 

### that may decode digitally encrypted cable signals for vie wing on subscriber TVs, and (2) o ver

- the

- a ir digital

- to

- analog adapters (OTA

- DTAs) that decode unencrypted over the air digital broadcast signals transmitted via antenna for viewing on older analog TVs that lack a digital tuner.

Set

- top box power draw depe nds on its features, and today there is more variety and complexity in features than ever before. In our prior study we divided subscription STBs into three feature categories: (1) DVR with any tuner; (2) non

- DVR with Standard Definition (SD) tuner, and (3 ) non

- DVR with High Definition (HD) tuner (FhCSE 2011). Since 2010, new device categories have emerged that affect power draw and usage. Among these are (4) multi

- room/video server STBs that may have DVR capabilities; and (5) video client STBs that receive programming from multi

- room server STBs. Some STBs, called thin
clients , are designed to interface with and obtain content primarily from a multi

- room video server STB or gateway that is connected directly to the service provider, rather than directly wit h the service provider. Since there are presently relatively few thin clients and video clients in service, we collectively label them thin clients in this study.

Although there are relatively few manufacturers and models of STBs, the actual power draw of a specific device depends on what combinations of features are enabled for that particular household. Service providers can change the activated features of deployed STBs through software updates. For example, a service provider might launch multi

- room DV R capability in compatible set

- top boxes STBs through a software update. Some STBs include five or more tuners that can enable simultaneous viewing or recording of several programs, though not all of these tuners may be enabled or activated. While, such

co nfiguration decisions may influence power draw to some extent, there is limited publically available information about the distribution of features enabled by different providers.

23 Other studies have referred to Telco TV as IPTV, but Telco TV includes subscription TV services that are not provided via IP, most notably
Verizon FiOS. It does not include the streaming of video over an internet con nection.

24 Sometimes called over

- the

- top (OTT) STBs, these refer to devices that receive media over the internet without a multiple system operator involved in content distribution.Fraunhofer USA Center for Sustainable Energy Systems 

### 77



### 3.11.1.1 Installed Base To gain better understanding of the complex landscape of ha rdware and features, we conducted the CE

U s age Survey to estimate the number of subscribers and different types of STBs in service. We combined those results with market research and industry specific data to estimate the feature distribution among households.

3.11.1.1.1 Pay TV Set

- top Boxes 

### The CE Usage Survey found that 95 million households subscribe to at least one multichannel video service (80% of all households, 83% of TV households). Of subscriber households, 91% claimed to have exactly one service, 8% two, and 1% three, for a total of 105 million TV subscriptions. Our survey results are comparable to other industry estimates, shown in Table 3

- 58 . Since our survey appe ars to slightly

over

- represent cable and telco subscribers, we form a best estimate of the subscriber base by taking an average of values from Nielsen, SNL, and LRG sources 25



### .

We asked U.S. adults about STBs connected to their four most

- viewed tel evisions, see Table 3

- 59

. Because we asked only about STBs associated with the first four TVs, we assumed that the ratio of STBs to TVs was constant in a given household to make a reasonable upper

- bound estimate 26 

### o f STBs per household. Thus, if a household had 8 TVs, and reported 3 STBs on the first four TVs, we would compute 3STBs/4TVs x 8TVs = 6 STBs. Based on this analysis, we found that depending on service type there are between 1.3 and 2.3 STBs (DVR + non DVR) and 0.5 to 0.7 DVR STBs per subscriber household. About 53% of subscriber households reported having at least one DVR, which is close to the 52

- 55% found by other industry sources (Nielsen 2013, LRG 2013d). Of reporting DVR households, we estimate that 90 % had one, 8% had two, and 1% had 3 or more DVRs.

Table 3

- 58 : Pay TV customers by service, millions.

Table 3

- 59 : Installed base of pay TV STBs by service (Nov. 2013 survey).

* Does not include cable DTAs.

* * S ome subscribers have more than one service and some households are not subscribers

. 

### All satellite and telco subscribers require at least one STB to receive any service in the home, but for

ca ble customers this is not always true. Some cable providers offer basic unencrypted service, and customers can receive basic unencrypted service without any STBs. Other cable providers require either

25 The original LRG data included subscribers from only the largest provid ers, which they claim account for 94% of all pay TV subscribers. We adjusted the cable values to include the missing 6%, since satellite and telco providers are principally comprised of two pro viders each.

26 If we had instead assumed that households could have only a maximum of four STBs, the totals would be about 8% lower. Service Survey

Nov. 2013 Nielsen 2013

Q2 2013 SNL 2013b

- c

Q2 2013 LRG 2013 a - b

Q3 2013 Estimate [ % ] of Tot al

Cable 62 56 55 56 56 55% Satellite 31 34 34 34 35 34% Telco 12 10 11 10 11 11% Total 105 100 99 101 101 100%

Service Subscrib ers

[ millions ] STBs per

Subscriber STBs,

[ millions ] [%] of Pay

TV STBs DVRs per

Subscriber DVRs

[ millions ] DVR:STB

by Service Cable * 56 1.33 74 44% 0.49 28 37% Satellite 35 1.99 69 41% 0.67 23 34% Telco 11 2.32 25 15% 0.58 6 25% Total / Wt. Avg. ** 101 1. 66 167 100% 0.56 57 34%Fraunhofer USA Center for Sustainable Energy Systems 

### 78



### an STB or a cable DTA for viewing digitally encrypted ch annels or for viewing digital channels on analog
televisions. The CE Usage Survey indicates that cable subscribers had the fewest STBs per household, compared with satellite and telco subscribers. Because of the survey question wording and because of
the low number of STBs per cable household, it is unlikely that U.S. adults included cable DTAs in their responses. By 2013 there were about 28 million cable DTAs in service (SNL 2013a), and adding these to the cable STBs from our survey we find 1.8 STBs per cable hous ehold.

Survey responses suggest potential for misunderstanding among the STB questions 27 

### , so these survey results should be considered only as approximate estimates of the installed base. First, about 28% of cable, 20% of satellite, and 30% of telco subscr ibers indicated they had no STBs, even though both satellite and telco customers require at least one STB to receive service. We excluded those unviable responses for satellite and telco subscribers when estimating STBs per subscriber. Second, about 5% of single

- service subscribers indicated having both a DVR and non

- DVR STB connected to the same TV. We counted these unusual responses as a single non

- DVR STB, since they may represent the presence of a standalone DVR in conjunction with a pay

- TV STB. We also assumed that households with a multi

- room STB configuration had at most one DVR. Not doing so led to a DVR count that was about 27% higher than the SNL (2013a) estimate. Table 3

- 60 shows estimates from several sou rces by technology. 28

Table 3

- 60 : Installed base of pay TV STBs, millions.

SNL 2013a Q2 2013 Survey

Nov 2013 FhCSE 2011

Q2 2010 Notes

Cable Non DVR 58.6 46.6 50.3

SD 33.8

- 35.4
HD 24.7

- 14.9
IP Client 0.1

- - DVR 26.8 27.5 22.5 No breakdown in survey by SD/HD.
SD 2.8

- - HD 22.4

- - IP Gateway 1.6

- - Cable DTA 27.6 27.6 14.0 Not asked in 2013 survey, assume SNL value

. Satellite Non DVR 74.7 45.5 59.8

SD 44.2

- 49.2
HD 30.5

- 10.6
DVR 18.9 23.0 16.3 No breakdown in survey by SD/HD. Telco Non DVR 21.8 18.6 12.1

SD 3.8

- 5.0
HD 18.0

- 7.1
DVR 10.2 6.1 3.7 No breakdown in survey by SD/HD. Total 238.5 195.0 178.7 Subtotals Cable 113.0 101.7 86.8

Satellite 93 .6 68.6 76.1 Telco 32.0 24.7 15.8
DVRs 55.9 56.6 42.5
Non

- DVRs 182.7 138.4 136.2



### Whole

- home or multi

- room STBs are growing in popularity and offer customers the flexibility of viewing or recording programming throughout their home without nee ding a fully

- featured STB for each TV. We

27 We asked participants to select all types of set top boxes connected to each of their TVs, including DVR STB, non

- DVR STB, streaming media device with DVR, and streaming media device without DVR. It is likely that participants had trouble making the distinction among these devices.

28 We do not consider the 0.6M digital cable ready devices that receive programming wi thout an STB using a CableCARD (SNL 2013a).Fraunhofer USA Center for Sustainable Energy Systems 

### 79



### asked pay TV subscribers about the multi

- room features of their set top boxes. Households indicated if they could (1) record in one room and playback in another, (2) pause live TV and resume watching in
another roo m, and (3) record five or more shows at once. Positive responses to either of the first two questions indicate that a household is likely to have a multi

- room DVR setup, while the third indicates that at least one STB that is capable of serving multiple ro oms. About 4% of U.S. adults reported having
multi

- room features (1) or (2) despite owning only one TV, so we counted these responses as single

room DVRs. Many STBs ship with features that can be enabled through software updates issued by service provider s. A major cable provider announced in Jun. of 2013 that it would be launching multi

room DVR capability to 8 million of its STBs through a software update (Multichannel 2013). This means that asking users about features may not always correctly identify m ulti

- room STBs hardware if those features have not yet been activated or if the user is unaware such features exist. Still, we can use the responses to estimate the number of multi

- room STBs. Table 3

- 61 shows our e stimates for multi

- room STBs among different service providers. Notably, a smaller portion of cable customers have a multi

room setup than do satellite and telco customers, partially because about 28% of cable households reported having no STBs installed. In total, we estimate that up to 26% of pay TV households have a
multi

- room setup (2 or more TVs and yes to questions (1) or (2)) and that 30.7% have at least one multi

room STB (1 or more TVs and yes to questions (1), (2), or (3)). We estimated the number installed by applying the percentage to the subscriber count, assuming at most one multi

- room server STB per
household.

Table 3

- 61 : Subscribers with multi

- room STBs, millions (Nov. 2013 survey).

Cable Satel lite Telco All All Pay TV Subscribers 55.7 34.5 10.7 100.8 Multi

- room households, % of subscribers 15.1% 34.7% 40.6% 25.9% Multi

- room ready households, % of subscribers 20.2% 40.0% 43.2% 30.7% Multi

- room server STBs 11.3 13.8 4.6 30.9

Table 3

- 62 : Cumulative STB shipment projections from Q2

- 2010 to Q4

- 2013 (DOE 2013a).

Base STB Base
DVR Multi

Room Multi

- Room

with DVR Video

Client Total Pct. Cable 47.0 8.4 3.3 7.2 0.4 66.3 42% Satellite 21.6 12.1 5.0 10.7 0.4 49.8 32% Telco 5.8 2.1 0.8 1.8 0.6 11.1 7% Thin Client 2.5

- - - - 2.5 2% Digital Media Streaming 27.1

- - - - 27.1 17% Total 104 22.6 9.1 19.7 1.5 156.8 100% 66% 14% 6% 13% 1% 100%

- * Thin clients are combined for cable and satellite pr oviders.



### Pay TV STB shipments from the previous three years (DOE 2013a) totaled 127 million units, slightly more than half of the current installed base. STBs with servers totaled 29 million, of which 68% had DVRs. This
total is consistent with the 31 mil lion found in our survey, and as such, these data will be used to weight the power draw values in the subsequent analysis. In the DOE dataset, the video client category represents STBs that receive video from a multi

- room video server STB. Since there are relatively few in service, we consider these with thin client STBs in our analysis.Fraunhofer USA Center for Sustainable Energy Systems 

### 80

3.11.1.1.2 Standalone Set

- top Boxes 

### Standalone STBs are those obtained independently of TV service providers, such as digital media streaming devices and standalone DVRs. Digital med ia streaming devices enable TV users to view
content delivered over the Internet

. 29 

### Though many newer smart TVs and Blu

- ray players have this functionality built

- in, here we are only concerned with non

- integrated streaming devices. 30



### We estimate there were at most 40 million digital media streaming devices installed by the end of 2013

– about four times higher than in 2010 (FhCSE 2011)

– based on cumulative sales data from 2006

- 2013 (CEA S&F 2013, BI 2014). Sales of the top three streaming media devices exce eded 15.2 million units in 2013 and these make up more than 85% of the market (BI 2014). DOE forecasts for 2013 were lower, at 10 million units (DOE 2013a). Our survey indicated that there were 57.1 million digital media streaming devices in service, and t he average household had 0.48 such devices (1.7 devices per owner household, 30% ownership). This is somewhat higher than a recent CEA survey (O&M 2013) that found 46.6 million digital streaming media devices (1.6 devices per owner household, 24% ownership ). A 2013 survey of 10,000 broadband households found that only 14% had a streaming media device (Parks 2013). Both survey estimates exceed the likely maximum installed base value and suggest potential confusion among consumers about what constitutes a dig ital streaming device. For instance, about 50% of owners reported that their streaming media devices had DVR capabilities; however the majority of devices do
not offer this feature.

Standalone DVRs comprise a small part of the installed base, as most DVRs are integrated with subscription STBs. Standalone TiVo subscribers numbered 1 million in Q3 2013, down from a peak of 1.7 million in 2007 (LRG 2013) and 1.5 million in 2010 (Gorman 2010). We estimate a similar decline in
standalone DVRs from the 3 million in 2010, for a total of 2 million in 2013.

Over

- the

- air (OTA) DTAs are devices that enable analog TVs to receive digital OTA broadcast signals. Since all new TVs must include a digital tuner, the number of these devices is expected to decline as
older TVs are retired. An appreciable number of analog CRT TVs have been retired in the previous three years, and based on analysis of survey responses 31 

### the number of households with at least one CRT TV was 60% lower in Dec. 2013 than in Aug. 2009 (CEA 2014, FhCSE 2009). We estimate that the installed
base of OTA

- DTA has declined at the same rate, and conclude that there are now 13 million units in service compared with 33 million units in 2010.

Table 3

- 63 : Installed b ase of standalone STBs, millions.

Device Units % of Standalone STBs Digital Streaming 40.2 72.5% Standalone DVR 2.0 3.6% OTA

- DTA 13.2 23.8% Total 55.4 100%

29 Such as Netflix or Hulu.

30 Such as Apple TV, Roku, or Chromecast.

31 As noted in the Television section of this report, people may incorrectly identify television types in surveys, so these numb ers should serve only as approximate indicators.Fraunhofer USA Center for Sustainable Energy Systems 

### 81



### 3.11.1.2 Unit Energy Consumption STB power draw generally depends on its available features. We consid er power draw across multiple feature categories including: provider type, ability to serve video content to multiple rooms (e.g., multi

room), HD or SD tuners, and DVR capability. STBs can have multiple tuners, allowing more than one TV
to use the same ST B simultaneously, or allowing viewers to record a program while watching another. Minimalist STBs, called thin

- clients, draw less power than ordinary STBs by relying on a full

- featured STB for their signal instead of communicating with the provider directl y.

STBs may have several power modes: (1) on

- or active

- mode, (2) sleep mode, and (3) deep sleep mode. Deep sleep is a sub

- state of sleep mode that draws even less power, but may cause the device to require more time to respond when returning to active mo de. Few STBs include a deep sleep mode, and many have similar power draw in both active and sleep modes. STBs lack a true off mode, and we believe it is uncommon for users to unplug or use power strips to completely power down STBs, since doing so may

prov oke a disruptive automatic reprogramming period.

3.11.1.2.1 Power Draw 

### To determine power draw across providers, features, and usage modes, we relied on several sources. EPA (2012) provided measurements of on

- and standby

- mode power draw for many subscription STBs,
and we used these to represent STBs manufactured and installed since mid 2010 , see Figure 3

- 38 . We
used the power draw values from (FhCSE 2011) to represent units manufactured before 2010. For each
feature combina tion

– provider, DVR/non

- DVR, single/multi

- room, HD/SD

– we averaged power draw across the measured devices. We did not have access to the installed base data for each model, and were therefore unable to further refine our model by weighting power draw by the prevalence of specific models. Figure 3

- 38 shows how power draw varies among devices in similar categories

.

Figure 3

- 38 : Power draw of subscription set

- top boxe s by provider type and selected features, n=84 (EPA 2012).



### Using a combination of installed base figures for 2010 (FhCSE 2011) and 2013 (based primarily on SNL data and secondarily on phone survey results), and industry sales data and projections (DOE 201 3a, SNL
2013a

- c), we estimated the total number of devices of each type. We further subdivided the installed base for each category by year of manufacture (pre

- or post

- 2010) to enable power draw weighting by vintage. We retained the power draw values fro m FhCSE (2011) for standalone DVRs and OTA

- DTAs. For digital streaming media devices, we used sales data (BI 2014) and power draw measurements (FhCSE 2012, EPA 2012, AnandTech 2013, Roku 2011) to calculate a weighted average power draw by mode. 0 10 20 30 on

sleep

has DVR Cable Telco

DTA single

- room multi

- room Satellite

thin client multi

- room

single

- room single

- room W

thin clientFraunhofer USA Center for Sustainable Energy Systems 

### 82



### Next, we w eighted power draw by manufacture date (pre

- or post

- 2010) to produce the estimates
shown in Table 3

- 64 and Table 3

- 65 . In cases where the sum of older devices (from 2010) and newly sold devices (from 2010

- 2013) was greater than the 2013 installed base (according to the FhCSE survey), we
assumed that older devices were retired to account for this difference. In cases where the installed base
in 2013 exceeded the sum of olde r devices and newly sold devices, we assumed that the projected sales figures were too low, and increased their number accordingly.

Average 32 

### on

- and (standby

- ) mode power draw values were 15.6 W (13.7) for cable, 13.5 W (12.2) for satellite, and 12.9 W (1 1.1) for telco providers. These values are each about 1

- 2 W lower than in 2010, even as the portion of units with HD, DVR, and video streaming capabilities have increased.

Table 3

- 64 : Power draw and installed base by device.

2010 Installed Base New Units from 2010

- 2013 2013 Installed Base Installed Power Draw [W] Sales Power Draw [W] Installed Power Draw [W] Type Features millions Active Sleep millions Active Sleep millions Active Sleep Cable SD 35.4 16. 5 15.9 27.1 15.6 13.1 31.0 15.7 13.4

HD 14.9 14.9 13.5 19.8 15.6 13.1 22.6 15.5 13.1 DVR (SD or HD) 22.5 29.6 27.3 8.4 20.8 17.0 19.6 25.8 22.9 Multi

- room 0.0 NA NA 3.3 26.9 26.0 3.3 26.9 26.0 Multi

- room+ DVR 0.0 NA NA 7.2 25.5 22.1 7.2 25.5 22.1 Thin Client 0.0 NA NA 1.7 7.8 7.7 1.7 7.8 7.7 Cable DTA 14.0 4.4 4.4 13.6 4.8 4.7 27.6 4.6 4.5 Satellite SD 49.2 8.5 7.6 12.8 6.5 5.4 40.3 7.9 6.9

HD 10.6 20.7 18.2 8.8 11.3 10.0 27.8 14.9 13.1 DVR (SD or HD) 16.3 24.0 21.8 12.1 18.8 18.0 8.2 18.8 1 8.0 Multi

- room 0.0 NA NA 5.0 23.5 21.8 5.0 23.5 21.8 Multi

- room+ DVR 0.0 NA NA 10.7 23.5 21.8 10.7 23.5 21.8 Thin Client 0.0 NA NA 1.7 6.6 5.5 1.7 6.6 5.5 Telco SD 5.0 10.7 10.5 1.0 9.4 9.1 3.5 10.3 10.1

HD 7.1 13.5 11.8 4.8 9.4 9.1 16.8 11.1 10.2 DVR (SD or HD) 3.7 19.3 14.9 2.1 15.8 12.3 8.4 17.3 13.4 Multi

- room 0.0 NA NA 0.8 9.4 9.1 0.8 9.4 9.1 Multi

- room+ DVR 0.0 NA NA 1.8 15.8 12.3 1.8 15.8 12.3 Thin Client 0.0 NA NA 0.6 9.4 9.1 0.6 9.4 9.1 Standalone Digital Streaming 8.9 8.0 6.0 27.1 3.7 1.5 40.2 4.7 2.5

DVR 3.0 33.0 30.0 0 NA NA 2.0 33.0 30.0 OTA

- DTA 33.0 6.5 0.8 0 6.5 0.8 13.2 6.5 0.8 Total /W eighted Avg

. 223.6 14.2 12.2 170.4 13.4 11.5 294.0 12.8 10.9 Subtotals Cable 86.8 17.7 16.6 81.2 15.5 13.3 113.0 15.6 13.7

Satellite 76. 1 13.5 12.1 51.0 15.5 14.2 93.6 13.5 12.2 Telco 15.8 14.0 12.1 11.1 11.6 10.2 32.0 12.9 11.1 Standalone 44.9 8.6 3.8 27.1 3.7 1.5 55.4 6.1 3.1



### 3.11.1.2.2 Usage and Consumer Behavior 

### The power draw of most pay TV STBs in 2013 varies weakly with power mode, so kn owing precisely the number of hours spend in on vs. sleep mode does not strongly influence the energy consumption estimates. If deep sleep mode becomes more prevalent, or if light sleep begins to deliver deeper reductions in power, it may be necessary to d evelop updated estimates of time spent in each mode.

32 Weighted average according to num ber of units in each device category.Fraunhofer USA Center for Sustainable Energy Systems 

### 83



### Consequently, we continue to apply the usage estimates from FhCSE (2011) to calculate unit energy consumption, as shown in Table 3

- 65

.

3.11.1.2.3 Unit Energy Consumption


### W e estimate that, on average, pay TV STBs consume 119 kWh/yr and standalone STBs consume

45 kWh/yr. Unit energy consumption (UEC) by device is given in Table 3

- 65 . Cable units continued to consume more energy per de vice, at 128 kWh/yr, compared with 112 and 106 for satellite and telco, though most figures were lower than in 2010

– 20% lower for cable, no change for satellite, and 10% lower for telco. Cable saw the largest UEC decrease mainly because of the uptake of low

- power cable

DTAs.

DVR

- enabled STBs (including multi

- room DVRs), account for about 37% of the total consumption of pay

TV STB energy use. Although their overall numbers have increased, their installed fraction remains steady at about 23% of the install ed base of pay TV STBs, mainly due to the simultaneous increase in the number of cable DTAs. The UEC of DVR STBs has declined by about 16% since 2011. Multi

- room server STBs consume on average 196 kWh/yr, account for about 20% of total pay

- TV STB energy us e, and comprise 12% of installed pay TV STBs.

3.11.1.3 Annual Energy Consumption The total annual energy consumption (AEC) of all STBs is 31 TWh, Table 3

- 65 . About 90% is attributed to pay TV STBs and 10% to standalone STBs.

Figur e 3

- 39 : Summary of installed base, UEC and AEC for STBs

. 0 10 20 30 40 50 SD
HD DVR (HD or SD) Multi-room Multi-room + DVR Thin Client Cable DTA
SD
HD DVR (HD or SD) Multi-room Multi-room + DVR Thin Client
SD
HD DVR (HD or SD) Multi-room Multi-room + DVR Thin Client Digital Streaming

DVR OTA-DTA Cable

Satellite

Telco
Standalone
millions

0 100 200 300 UEC [kWh/yr] active sleep

0 2 4 6 AEC [TWh/yr]

0 50 100 150 Cable

Satellite

Telco

Standalone millions

0 50 100 150 active sleep
UEC [kWh/yr]

0 10 20 AEC [TWh/yr]Fraunhofer USA Center for Sustainable Energy Systems 

### 84

Table 3

- 65 : UEC and AEC summary for STBs.

Units [millions] Power Draw [W] Usage [h/day] UEC [kWh]

Type Features 2013 Installed Pre

2010 Post

2010 Active Sleep Active Sleep Active Sleep Total AEC [TWh] Cable SD 31.0 3.8 27.1 15.7 13.4 12.1 11.9 69.5 58.2 127.7 4.0

HD 22.6 2.8 19.8 15.5 13.1 12.1 11.9 68.6 56.9 125.6 2.8 DVR (HD or SD) 19.6 11.2 8.4 25.8 22.9 12.1 11.9 114.0 99.4 213.4 4.2 Multi

- room 3.3 0.0 3.3 26.9 26.0 12.1 11.9 118.6 112.8 231.4 0.8 Multi

- room+ DVR 7.2 0.0 7.2 25.5 22.1 12.1 11.9 112.8 95.8 208.6 1.5 Thin Client 1.7 0.0 1.7 7.8 7.7 12.1 11.9 34.4 33.4 67.9 0.1 Cable DTA 27 .6 14.0 13.6 4.6 4.5 24.0 0.0 40.3 0.0 40.3 1.1 Satellite SD 40.3 27.5 12.8 7.9 6.9 10.8 13.2 30.9 33.2 64.1 2.6

HD 27.8 10.6 17.2 14.9 13.1 10.8 13.2 58.7 63.3 122.0 3.4 DVR (HD or SD) 8.2 0.0 8.2 18.8 18.0 10.8 13.2 74.3 86.9 161.2 1.3 Multi

- room 5.0 0.0 5.0 23.5 21.8 10.8 13.2 92.6 105.1 197.7 1.0 Multi

- room+ DVR 10.7 0.0 10.7 23.5 21.8 10.8 13.2 92.6 105.1 197.7 2.1 Thin Client 1.7 0.0 1.7 6.6 5.5 10.8 13.2 26.0 26.5 52.5 0.1 Telco SD 3.5 2.5 1.0 10.3 10.1 13.2 10.8 49.8 39.8 89.6 0.3

HD 16 .8 7.1 9.7 11.1 10.2 13.2 10.8 53.7 40.3 94.0 1.6 DVR (HD or SD) 8.4 3.7 4.7 17.3 13.4 13.2 10.8 83.5 52.9 136.4 1.1 Multi

- room 0.8 0.0 0.8 9.4 9.1 13.2 10.8 45.3 35.8 81.2 0.1 Multi

- room+ DVR 1.8 0.0 1.8 15.8 12.3 13.2 10.8 76.0 48.4 124.4 0.2 Thin Client 0.6 0.0 0.6 9.4 9.1 13.2 10.8 45.3 35.8 81.2 0.1 Standalone Digital Streaming 40.2 8.9 31.3 4.7 2.5 21.6 2.4 36.7 2.2 38.9 1.6

DVR 2.0 2.0 0.0 33.0 30.0 11.5 12.5 138.5 136.9 275.4 0.6 OTA

- DTA 13.2 13.2 0.0 6.5 0.8 10.8 13.2 25.6 3.9 29.5 0.4 Total /W eighted Avg. 294.0 107.4 186.6 12.8 10.9 14.2 9.8 59.1 45.8 104.9 30.8 Subtotals Cable 113.0 31.8 81.2 15.6 13.7 15.0 9.0 73.6 54.5 128.1 14.5

Satellite 93.6 38.1 55.5 13.5 12.2 10.8 13.2 53.2 58.7 111.9 10.5 Telco 32.0 13.3 18.7 12.9 11.1 13. 2 10.8 61.9 43.8 105.8 3.4 Standalone 55.4 24.1 31.3 6.1 3.1 18.7 5.3 37.7 7.4 45.2 2.5



### 3.11.2 Comparison with Prior Energy Consumption Estimates Our pay TV STB energy use estimate of 28.3 TWh/yr is about 18% higher than our prior estimate of

24 TWh/yr (FhCSE 2011) and close to that of 27 TWh/yr (NRDC 2011), both for 2010. The adoption of new features, such as HD, DVR, and multi

- room video server, and the overall increase in deployed STBs is driving changes in STB energy consumption in the pay TV category. Eve n as new features become adopted, the power draw of individual devices categories appears to be on a slight decline (see Table

3

- 64 ). Figure 3

- 40 and Figure 3

- 41 show trends in device sales. Annual sales of pay TV STBs is about 33 million units per year, suggesting an average product lifespan of about 7 years, based on a 238 million
unit installed base.

In Dec. 201 2 , fifteen multich annel video providers and STB manufacturers signed a voluntary agreement that aims to reduce the energy consumption of set

- top boxes (NCTA 2014) . As part of the agreement, 90% of devices purchased after Jan. 1, 2014 will need to meet ENERGY STAR v3.0 effic iency standards

. In Dec. 2013, a non

- regulatory consensus agreement was signed with the addition of efficiency advocates, and endorsed by DOE, that added an additional Tier 2 requirement for 2017 (NCTA 2014). According to DOE (2013), “t hese new standards

– developed through a voluntary agreement between the pay

- TV industry, the consumer electronics industry

, and U.S. Energy Advocacy organizations (NRDC, ACEEE)

– will improve set

- top box efficiency by 10

- 45% (depending on box type) by 2017. ” The voluntary

ag reement also includes additional energy efficiency provisions, including light sleep capabilities,Fraunhofer USA Center for Sustainable Energy Systems 

### 85



### automatic power down features, and whole

- home DVR solutions being made available as an alternative to multiple in

- home DVRs for subscribers. These changes wi ll likely affect energy consumption going forward and will need to be considered in future analyses.

In the standalone STB category, the major shift is a large increase in the installed base of digital media streaming devices. Power draw for these devices, while already low, has declined slightly from 2010. Comparisons with prior estimates are given in Table 3

- 66 an d Table 3

- 67

.

Table 3

- 66 : Prior energy consumption estimates for subscription STBs

.

Year Units Power [W] Usage [h/yr] UEC AEC Source

[millions] Active Off Active Off [kWh/yr] [TWh/yr]
Cable
2013 113 16 14 5,475 3,285 128 14.5 Current
2010 87 18 17 4,52 6 4,234 150 13.0 FhCSE 2011
2008 52

- - - - 173 9.0 LBNL 2010 2006 77 16 15 2,730 6,030 134 10.0 TIAX 2007 2003 35 16 16 1,825 6,935 140 4.9 NRDC 2005 2003

- - 23 2,555 6,205

- - DEG 2004 2003 65 23 22

- - - - ACEEE 2004 2000 49 13 11

- - 103 5.0 LBN L 2001 Satellite
2013 94 14 12 3,941 4,819 112 10.5 Current
2010 76 14 12 3,941 4,819 112 8.5 FhCSE 2011
2008 51

- - - - 206 10.5 LBNL 2010 2006 70 15 14 3,240 5,520 129 9.0 TIAX 2007 2003 32

- - - - - - NRDC 2005 2003

- - 16 2,555 6,205

- - DEG 2004 2003 32 18 17

- - - - ACEEE 2004 2000 13 17 16

- - 140 1.9 LBNL 2001 Telco
2013 32 13 11 4,834 3,926 106 3.4 Current
2010 16 14 12 4,834 3,926 115 1.8 FhCSE 2011
2008 3

- - - - 164 0.5 LBNL 2010

Table 3

- 67 : Prior energy consumption estimates for standalone STBs

.

Year Units Power [W] Usage [h/yr] UEC AEC Source

[millions] Active Off Active Off [kWh/yr] [TWh/yr] Digital Streaming
2013 42 4.7 2.5 7,884 876 36 1.6 Current
201 0 9 8.0 6.0 7,884 876 68 0.6 FhCSE 2011
OTA

- DTA
2013 13 6.5 0.8 3,942 4,818 29 0.4 Current
2010 33 6.5 0.8 3,942 4,818 29 1.0 FhCSE 2011
2008 35 6.5 0.8 4,745 4,015 27 0.9 LBNL 2011
DVR
2013 2.0 33 30 4,198 4,562 275 0.6 Current
2010 3.0 33 30 4,198 4,562 275 0.8 FhCSE 2011
2006 1.5 27 27 2,080 6,680 237 0.4 TIAX 2007 2003

- 24 24

- - - - NRDC 2005Fraunhofer USA Center for Sustainable Energy Systems 

### 86

Figure 3

- 40 : Annual STB sales to dealers by display technology.

Figure 3

- 41 : Cumulative STB sales to dealers by display technology since 2005.



### 3.11.3 References ACEEE. Amann, J.T. 2004. “Set

- top boxes: Opportunities and issues in setting efficiency standards.” American Council for an Energy

- E fficient Economy. Report No. A041. Jul. AnandTech. 2013. Google Chromecast Review. http://www.anandtech.com/show/7186/google

chromecast

- review

- an

- awesom e

- 35

- hdmi

- dongle/2

. Retrieved Mar. 2014.

BI. Hoelzel , Mark. 2014. “The Connected TV Landscape.” Business Insider Australia. http://www.businessinsider.com.au/the

- connected

- tv

- landscape

- why

- smart

- tvs

- and

- streaming

gadgets

- are

- conquering

- the

- living

- room

- 2014

- 2 . Feb.
CEA S&F. 2013. “U.S. Consumer Electronics Sales & Forecasts 2009

- 2014.” CEA Market Research Rep ort. Consumer Electronics Association. Jul.

CEA O&M. 201 3 . “1 5 th 

### Annual H ousehold CE O wnership and M arket P otential.” CEA Market Research Report. Consumer Electronics Association. May. CEA. 2014. “CRT Television Ownership and Usage Update.” Consumer Elect ronics Association. Jan. DEG. 2004. “Analysis of standards options for consumer electronics standby losses.” Codes and Standards Enhancement Initiative for PY2004: Title 20 Standards Development. Davis Energy Group Report for Gary Fernstrom, Pacific Gas an d Electric Company. May. DOE. 2013a. “National Impact Analysis.” Rulemaking for Set

- top Boxes Energy Conservation Standards and Test Procedure . U.S. Department of Energy. http://www1.eere.energy.gov/buildings/ appliance_standards/rulemaking.aspx/ruleid/33. Retrieved Feb. 2014.
DOE. 2013b. “ U.S. Energy Department, Pay

- Television Industry and Energy Efficiency Groups Announ ce Set

- Top Box Energy Conservation Agreement; Will Cut Energy Use for 90 Million U.S. Households, Save Consumers Billions ” U.S. Department of Energy. Dec. EPA. 2012. Draft 2 Version 4.1 Set Top Box Dataset. U.S. Environmental Protection Agency. http://www .energystar.gov/products/specs/sites/products/files/Draft_2_Version_4_1_Set_top_Box_Dataset.xlsx 0 10 20 30 40

2005 2007 2009 2011 2013 Digital Strm.
Telco
Satellite
Cable STBs sold annually [millions]

0% 20% 40% 60% 80% 100%

2005 2007 2009 2011 2013 Portion of annual sales

0 100 200 300

2005 2007 2009 2011 2013 Digital Strm.
Telco
Satellite
Cable STBs sold since 2005 [millions]

0% 20% 40% 60% 80% 100%

2005 2007 2009 2011 2013 Portion of sales since 2005Fraunhofer USA Center for Sustainable Energy Systems 

### 87



### FhCSE. Roth, Kurt and Bryan Urban. 2009. “Assessment of the Energy Savings Potential of Policies and Measures to Reduce Television Energy Consu mption.” Final Report to the Consumer Electronics Association. Fraunhofer Center for Sustainable Energy Systems. Oct.
FhCSE. Urban, Bryan, K urt Roth, and Verena Tiefenbeck. 2011. “Energy C onsumption of C onsumer E lectronics in U.S. H omes in 2010.” Final Rep ort to the Consumer Electronics Association. http://www.ce.org/CorporateSite/media/Government

- Media/Green/Energy

- Consumption

- of

- CE

- in

U

- S

- Homes

- in

- 2010.pdf . Dec.
FhCSE. 2012. Craig Akers, Linda Mayer, and Kurt Roth. Power Measurements of Selected Set Top Boxes. Gorman, Bill

. 2010

. “TiVo loses 96,000 subscribers in most recent quarter.” TV by the Numbers

. http:// tvbyth enumbers.com/2008/05/28/quarterly

- net

- new

- tivo

- subscribers

- 2001

- april

- 2008/3945

. May

. LBNL

. Cheung, H.Y.
, A. Meier, and R. Brown

. 2011

. Energy savings assessment for digital

- to

- analog converter boxes

. Lawrence Berkeley National Laboratory

. Prepared for U.S

. Department of Energy

. Mar. LBNL. Rosen, K., A. Meier, and S. Zandelin. 2001. “Energy use of set

- top boxes and telephony products in the U.S.” Lawrence Berkeley National Laboratory. Report No. LBNL

- 45305. Jun.

LBNL

. Sanchez, Marla, Steven Lanzisera, Bruc e Nordman, Alan Meier, Rich Brown

. 2010

. “EEDN: Set top box market assessment report.” Lawrence Berkeley National Laboratory

. Feb

. http://efficientnetwork s.lbl.gov/pubs/EEDN_task_2

- 4

- 1_STB_Market_Assessment_Report.pdf

. LRG. 2013a. “Major Multi

- Channel Video Providers Lost About 25,000 Subscribers in Q3 2013.” Leichtman Research Group. http://www.leichtmanresearch.com/press/111813release.html . Nov. LRG. 2013b. Major multi

- channel video providers lost about 345,000 subscribers in 2Q 2013. FierceCable. http://www.fiercecable.com/press

- releases/major

- multi

- channel

- video

- providers

- lost

about

- 345000

- subscribers

- 2q

- 2013 . Aug.
LRG. 2013c. “The Rise and Plateau of DVRs.” http:// www.leichtmanresearch.com/research/notes12_ 2013 .pdf LRG. 2013d. “DVRs Leveling Off at About Half of All TV Households.” http://www.leichtman research.com/press/120613release.html

. Multichannel News. Jeff Baumgartner. 2013. “Comcast Tees Up Multi

- Room DVR for X1.” http://www.multichannel.com/distribut ion/comcast

- tees

- multi

- room

- dvr

- x1/143670 . Jun. NCTA. 2014. Voluntary Agreement for Ongoing Improvement to the Energy Efficiency of Set

- Top Boxes. http://www.ncta.com/energyagreement . National Cable and Telecommunication Association.
Nielsen. 2013. “The Cross

- Platform Report | Q2 2013.” Sept. NRDC. Foster, S. 2005. “Cable and Satellite set

- top boxes: opportunities for energy savings.” Ecos Consulting report for the Natural Resources Defense Council. Mar

. NRDC

. Horowitz, Noah

. 2011

. Better viewing, lower energy bills, and less pollution: improving the efficiency of television set

- top boxes

. National Resources Defense Council

. Jun

. Roku. 2011. “Roku’s Power Consumption when Idle.” Roku Forums. http://forums.roku.com/ viewtopic.php?p=287461&sid=08c945a0ae6dc63df0d99a9e52d1cd13

. Retrieved Mar. 2014. SNL. 2013a. Set Top Box Installed Base. Private communica tion of industry research. SNL Kagan. Nov.
SNL. 2013b. SNL Kagan Releases 2nd

- Quarter U.S. Multichannel Subscriber Report . SNL Kagan. PR Web. http://www.prweb.com/releases/2013/9/prweb11 070470.htm . Sept. SNL. 2013c. “U.S. Multichannel Subscriber Update and Programming Cost Analysis.” SNL Kagan White Paper. Jun.Fraunhofer USA Center for Sustainable Energy Systems 

### 88



## 3.12 Televisions

3.12.1 Current Energy Consumption Televisions continue to be the most widely owned consumer electronic device in the U.S. at 97

- 98 % household penetration in 201 3 ( CEA O&M 2013, 2013 CE Usage Survey ). TV energy consumption varies with display type, screen size, and year of manufacture. High

- definition flat

- panel displays continue to dominate the marketplace (74% household pen etration), while displays with ultra

- high definition (UHD) are now becoming available. Newer features such as Internet capable TVs and 3DTVs are increasing in popularity, with 15% and 9% household penetration (CEA O&M 2013). At the same time, unit energy

c onsumption is declining due to improvements in display technologies.

As in prior studies, our TV energy use estimates are based primarily on usage and ownership data from the CE Usage Survey , manufacturer

- reported power draw measurements, and industry sales dat a

.

3.12.1.1 Installed Base
Televisions slightly outnumber people in U.S. homes with 338 million owned (CEA O&M 2013) and 301
mill ion plugged in ( 2013 CE Usage Survey ). A review of recent TV ownership surveys is presented in
Table 3

- 68

. Figure 3

- 42 shows t he distribution of TVs per household for 201 3 and 2010

.

Table 3

- 68 : Installed base estimates for TVs in 2013.

Year Household

Penetration Households

[millions] Units/Owner

Household Installed Base

[millions] Sources

2013 96.8% 119 2.6 301 * 2013 CE Usage Survey
2013 98.0% 119 2.9 338 CEA O&M 2013
2012 99.0% 119 2.9 340 CEA O&M 2012
2011 96.0% 119 3.0 343 CEA O&M 2011
2010 99.0% 116 3.1 353 * CE Usage Survey Oct

- 2010
2010 99.1% 116 2.9 328 Nielsen 2010

2010 95.0% 114 3.0 325 CEA O&M 2010
2009 95.8% 11 6 2.4 271 ** CE Usage Survey Aug

- 2009
2009 99.0% 114 3.0 339 CEA O&M 2009
2009 99.2% 115 2.9 335 Nielsen 2010

* Indicates TVs that were plugged into an electrical outlet during the past month. ** Indicates TVs that were used to watch television at least once in the past week.

Figure 3

- 42 : TV ownership distribution (CE Usage Survey)

.


### Plugged

- in TVs appear to have declined by 50 million units or 14% since 2010, and while sharp, this decrease may be rea sonable. Previous estimates place household TV ownership in slight excess of the U.S. population. It is plausible that many older and lesser

- used TVs (primarily CRTs) are being discarded

3% 29% 28%

20%

11%

5% 2% 1% 0% 0% 1% 0% 10% 20% 30%

0 1 2 3 4 5 6 7 8 9 10+ 2010 2013

TVs per householdFraunhofer USA Center for Sustainable Energy Systems 

### 89



### without being replaced. Nielsen found that about 1 million households own no TVs (Nielsen 2013), while our survey indicated this was closer to 4 million. Even though the number of households has increased from about 116 to 119 million households, the number owning at least one TV has remained constant at
about 115 million.

According to EPA estimates, 23.6 million TVs were disposed of in 2010 and a further 28.5 million were ready for end of life management (EPA 2011). Assuming a consistent disposal rate during the 3.5

- year period since the 2010 study, 83

- 100 million TVs woul d have been removed from the installed base during this period. Consistent with that

, a recent phone survey

- based study of CRT TVs in U.S.
households estimated that during the past five year 91 million CRT TVs were disposed by U.S.
households ( CE A 2014 )

. During the same 3.5 year period, sales to dealers were 131 million units (CEA S&F 2013), which is at least enough to mai ntain prior installed base levels.

U.S. adult s indicated the display technology and screen size of their four most

- used TVs. Though many display types exist, we limited the options to avoid confusion. The LCD category represents both LED, OLED, an d fluorescent lit displays. Consumers did not know or specify their display type for 13% of TVs
and screen size for 4% of TVs. Our survey and modeling identified 80 million C RTs plugged in in U.S
homes in 2013

. For comparison, CEA (2014) found that 41 percent of households had at least one CRT
TV
, with an average o f 1.86 CRT units per household . This yields a total of 91 million CRT TVs in homes including units in storage
, in February 2014

.
To verify the consistency of survey reported screen sizes, we compared the distribution reported size with sales data from an industry source for TVs sold from 2010

- 2012. LCD screen size agreed very well; however, many people reported owning plasma displays smaller than 35 inches even though nearly all plasma displays are greater than 37 inches. Historically, survey

- based plasma ownership estimates have been higher than cumulative sales figures (FhCSE 2011), necessitating some adjustment. To compensate, we reclassified all reported plasma displays with screen sizes 37 inches or below as LCD TVs. In total we reclassified 15.3 million plasma TVs as LCD TVs , which greatly improved the plasma TV size distribution’s agreement with sales data, without appreciably affecting the already good agreement of the LCD screen size distribution, see Figure 3

- 43 . The breakdown of TVs by display type is given in Table 3

- 69

.

Figure 3

- 43 : Screen size for LCD and Plasma TVs from 2010 to 2012

. Reclassifying survey responses for Plasma TVs of 37 in. or lower as LCD TVs improves survey agreement with sales data

.Fraunhofer USA Center for Sustainable Energy Systems 

### 90

Table 3

- 69 : Distribution of TVs by display type

. Figure 3

- 44 : TVs by display type.



### Source L CD Plasma CRT Proj

. 2013 FhCSE Model 63% 7% 27% 4% 2013 Nov. CE Usage Survey 57% 12% 27% 4% 2013 CEA O&M Survey 39% 19% 42%

- 2010 FhCSE Model 33% 7% 54% 6% 2010 CEA O&M Survey 21% 13% 62% 5% 2009 Aug. CE Usage Survey 25% 7% 62% 5%



### TV size continues to increase, with an average diagonal screen size of 34 inches, up from 29 inches in

2010 33 

### (FhCSE 2011) and 26 inches in 2006 (TIAX 2007). In Figure 3

- 45 we show the distribution of
screen size and a ge according to the Aug. 2009 survey. Primary TVs, those used most in a household, are substantially larger at about 41 inches ( 38 in 2010) . TVs averaged about 5.5 years old ( 6.2 in 2010) 34 

### according to the CE U s age Survey

.

Figure 3

- 45 : TVs by screen size and age ( Nov. 2013 survey). Bin ranges not of equal size.



### Usage patterns greatly affect TV energy consumption estimates , and n ewer, larger TVs tend to be used more frequently than older, smaller ones. We a ccounted for usage patterns by assigning TVs to a “usage priority group” where TV1 is the most used TV in a household, TV2 is the second most used, and so on. The assignments, based on survey responses , are indicated in Figure 3

- 46

.

33 Average display size is approximate. In the 2013 survey, responders gave their best estimate in inches, while i n 2010, we asked only about discrete size ranges.

34 The figure was obtained by assuming that TVs in the 15+ category were exactly 15 years old

. Since discrete size ranges were recorded, average age is approximate. 188

20 81

11
0 50 100 150 200

LCD Plasma CRT Proj. 2010 2013 Millions

3% 5% 20%

14% 28%

21%

10%

0% 10% 20% 30%

<14 14-18 19-24 25-31 32-41 42-51 51+ 2010 2013 Percentage of TVs

Diagonal Screen Size [in.] 18% 38%

23%

12% 9%

0% 10% 20% 30% 40%

<1 2-4 5-9 10-14 15+

2010 2013 Percentage of TVs

Age in YearsFraunhofer USA Center for Sustainable Energy Systems 

### 91

Figure 3

- 46 : Distribution of TVs by display technology and usage priority

.



### 3.12.1.2 Unit Energy Consumption
3.12.1.2.1 Power Draw 

### Since our previous study in 2010, two new ENERGY STAR specification s have g one into effect ( v 5.3 and

v 6.0 ), setting more stringent requirements for maximum on mode power draw based on screen area
and summarized in Table 3

- 70 (EPA 2013). ENERGY STAR

- compliant TVs accounted for 84% of the u nits sold in 2012 and 96% in 2011 (EPA 2010

- 12).

Table 3

- 70 : ENERGY STAR power draw requirements for TVs.

ENERGY STAR Screen Area

[in 2 ] Max

. On Mode

Power [W] Max. Sleep Power [W] Manufacture Date

v6.0 A P max = 100

∙ tanh(0.00085

∙ (Α

– 140) + 0.052) + 14.1 1.0 May 15, 2013

v 5. 3 A < 275 P max = 0.130∙A + 5 1.0 May 1, 2012

v 5. 3 275 ≥ A ≥ 1068 P max = 0.084∙A + 18 1.0 May 1, 2012

v 5. 3 A > 1068 P max = 108 1.0 May 1, 2012

v 4.0 A < 275 P max = 0.190∙A + 5 1.0 May 1, 2010

v 4.0 A ≥ 275 P max = 0.120∙A + 25 1.0 May 1, 2010



### We assessed TV power draw as a function of display type, screen size, and production year, developing linear regressions based on several data sources, see Table 3

- 71 . For TVs sold until 2010, we used power regressions from our 2010 study (FhCSE 2011). For TVs sold between 2010 and 2013, we developed new regressions from a combination of California Energy Commission appliance database (CEC 2 013) and the

EPA ENERGY STAR list of qualified TVs (EPA 2013). The CEC database provides active mode power draw and linear screen size (n= 4,829 models, 96% LCD or OLED and 4% Plasma), but it does not provide year of manufacture or standby power draw. Of t he listed units, 69% of LCD displays had active mode power
draw that met ENERGY STAR v5.3 (95% for v4.0), while 37% of Plasma displays met v5.3 (89% for v4.0). These compliance levels suggest that the CEC database is representative of TVs sold during the 2 011

- 2013 period, and we use their values to generate new linear active mode power regressions given in
Table 3

- 71

.

The ENERGY STAR 6.0 draft development dataset (n=430, 83% LCD, LED, or OLED; 17% Plasma) includes

ENERGY STAR qualified TVs on the market in Q4 of 2010 through 2011 (EPA 2013). Off

- mode power draw for these TVs averaged 0.27 W, and the current list (Dec 2013) of qualified TVs contains 998 models, for which the average standby mode power draw is 0.29 W. These figures are slightly lower 0% 10% 20% 30% 40%

TV1 TV2 TV3 TV4 TV5 TV6+ 2013

Projection

Plasma

LCD

CRT

0%

10% 20% 30% 40%

TV1 TV2 TV3 TV4 TV5 TV6+ 2010

Projection

Plasma

LCD

CRTFraunhofer USA Center for Sustainable Energy Systems 

### 92



### than the 0.41 W found in the 2010 study. For TVs made prior to 2008, we assume 4 W for off

- mode power draw (TIAX 2008).

The ENERGY STAR v6.0 draft 2 development dataset (n=1,697, 94% LCD+LED+OLED and 6% Plasma)
includes a ctive but not standby power draw for ENERGY STAR qualified TVs that went on the market in Q1 2011 through Q2 2012 (EPA 2013).

Table 3

- 71 : Active mode power regressions by TV screen area, display, and productio n year

.

Figure 3

- 47 : Power regressions for LCD and Plasma TVs (CEC 2013).



### Internet connected TVs, if they remain connected during standby mode, could significantly increase energy consumption; one model drawing 24W in inactive mode compare d with less than 1 W for most

non

- connected TVs (NRDC 2012). About 3% of TVs in the v6.0 development dataset offered Internet connectivity, though there were insufficient power draw data for connected

- standby mode. It is also unknown what portion of Intern et ready TVs are (1) connected to the Internet and (2) maintain their connection while the display is off, both of which would affect the standby power draw. Internet capable TVs have a 15% household penetration as of 2013 (CEA O&M 2013). 0 100 200 300 400

0 1000 2000 3000

CEC non-ES 5.0

CEC ES 5.0

[in 2 ] W LCD TVs

0 100 200 300 400

0 1000 2000 3000

CEC non-ES 5.0

CEC ES 5.0

[in 2 ] W Plasma TVs P[W]=C 1 +C 2 ∙ A[in 2 ] Display Year C 1 C 2 R 2 N Source
LCD 2011

- 3 ES 16.47 0.05 0.74 3,208 CEC

2011

- 3 non

- ES 28.59 0.10 0.69 1,419 CEC 2011

- 3 ALL * 12.58 0.08 0.54 4,627 CEC 2010 * 24.06 0.09 0.71 123 Fraunhofer 2010
2009 17.15 0.17 0.74 98 Fraunhofe r 2010 2008 11.59 0.20 0.91 99 Fraunhofer 2010
2008

- 9 * 15.98 0.18 0.81 197 Fraunhofer 2010
2005

- 7 * 19.23 0.25 0.93 121 ENERGY STAR Plasma 2011

- 3 ES 52.19 0.04 0.42 72 CEC

2011

- 3 non

- ES 105.50 0.04 0.15 124 CEC 2011

- 3 ALL * 58.26 0.06 0.24 196 CE C 2010 * 4.77 0.14 0.53 24 Fraunhofer 2010
2009

- 15.78 0.24 0.91 22 Fraunhofer 2010
2008 35.32 0.21 0.90 19 Fraunhofer 2010
2008

- 9 * 8.48 0.22 0.89 41 Fraunhofer 2010
2005

- 7 * 80.54 0.29 0.58 33 ENERGY STAR Projection 2005

- 7 * 87.45 0.07 0.61 10 EN ERGY STAR
CRT 2006 * 59.97 0.10 0.91

- TIAX 2007
* Regression used in the energy model. Other data provided for reference.
ES= ENERGY STAR qualified product; non

- ES=Non ENERGY STAR qualified product; ALL=ES + non

- ES products.Fraunhofer USA Center for Sustainable Energy Systems 

### 93



### TV power draw may be influenced by other factors, such as screen resolution

, brightness settings, and other features, though without better installed base and power draw data, these factors could not be
evaluated. For instance, Figure 3

- 48 shows how much more power is needed in a bright room vs. the
baseline of a dark room , when using automatic brightness control . On average, power draw was about 50 W higher and nearly twice for the bright room case. About 70% of TVs in the ENERGY S TAR v6.0 development dataset offer automatic brightness control, though it is not clear how many users actually implement this feature (EPA 2013), adding some uncertainty to the actual power draw measurements.

Figure 3

- 48 : Impact of TV brightness on power draw (EPA 2013).



### 3.12.1.2.2 Usage 

### Average usage per

- TV appears steady at 3.2 h/day (5.2 for the primary TV), while on

- time has increased slightly to 4.4 h/day (from 3.8 in Aug. 2009). This apparent 10% increase in un it on

- time was more than offset by the 14% decrease in the installed base during the same period, suggesting a 4% decrease in total TV active usage.

We determined usage from the CE Usage Survey . Active usage includes the time when users engage in

a ny TV

- related activities (viewing TV, DVD, game consoles, etc.), while “on time” also includes the time
when the TV is left on but unused. Our surveys asked for the usage of the four most used televisions per household. We derived usage estimates for lesse r

- used TVs using a proportional scaling 35 

### by usage priority. The precision of usage estimates for TVs beyond the four most

- used per household is not so important, since we estimate they represent only a small portion of the total usage (3%) and installed
ba se (11%)

. Their usage occurs mainly in the off mode, so energy estimates for these lesser

- used TVs is
more sensitive to off

- mode power draw and less sensitive to active mode usage and power draw
estimates.

Lawrence Berkeley National Laboratory (LBNL) cal culated TV usage profiles from Nielsen’s metered usage data in over 12,000 representative U.S. households from May 2007 to 2011 (DOE 2012). Metering devices were installed on each TV of a participating household and measured TV on

- time for each TV, though TVs that were not used at all were excluded from the dataset. They found that the average TV viewing time was 5.5 h/day, about 7 h/day for primary TVs and less than 2.5 h/day for non

- primary TVs.

35 For each TV display category, we calcul ated the average usage for TVs 4 and 5 using a proportional scaling by TV usage priority (e.g., usage of TV5 = average(TV1/TV2, TV2/TV3, TV3/TV4)∙TV4). 0 50 100 150 200 250 300

TVs, n=301 Bright Room - 300 Lux Dark Room - 0 Lux W

0 100 200 300

0 100 200 300 Bright Room - Dark Room [W]

Bright Room Mode [W]Fraunhofer USA Center for Sustainable Energy Systems 

### 94



### These values are generally similar to our values of 7.0 and 2.9 h/day for primary and non

- primary TVs, respectively. The LBNL study also compared results with data from the 2009 Renewable Energy Consumption Survey (EIA 2011) and noted that the survey method produced lower usage values than the Nielsen data set, whi ch was based on in

- home metering of TV on

- time. According to Nielsen (2013),

per

- person TV usage in 2013 amounts to 5.6 h/day (2,049 h/yr), of which 86% is traditional TV, 7% is

time

- shifted TV, 3% is DVD/Blu

- Ray, and 4% is video game console usage. These per

- person usage figures remain relatively unchanged in recent years (5.5 h/day in 2012 and 2011).

Of the TVs represented in our survey, Plasma TVs had the highest usage at about 5.8 h/day, followed by LCD (4.8), Projection (4.7), and CRT (3.1). Newer TVs had higher usage than TVs that were 3 or more years old (5.3 vs. 4.7 h/day), and larger TVs had higher usage than those less than 40 inches (6.1 vs. 4.4 h/day).

3.12.1.2.3 Unit Energy Consumption 

### To calculate UEC and AEC for TVs, we combined input from the CE U s age Survey with the power draw regressions from Table 3

- 71 to determine energy usage by mode for each TV usage group, subdivided by display technology and screen size . We then applied our 2013 installed base estimat e of 300.7 million
TVs to obtain the AEC estimates shown in Table 3

- 72 . We estimate average unit energy consumption at 166 kWh/yr in 2013 and about 9% lower than in 2010. Even though screen sizes of newly purchased TVs continue to increase, per

- unit consumption has continued to drop stemming from the major fall of less

efficient CRT displays.

Table 3

- 72 : UEC and AEC calculations for TVs for 2013

. Usage Installed Base U sage Size Age Power [W] UEC AEC AEC Group [millions] [%] [h/day] [in] [yr] Active Off [kWh/yr] [TWh/yr] Fraction
TV1 115 38% 7.0 41 4.4 105 1.1 274 31.6 63% TV2 81 27% 3.8 32 5.6 81 1.6 125 10.1 20% TV3 48 16% 2.6 29 6.0 78 1.9 89 4.2 9%
TV4 24 8 % 2.4 29 6.5 80 2.0 84 2.0 4%
TV5 11 3% 1.6 28 7.3 81 2.4 65 0.7 1% TV6+ 23 8% 1.1 28 8.0 84 2.6 57 1.3 3% Total /Avg. 301 100% 4.4 34 5.5 90 1.6 166 50 100%
Estimates based on CE Usage Survey (Nov. 2013), CEA 2013 sales data, CEA partner surveys, a nd EPA power data.

Figure 3

- 49 : TV unit energy consumption by usage priority and display type. 0 100 200 300 400

TV1 TV2 TV3 TV4 TV5 TV6+ off

on kWh/yr

0 100 200 300 400

LCD Plasma CRT Proj. off

on kWh/yrFraunhofer USA Center for Sustainable Energy Systems 

### 95



### 3.12.1.3 Annual Energy Consumption
We estimate that TVs consume 50 TWh/yr, with primary TVs responsible for 63 % of the total AEC , as summarized in Table 3

- 72 and Table 3

- 73 . This 23% decline from 2010 consumption comes primarily from the 15% drop in the installed base and from the mass ive decline of CRTs in favor of more efficient LCD displays.

A bout 93 % of TV energy usage occurs in active mode, while the remaining 7 % occurs in off mode . The
shift toward lower off

- mode consumption is a result of improved off

- mode efficiency of newer TVs (the large majority under 1 W) and the concurrent retirement of older, unused TVs with higher off

- mode power draw. Naturally a TV’s usage priority has the biggest influence: 9 8 % of TV1 energy usage is from active mode, compared to less than 70% for TV 5 an d beyond.

Figure 3

- 50 : Active and off mode AEC by TV priority and display type.



### 3.12.2 Comparison with Prior Energy Consumption Estimates Prior estimates of television AEC are given in Table 3

- 73 together with our estimates of 50 TWh for 2013. For the first time in over a decade, the number of plugged

- in TVs has decreased significantly, with a shift from CRT to LCD TVs contributing to a sharp 20% decline in AEC. Our best understanding of this decline is that older, less

- efficient TVs and primarily CRT displays are being taken out of service

– either to be recycled, disposed of, or set aside. Since our only indication of these changes come from our phone survey, there remains some uncertainty. Active TV usage remained fairly consistent, while TV on

time has increased somewhat from previous estimates. Active mode power has continued to decrease, even while average screen size continues to increase, owing to the greater e fficiency of newer displays.

Table 3

- 73 : Prior energy consumption estimates for TVs

.

Year Units Power [W] Usage [h/yr] UEC AEC Source

[millions] Active Off Active Off [kWh/yr] [TWh/yr]
2013 301 90 1.6 1,6 06 7,154 166 50 Current
2010 353 104 3.0 1,392 7,368 183 65 FhCSE 201 1 2009 342 105 3.3 1,392 7,368 188 64 FhCSE 201 1 2006 275 111 4 .0 1,882 6,878 244 67 TIAX 2008 2006 * 237 98 4 .0 1,882 6,878 222 53 TIAX 2007 2004 * 234 100 3.9 1,278 7,483 156 37 NRDC 2005 1998 * 212 75 4.5 1,443 7,317 150 31 LBNL 1999 1997 * 229 60 4 .0 1,460 7,300 117 27 ADL 1998 1995 * 191 77 4 .0 1,498 7,262 141 26 LBNL 1998
* Analog TVs only. 0 10 20 30 40

TV1 TV2 TV3 TV4 TV5 TV6+ off

on TWh/yr

0 10 20 30 40

LCD Plasma CRT Proj. off

on TWh/yrFraunhofer USA Center for Sustainable Energy Systems 

### 96



### O lder CRTs continue to be replaced with newer, more efficient digital flat panel TVs, a s indicated by Figure 3

- 51 and Figure 3

- 52

. About 91 % of the 40 million TVs sold per year are flat panel LCD displays,
and these have overtaken CRTs as the most prevalent d isplay technology in homes

.

Figure 3

- 51 : Annual TV sales to dealers by display technology (CEA 201 3, 2010 )

.

Figure 3

- 52 : Cumulative TV sales to dealers by display technology since 1999 (CEA 201 3, 2010 )

.



### 3.12.3 References ADL. 1998. “Electricity consumption by small end uses in residential buildings.” Final Report by Arthur D. Little for the U.S. Department of Energy, Office of Building Equipment. Aug.

CEA. 2014. “ 2014 CRT Television and Monitors per U.S. Household ” . CEA Market Research Report. April.
CEA. 2013. Second Annual Report of the eCycling Leadership Initiative. Consumer Electronics Association. http://www.ce.org/CorporateSite/media/Government

- Media/Green/eCycling

Leadership

- Initiative

- Year

- Two

- Report.pdf . Apr.

CEA O&M. 2009. “11 th 

### Annual H ousehold CE O wnership and M arket P otential.” CEA Market Research Report. Consumer Electronics Association. May.

CEA O&M. 2010. “12 th 

### Annual H ousehold CE O wnership and M arket P otential.” CEA Market Research Report. Consumer Electronics Association. May.

CEA S&F. 2013. “U.S. Consumer Electronics Sales & Forecasts 2009

- 2014.” C EA Market Research Report. Consumer Electronics Association. Jul.

CEA S&F

. 2010. “ U.S. C onsumer E lectronics S ales & F orecasts 2006

- 2011.” CEA Market Research Report. Consumer Electronics Association. Jul.
CEC. 2013. Appliance Eff iciency Database. California Energy Commission. http://www.appliances.energy.ca.gov/QuickSearch.aspx

. Retrieved Dec. 2013. 0 10 20 30 40

1999 2001 2003 2005 2007 2009 2011 2013 Projection
Plasma

LCD

CRT TVs sold annually [millions]

0% 20% 40% 60% 80% 100%

1999 2001 2003 2005 2007 2009 2011 2013 Portion of annual sales

0 100 200 300 400

1999 2001 2003 2005 2007 2009 2011 2013 Projection
Plasma

LCD

CRT TVs sold since 1999 [millions]

0% 20% 40% 60% 80% 100%

1999 2001 2003 2005 2007 2009 2011 2013 Portion of units sold since 1999Fraunhofer USA Center for Sustainable Energy Systems 

### 97



### DOE. 2012. “Television Usage Analysis: Energy Efficiency Progra m for Consumer Products: Television Sets.” U.S. Department of Energy. http://www1.eere.energy.gov/buildings/appliance_standards/ pdfs/tv_tpnopr_usagea nalysis.pdf . Mar.
EIA. 2011. “2009 Residential Energy Consumption Survey.” U.S. Energy Information Administration. http://www.eia.gov/consumption/residential/index.cfm

. EPA. 201 3 . “EN ERGY STAR program requirements for televisions.” Partner commitments Versions 4.0 and 5.0. Environmental Protection Agency. Oct.
EPA. 2012, 2011, and 2010. ENERGY STAR Unit Shipment and Market Penetration Report. Calendar Year Summaries. Environmental Prot ection Agency.
EPA. 2011. “Electronics Waste Management in the United States Through 2009.” Environmental Protection Agency. May

FhCSE. Urban, Bryan, K urt Roth, and Verena Tiefenbeck. 2011. “Energy C onsumption of C onsumer E lectronics in U.S. H omes in 2010 .” Final Report to the Consumer Electronics Association. http://www.ce.org/CorporateSite/media/Government

- Media/Green/Energy

- Consu mption

- of

- CE

- in

U

- S

- Homes

- in

- 2010.pdf . Dec.

FhCSE. Roth, K urt and B ryan Urban. 2009. “Assessments of the energy savings potential of policies and measures to reduce television energy consumption.” Final report to the Consumer Electronics
Association. Oct.
LBNL. Rosen, K. and A. Meier. 1999. “Energy use of televisions and videocassette recorders in the U.S.” Lawrence Berkeley National Laboratory. Report LBNL

- 42393. Mar.
LBNL. Sanchez, M.C., J.G. Koomey, M.M. Moezzi, and W. Huber. 1998. “Miscellaneous elect ricity use in the U.S. residential sector.” Lawrence Berkeley National Laboratory. Report LBNL

- 40295.
Nielsen. 2010. “Television audience 2009.” Apr. http: //blog.nielsen.com/nielsenwire/wp

content/uploads/2010/04/TVA_2009

- for

- Wire.pdf

. Nielsen. 2012. Viewing on Demand. The Cross

- Platform Report Q2: 2012. http://www.nielsen.com/ us/en/reports/2012/state

- of

- the

- media

-- cross

- platform

- report

- q2

- 2012.html . Nov.

Nielsen. 2013. “ No TV? 5 million U.S. households bid boob tube goodbye .” USA Today. http://www.usatoday.com/story/money/business/2013/04/07/zero

- tv

- homes/2061127

. Nielsen. 2013. State of the Media U.S. Consumer Usage Report.
Nielsen. 2013. Viewing on Demand. The Cross

- Platform Report Q2: 2013. http://www.nielsen.com/us/en/reports/2013/q2

- 2013

- cross

- platform

- report.html . Sept.
NRDC. Horowitz, N. 2012. NRDC Comments on ENERGY STAR’s Final Draft Version 6.0 Eligibility Criteria for Televisions. National Research Defense Council. Jul.
NRDC. Ostendorp, P., S. Foster, and C. Calwell. 2005. “Televisions: active mode energy use, new horizons for energy efficiency.” National Research Defense Council. Mar.

TIAX. Roth, K., K. McKenny. 2007. “Energy consumption by consumer electronics in U.S. Residences.” Final report to the Consumer Electronics Association (CEA). Jan.
TIAX. Roth, K., K. McKenny, R. Ponoum, and C. Paetsch. 2008. “Residential miscellaneous electric loads: energy consumption characterization and savings potential in 2006 and scenario

- based projections for 2020.” Apr.Fraunhofer USA Center for Sustainable Energy Systems 

### 98



## 3.13 Video Game Systems

3.13.1 Current Energy C o nsumption The video game systems described in this section refer to video game consoles, such as th e Sony PlayStation 3, Nintendo Wii, or Microsoft Xbox 360, and includes consoles in the installed base as of Jul. 2013. Hence, the Sony PlayStation 4 and Xbox One gaming consoles were not included as they were released in fall of 2013. Handheld devices, su ch as the Sony Playstation Portable and the Nintendo DS are not covered in this report.

3.13.1.1 Installed Base
We estimate an installed base of 128 36 

### million video game consoles in 2013 (see Table 3

- 74 ) based on the CE Usage Survey (see A ppendix A). This is 17 percent higher than in 2010 (FhCSE 2011). We also asked in this survey about the ownership of recently released video game consoles such as Xbox One and PlayStation 4; however, the 128 million installed base estimate excludes those c onsoles. Appendix

B.3.1 presents an installed base estimate for video game consoles in early 2014 that includes the Xbox One and PlayStation 4.

Table 3

- 74 : Installed base of video game consoles

.
Installed Base [millions] Penetration Sources

128 51% 2013 CE Usage Survey



### We estimate the installed base of different video game console models from the CE Usage Survey . Each video game console model has several vintages, defined by the year of release, that have different power draws in operational modes. Consequently, we estimate the installed base distribution by model and vintage using sales data provided by Microsoft, Nintendo and Sony (Calland 2014, Jessop 2014,
Boxleitner 2 014 , Nintendo 2013 ) . If the sum of the sales of a particular video game console model
exceeds the installed

- base estimate from the CE Usage Survey , we adjusted the installed base estimates for different vintages of specific models by eliminating units of the oldest vintage(s) until the installed based estimates agreed. For example, the survey yielded a lower installed base estimate of Microsoft Xbox 360 units than cumulative Xbox 360 sales, so we removed units sold in 2005 and 2006 from the
installed b ase. We also found that all owners of the Nintendo GameCube console had not used the console for any purpose “yesterday” (see Figure 3

- 54 ). Thus, we assumed that no more units remained
in the installed base.

Figure 3

- 53 shows that s o

- called 7 th 

### generation consoles , i.e. the Nintendo Wii (Wii) , Sony PlayStation 3 (PS3), and Microsoft Xbox360 (Xbox 360) , account for 77% of the installed base. The Sony PlayStation 2 (PS2), released in March, 2000, remains on e of the most popular (17% of installed base) video game consoles ( Figure 3

- 53 ); this is consistent with the 20% estimate in 2012 of Nielsen (2012). The Nintendo Wii U, released in Nov. 2012, introduced the 8 th 

### generation of video game consoles. As of mid

- 2013, we estimate that it accounted for approximately 1% of the installed base.

36 We adjusted final installed base results using sales data provided by Nintendo, Sony and Microsoft (C alland 2014, Jessop 2014, Boxleitner 2014, Nintendo 2013).Fraunhofer USA Center for Sustainable Energy Systems 

### 99

Figure 3

- 53 : Fraction of video game systems installed in U.S. homes by platform

. 

### 3.13.1.2 Unit Energy Consum ption We used several modes to characterize gaming system energy consumption. Collectively, we refer to
“Active

- Gaming”, “Active

- Video streaming”, and “Active

- Video playback” as active modes.

 Active

– Gaming : The system is on and a game is being played.

 A ctive

– Video streaming : The system is on and video or audio is being played from a
network.

 Active

- Video playback : The system is on and video or audio is being played using its built

in DVD/Blu

- ray drive.

 Navigation : The console is on, but the user is not providing input to the console via the controller, i.e., the console is not being actively used.

 Standby : The power has been switched off by the user, but the system remains plugged in.

T he number of video game console owners who use consoles for vi deo streaming is increasing (Nielsen 2013)

, so our assessment consider s separate mode s for “Video streaming ” and “Video playback

. ” The energy consumption characteristics of “Navigation” mode used in our previous study ( FhCSE 2011 ) are very similar to those of the “Idle” mode as defined in Hittinger et al. (2012) and in EPA’s specification for game consoles (EPA 2013). Consistent with our prior study, w e decided to use only the “Navigation”
mode in this study

.

3.13.1.3 Power Draw
Table 3

- 75 summarizes the estimated power draw of video game consoles as a function of console platform, vintage, and operational mode. The power draw values for the 7 th 

### and 8 th 

### generations of video game consoles presented in this table were provided by video game co nsole manufacturers ( Calland 2014, Jessop 2014, Boxleitner 2014). They are consistent with power draw measurements from other studies analyzing video game console energy consumption (LBNL 2013, Hittinger et al. 2012, NRDC 2010). In addition, we used the po wer draw values for the Microsoft Xbox and Sony PlayStation 2 from NRDC (2010). Wii U

1% Wii

33%

Xbox
360 26% Xbox 5% PS 3 18% PS 2 17%Fraunhofer USA Center for Sustainable Energy Systems 

### 100

Table 3

- 75 : Installed base and power draw by mode of video game systems.

Installed Base Power [W]

Years [millions] [%] Gaming Video Streaming Video

Playback Navigation Standby

Nintendo Wii U 2012

- 2013 1.6 1.2% 33 31

- 32 0.4 Wii 2006

- 2013 42 33% 16 16

- 14 5.8 *

Microsoft Xbox 360 S/E 2010

- 2013 21 17% 86 67 67 67 0.4 Xbox 360 2007

- 2009 12 9% 121 97 96 97 1. 8
ALL Xbox 360

/ Wt. Avg. 2007

- 2013 33 26% 99 78 77 77 0.9 Xbox 2001

- 2008 6.1 5% 64

- - 60 1.7 Sony PS3 Super Slim 2012

- 2013 4.3 3% 82 62 74 68 0.2 PS3 Slim 2009

- 2011 12 9% 102 77 94 91 0.7 PS3 2008 4.4 3% 137 112 126 115 1.3 PS3 2007 2.3 2% 1 90 160 178 165 1.4 PS3 2006 0.6 0.5% 220 166 209 188 1.5
ALL PS3/Wt. Avg. 2006

- 2008 23 18% 117 92 108 101 0.8 PS2 2000

- 2013 22 17% 24 24 ** 24 24 1.7 Total/Wt. Avg.

- 128 100% 60 49 72 51 2.6

* Calculated as the weighted average based on the portion o f different vintages of the Nintendo Wii gaming consoles by year ( 1.7, 1.7 and 0.7 watts if connect24 disabled, 10, 7 and 5watts if enabled for Wii gaming consoles released since 2006, 2009 and 2010, resp ectively (Boxleitner 2014) ) and assuming that 30% of users have the Wii connect24 disabled (FhCSE 2011). Wi iconnect24 is not available on the

newer Wii U console.

** We used power draws for video streaming and playback the same as for active mode and navigation because we did not find power draw values for these modes.



### 3.13.1.3.1 Usage 

### We asked about video game console usage in the CE Usage Survey (2013). Based on the responses received and our usage estimation models (see Appendix B.3.4 for more details), we estimate that systems spend an average of 1 hour total per day in all active modes, i.e., in active

- gaming, active

- video streaming and active

- video playback modes. In addition, we estimate that video game consoles were left

on for an additional 2.4 hours/day in 2013 (i.e., navigation mode). Among different video game console platforms, the most actively used video game consoles were the Xbox 360, PlayStation 3 and Wii U, for 1.5, 1.5 and 1.1 hours/day, respectively (see Figure 3

- 54 ). Our estimates of average active usage and time spent in navigation mode in 2013 are less than the 3.1 hours/day active usage and 4.0 hours/day in on mode found in our study in 2010 (FhCSE 2011).Fraunhofer USA Center for Sustainable Energy Systems 

### 101

Figure 3

- 54 : Turned ON and activ ely used hours/day for different video game console platforms

.

Table 3

- 76 : Usage by different video game consoles (CE Usage Survey).
Usage [h/yr]
Years Gaming Video Streaming Video Playback Navigation Sta ndby
Nintendo Wii U 2012

- 2013 108 293

- 1,205 7,154 Wii 2006

- 2013 100 82

- 876 7,702 Microsoft Xbox 360 S/E a 2008

- 2013 365 146 37 693 7,519 Xbox 360 2007 402 146

- 693 7,519 Xbox 2001

- 2008 183

- - b 2
, 154 6,424 Sony PS3 Slim & Sup er Slim 2006

- 2013 394 115 44 657 7,550 PS2 2000

- 2013 197

- 22 1,059 7,483 Total/Wt. Avg.

- 245 89 21 885 7,521

a Xbox 360 S and Xbox 360 E are two redesigned model released in 2010 and 2013, respectively, of the Xbox 360 video game console (released in 2005). b The Xbox has an accessory that enables the playing of DVDs. Eight percent of CE Usage Survey (2013) respondents reported that they played DVDs on their Xbox “yesterday” (See AppendixB.3). However, we did not use this data in our usage and energy consumption estimates because we did not have power draw data for Xbox gaming consoles using this accessory.

Table 3

- 77 : Annual hours by mode for video game consoles for LBNL 2013, FhCSE 2011 and current stud y
.

Year Active Modes Standby Source
2013 1,240 7,521 Current study
2013 1,704 7,070 LBNL 2013 2010 1,450 7,310 ResCE 2010



### Table 3

- 78 compares the breakdown of console usage between gaming and other active modes in 2013,

2012 and 2010. We found a similar breakdown of time spend in active modes in 2013 and 2010. According to Nielsen (2013), game console users spent about 8% less of their total active time gaming in
2012 than in 2011.

Table 3

- 78 : Comparison of different estimates for the portion of active time in gaming a nd other modes

.

Year Active: Gaming Active:Other Source
2013 69% 31% Current study
2012 54% 46% Nielsen Newswire 2013
2010 66% 34% CEA Gaming and Energy Study 2010

0 1 2 3 4 5 6 7

Xbox Wii U PS2 Xbox
360 PS3 Wii

Left ON 5.9 3.3 2.9 1.9 1.8 2.4 Actively used 0.5 1.1 0.6 1.5 1.5 0.5 HoursFraunhofer USA Center for Sustainable Energy Systems 

### 102



### The CE Usage Survey found that the Nintendo Wii and Wii U gaming consoles were used more than 50% of the time for other purposes than gaming ( Figure 3

- 55 ).

Figure 3

- 55 : Distribu tio n of active usage among gaming and video ( streaming and playback ) by platform

.



### 3.13.1.3.2 Unit Energy Consumption 

### Our calculations of video game console UECs for different platforms are summarized in Table 3

- 79

.

Table 3

- 79 : UEC calculation for video game systems

. UEC [kWh/yr]

Years Installed Base

[millions] Gaming Video Streaming Video

Playback Navigation Standby Total

Nintendo Wii U 2012

- 2013 1.6 3.5 9.2

- 39 2.6 54 Wii 2006

- 2013 42 1.6 1.3

- 13 45 60 Microsoft Xbox 360 S/E 2010

- 2013 21 32 9.5 2.6 46 2.9 93 Xbox 360 2007

- 2009 12 45 14 2.9 67 14 143
ALL Xbox 360/Wt. Avg. 2007

- 2013 33 36 11 2.7 53 6.3 109 Xbox 2001

- 2008 6.1 12

- - 129 11 152 Sony PS3 Super Slim 2012

- 2013 4.3 32 7.1 3.3 45 1.7 89 PS3 Slim 2009

- 2011 12 40 8.9 4.1 60 5.1 118 PS3 2008 4.4 54 13 5.5 76 9.8 158 PS3 2007 2.3 75 18 7.8 108 11 220 PS3 2006 0.6 87 19 9.2 124 11 250
ALL PS3/Wt. Avg. 2006

- 2008 23 46 11 4.7 66 6.1 134 PS2 2000

- 201 3 22 4.7

- 0.5 25 13 43 Total/Wt. Avg.

- 128 20 5.3 2.7 41 20 88



### Figure 3

- 56 shows the breakdown of UEC and annual hours in 2013 by different modes compared with

usage . On average, navigation mode accounts for the largest porti on of UEC in 2013.

Figure 3

- 56 : Video game console UEC and u sage by mode

. 0% 20% 40% 60% 80% 100%

Xbox Xbox 360 PS2 PS3 Wii WiiU Active-Video playback Active-Video streaming Active-Gaming

0% 20% 40% 60% 80% 100% UEC Usage Active-gaming Video streaming Video playback Navigation StandbyFraunhofer USA Center for Sustainable Energy Systems 

### 103



### 3.13.1.4 Annual Energy C onsumption Video game systems consumed 11TWh in 2013 (see Ta ble 3

- 80 ).

Ta ble 3

- 80 : AEC summary for video game systems

UEC [kWh/yr] Installed Base [million] AEC [TWh]
88 128 11



### Seventh

- generation consoles, e.g. Microsoft Xbox 360, Nintendo Wii and Sony PlayStation 3, account f or the largest portion of AEC ( Figure 3

- 57 ) as well as the installed base.

Figure 3

- 57 : Annual Energy Consumption by different video game consoles



### 3.13.2 Comparison with P rior Energy Consumption Estimates
Table 3

- 81 summarizes prior energy consumption estimates for video game systems.

Table 3

- 81 : Prior energy consumption estimates for video game system s

.

Year Units [millions] Power [W] Usage [h/yr]

Source

Active All Idle + Navigation Standby Activ e All Idle + Navigation Standby UEC

[kWh/yr] AEC

[TWh/yr]
2013 128 58 a 51 2.6 355 885 7,521 88 11 Current
2013 105 46

- 1 1,704 c

- 7,056 68 7.1 LBN L 2013 2010 75 93 d 79 3.4 382 2,514 e 5,865 213 16 Hittinger et al. 2012
2010 109 85 a 75 2 1,120 330 7,310 135 14.7 FhCSE 2011
2008 63

- - - - - - - 16.3 b NRDC 2008 2006 64 36 31 0.8 406 558 7,796 36 2.4 TIAX 2007 1999 54 8

- 1 175

- 8,585 10 0.5 LBNL 2001 1995 64 20

- 2 365

- 8,395 24 1.5 LBNL 1998

a Weighted average of gaming and other uses. b Assumes that 50% of users leave on their system all the time.

c Includes time console is actively used and time console spends in navigation mode. d Does not include power draw for Sony PlayStation 2.

e Assumed that 30% of users leave their console idle when not in use.


### All three components of the AEC calculations have changed appreciably since 2010. First, the installed base increased by 17 percent. Rela tive to LBNL (2013), the current study found a higher proportion of PS2 consoles and fewer PS3 consoles; this could reflect differences due to the sample (households undergoing energy audits) and sample size (n=113) of that study (2013).

Second, the avera ge power draw in all modes decreased for the more recent versions of the 7 th



### - generation game consoles, which account for 77% of the installed base ( Figure 3

- 58 ). In general, game console active gaming

- mode power draw increased unt il it peaked around 2005/2006. Since then, the original versions of the two consoles with the highest active

- mode power draw, the PS3 and Xbox 360, have been replaced by versions that, ultimately, drew about 65 and 52 percent less power than their original versions, respectively. On the other hand, the active

- gaming mode power draw of the new Wii U Wii U
0.1 Nintendo Wii

2.5 Microsoft Xbox 360
3.4 Microsoft Xbox

0.9 Sony PS 3

3.1 Sony PS 2

0.9

0 2 4 6 8 10 12 TWh/yearFraunhofer USA Center for Sustainable Energy Systems 

### 104



### console is higher than that of the Wii it replaced. Nonetheless, the Nintendo Wii U still draws less power than the other two video game console platforms, and o nly accounts for about 1 percent of the 2013
installed base.

Figure 3

- 58 : Historical active

- gaming mode power draw values for video game systems (Calland 2014, Jessop 2014, Boxleitner 2014, NRDC 2010)



### Last ly, the estimated annual total active hours is almost three times smaller than in 2010, while the total
number of active

- all plus navigation hours decreased by about 18 percent (FhCSE 2011). The reason for the large decrease in estimated active

- use hours i s not clear. First, the active

- all hours estimate is similar to the estimate derived in Hittinger et al. (2012) from Nielsen usage data for 2010 and that of another phone survey (5.8 hours/ week per respondent ; PWC 2012). The difference in active

- all estima tes between our current and prior study (FhCSE 2011) could be due to several reasons. First, in the 2013

survey we asked about the respondent's usage "yesterday" instead of "per week" as in 2010 . Asking about active weekly usage instead of one particular d ay (i.e. yesterday) could create biases in average active usage estimates because U.S. adults may not accurately recollect their weekly usage. Second, in 2013, we asked for a response in hours and minutes, which can give a more granular answer tha n asking
about "only hours ” , which was survey method in 2010. Moreover, we found that our estimate (2.7 hours/day) for active usage in 2013 excluding U.S. adult s who answered zero hours/day is close to the 2010 estimate (3.1 hours/day) including U.S. adults who answered zero hours/week. This suggests that

in 2013 more U.S. adults answered that they did not use their video gaming console at all than in 2010. Potential explanations for a reduction in the total time spent in all active modes include the migrat ion of

some gaming activity to portable devices (i.e., smart phones and tablets) and higher penetration of video game consoles with auto power down (APD) functionality.

The field

- metering study performed by Lawrence Berkeley National Laboratory (LBNL 2013 ) monitored the power draw of 113 game consoles for three to ten weeks. The study measured an average time in all
active mode s that exceeds our estimate by more than 40 percent. This is mainly due to large differences in usage for the Wii consoles, i.e., L BNL (2013) estimates that the average Wii console spent more than
four times more time in all active modes than non

- Wii consoles. The reason for the difference in Wii

0 50 100 150 200 250

2000 2002 2004 2006 2008 2010 2012 2014 Year of Release PS3

PS3 Slim

PS2 PS3 Super Slim

Game Cube Wii U Xbox Xbox 360

Xbox 360 Slim Wii PS 4

Xbox One WFraunhofer USA Center for Sustainable Energy Systems 

### 105



### usage is not clear; however, both studies estimated similar time spent in active mode for the PS3 and
Xbox 360.

3.13.3 References Boxleitner, W. 2014. Personal Communication. Nintendo of America Inc. Feb. Calland, T. 2014. Personal Communication. Microsoft. Feb.
CEA. 2013. “15 ft 

### Annual household CE Ownership and Market Potential.” CEA Market Resear ch Report. Consumer Electronics Association. Apr. EPA. 2013. “Game Console Version 1.0 Recognition Program.” Mar. https://www.energystar.gov/products/ specs/game_console_version_1_0_recognition_program_pd

FhCSE. Urban, Bryan, K urt Roth, and Verena Tiefenbeck. 2011. “Energy C onsumption of C onsumer E lectronics in U.S. H omes in 2010.” Final Report to the Consumer Electronics Association. http://www.ce.org/CorporateSite/media/Government

- Media/Green/Energy

- Consumption

- of

- CE

- in

U

- S

- Homes

- in

- 2010.pdf . Dec.
Hittinger, E., K.A. Mullins, I . Azevedo. 2012. “Electricity consumption and energy savings potential of video game consoles in the United States.” Energy Efficiency. Mar. Jessop, J. 2014. Personal Communication. Sony Computer Entertainment America. Feb. LBNL. Desroches, L., J. Greenbl att, and S. Pratt. 2013. “Video game console usage and national energy consumption: Results from a field

- metering study” Lawrence Berkeley National Laboratory Report.
LBNL

- 6251E. Jun. Matthews, M. 2013. “U.S. video game hardware in 2012: Winners, losers a nd retirees.” Gamasutra. Jan. http://www.gamasutra.com/view/news/184714/US_video_game_hardware_in_2012_Winners_loser s_and_retirees.php Nielsen Newswire 2013, “Play vs. stream: the modern gaming console.” Mar. http://www.nielsen.com/us/en/newswire/2013/play

- vs

-- stream

-- the

- modern

- gamin g

- console.html

. Nielsen. 2012. “U.S. Gaming: A 360 o 

### View.” Feb. http://www.nielsen.com/us/en/newswire/2012/the

latest

- trends

- in

- us

- video

- gaming.html

Nint endo. 2013. “Consolidated Sales Transition by Region.” Sept. http://www.nintendo.co.jp/ir/library/historical_data/pdf/consolidated_sales_e1309.pdf

NRDC. 2 008. “Lowering the Cost of Play: Improving the Energy Efficiency of Video Game Consoles.” Ecos Consulting. http://www.nrdc.org/energy/consoles/files/consoles.pdf

. PWC. 2012.”The Evolut ion of Video Gaming and Content Consumption”. PricewaterhouseCoopers LLP. http://www.pwc.com/us/en/industry/entertainment

- media/publications/assets/pwc

- video

- gaming

and

- content

- consumption.pdf

. Sony. 2010. “PS3 System Software Update v3.40 And PlayStation Plus Available Later Today.” http://blog.eu.playstation.com/2010/06/28/ps3

- system

- software

- update

- v3

- 40

- and

- playstation

plus

- available

- later

- today/

. Sony. 2012. “PS3 System Software Update (v4.20).” http://blog.us.playstation.com/2012/06/25/ps3

- system

- software

- update

- v4

- 20/

.Fraunhofer USA Center for Sustainable Energy Systems 

### 106



## 3.14 Other Devices We estimate that other CE devices not analyzed in detail consumed about 2 8 TWh of electricity in 2013,

an amount equal to 17 percent of total residential CE AEC. Table 3

- 82 through Table 3

- 87 and Figure 3

- 59 summarize the AEC estimates and the data used to calculate the AEC of these product s. In general, these estimates have a higher degree of uncertainty than the estimates for CE produ cts analyzed in greater detail

. 37 

### The “other” category in 2013 includes several products evaluated in depth in the 2010 study that were not evaluated in furthe r detail in this study. Typically such products had moderate or lower AEC s in 2010, and our initial analysis suggested that their UEC was not likely to have changed greatly in 2013

.

Table 3

- 82 : UEC and instal led base estimates for other products

.

Product UEC [kWh /yr ] Installed Base

[millions] AEC

[TWh] AV Receiver with surround sound processor 65 48 3.1 Bluetooth Headset 5.4 67 0.4 Blu

- ray player 14 52 0.7 Boombox 25 109 2.7 Camcorder 2.3 58 0.1 Copy m achine (stand

- alone) 14 9 0.1 Cordless phone 12 128 1.5 Digital camera 0.3 156 0.05 Digital picture frame 6.5 50 0.3 DVD Player 22 142 3.1 eReader 2.7 45 0.1 External Storage Device 17 89 1.5
Fax Machine (stand

- alone) 46 10 0.5 Handheld GPS 1.3 79 0.1 Headphones 0.6 267 0.2 Home Theater in a Box (HTIB) 89 20 1.8 Internet Phone Device 36 60 2.2 Mobile (non

- smart) Phone 2.2 121 0.3 Portable DVD or Blu

- ray disc player 2.7 80 0.2 Portable Game Devices 4.1 61 0.3 Portable media/MP3 Player/CD Playe r 5.6 a 149 0.8 Portable Wireless Speaker 1.0 48 0.05 Printer + MFD (multi

- functional device) 22 93 2.0 Projector 55 4 0.2 Radio 9.2 81 0.7 Scanner (stand

- alone) 0.8 9 0.01 Soundbar 82 16 1.3 Telephone Answering Device 14 16 0.2 Video Cassette Recor der (VCR) 34 43 1.5 Total /Wt. Avg. 13 2,110 28

a UEC from Roth and McKenney ( 2007 )

.

37 In addition, the uncertainty in the estimates for “other” products can vary significantly among products.Fraunhofer USA Center for Sustainable Energy Systems 

### 107

Figure 3

- 59 : UEC, installed base, and AEC of other CE devices evaluated in less detail

. 0.8 0.3 1.0 1.3 2.7 14 2.3 0.6 2.7 55 14 4.1 2.2 6.5 5.4 46 14 9.2 5.6 82 12 34 17 89 22 36 25 65 22

0 20 40 60 80 100 Scanner (stand-alone) Digital camera Portable Wireless Speakers

Handheld GPS eReader Copy machine (stand-alone)

Camcorder Headphones Portable DVD or Blu-ray disc player Projector Telephone Answering Device Portable Game Devices Mobile (non-smart) Phone Digital picture frame Bluetooth Headset Facsimile Machine (stand-alone)

Blu-ray player Radio Portable media/MP3 Players/CD Players Soundbar Cordless phone

VCR External Storage Device Home Theater in a Box (HTIB) Printer+MFD (multi-functional device)

Internet Phone Device

Boombox AV Receiver with surround sound...

DVD Player

Unit Energy Consumption [kWh/yr] 9.0 156 48 79 45 9.0 58 267 80 4.0 16 61 121 50 67 10 52 81 149 38 16 128 43 89 20 93 60 109 48 142

0 100 200 300 Installed Base [millions] 0.01 0.0 0.05 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.3 0.3 0.3 0.4 0.5 0.7 0.7 0.8 1.1 1.3 1.5 1.5 1.5 1.8 2.0 2.2 2.7 3.1

3.1

0 1 2 3 4 Annual Energy Consumption [TWh]

### 108

Table 3

- 83 : Average power draw by mode estimates for other products

.

Product Power [W] Active/Charging Sleep/Idle Standby/Off AV Receiver with surround sound processor 52 2 1 Bluetooth Headset NA / 2.0 a 1.2 0.3 Blu

- ray player 30 16 0.5 Boombox 5.2 4.1 2.1 Camcorder NA / 9.6 0.4 0.4 Copy machine (stand

- alone) 9.6 NA 1.5 Cordless phone 1.9 NA 0.5 Digital camera NA / 4.0 NA 0.3 Digital picture frame 3.1 NA 0 DVD Player 10 0.6 0 eReader NA / 1.4 a 1.2 0.3 External Storage Devi ce 1.2 NA NA
Fax Machine (stand

- alone) 6.5 5.2 0.4 Handheld GPS NA / 1.4 a 1.2 0.3 Headphones NA / 2.4 a 1.2 0.3 Home Theater in a Box (HTIB) 37 33 1.3 Internet Phone Device 6 4 NA Mobile (non

- smart) Phone 4 2.2 0.2 Portable DVD or Blu

- ray disc playe r NA / 3.2 a 1.8 1.0 Portable Game Devices NA / 1.8 a 1.2 0.3 Portable media/MP3 Player/CD Player 5 3 1.7 Portable Wireless Speaker NA / 5.1 a 2.3 1.4 Printer+MFD (multi

- functional device) 28 4 2.4 Projector 182 10 4.6 Radio 4.3 NA 1.6 Scanner (stand

- alone) 10 NA 1.5 Soundbar 30 b 12 b 4.0 b Telephone Answering Device 2 NA NA Video Cassette Recorder (VCR) 6.6 NA 1.2

a Power draw for charging is estimated from the battery energy capacity [Wh] of a battery charger divided by charging efficiency and c harge time [hours] (DOE 2012a, DOE 2012b). DOE did not provide the charger efficiency for some consumer electronics devices (DOE 2012b); therefore, we used the average charger efficiency of the devices from the same classes defined in DOE (2012a) . For exam ple, for Handheld GPS and Headphones we used Mobile Phone charging efficiency, for Portable Wireless Speakers we used Computer Speaker charging efficiency, and for eReaders we used Tablet charging efficiency. b Because the basic functionality and total s ystem output power of soundbar system s are similar to th ose of mini shelf stereo system s , we assumed that soundbars have the same power draw values as Mini Shelf Stereo System.

### 109

Table 3

- 84 : References for po wer draw by mode estimates for other products

Product Sources AV Receiver with surround sound processor FhCSE (2011) Bluetooth Headset DOE (2012a), DOE (2012b) Blu

- ray player FhCSE (2011) Boombox Bensch et al. (2010), Fraunhofer Measurements 2014
Camc order McAllister and Farrell (2004) Copy machine (stand

- alone) LBNL (2008) Cordless phone Bensch et al. (2010) Digital camera McAllister and Farrell (2004), Foster Porter et al. (2006), Wood (2011) Digital picture frame Bensch et al. (2010) DVD Player LBNL (2013) eReader DOE (2012a), DOE (2012b) External Storage Device Bensch et al. (2010)
Fax Machine (stand

- alone) Bensch et al. (2010) Handheld GPS DOE (2012a), DOE (2012b) Wireless Headphone DOE (2012a), DOE (2012b) Home Theater in a Box (HTIB) R oth and McKenney (2007) Internet Phone Device YouSustain (2009), Ooma (2009), Roth et al. (2006) Mobile (non

- smart) Phone Bensch et al. (2010), LBNL (2008) Portable DVD or Blu

- ray disc player DOE (2012a), DOE (2012b) Portable Game Device DOE (2012a), D OE (2012b)
Port able media/MP3 Player/CD Player Bensch et al. (2010), SELINA (2010) Portable Wireless Speaker DOE (2012a), DOE (2012b) Printer+MFD (multi

- functional device) FhCSE (2011) Projector Meister et al. (2011) Radio Bensch et al. (2010)
Scann er (stand

- alone) Bensch et al. (2010) Soundbar FhCSE (2013) Telephone Answering Device Bensch et al. (2010) Video Cassette Recorder (VCR) Bensch et al. (2010)

### 110

Table 3

- 85 : Annual usage by mode estimat es for other products

.
Product Active/Charging Sleep/Idle Standby/Off AV Receiver with surround sound processor 950 7,610 200 Bluetooth Headset 314 b 3,217 c 0 d /4,015 e
Blu

- ray player 300 30 8,430 Boombox 1,971 NA 6,789 Camcorder NA NA NA Copy machine (stand

- alone) 50 a NA 8,710 a Cordless phone 7,044 NA 1,716 Digital camera 13 NA 8,752 Digital picture frame 4,781 NA 3,979 DVD Player 2,044 1,861 4,855 eReader 526 b 752 c 548 d /6,935 e External Storage Device 8,760 NA NA Fax Machine (stand

- alone) 1 46 NA 8,614 Handheld GPS 73 b 110 c 0 d /8,578 e Headphone 146 b 219 c 0 d /4,015 e Home Theater in a Box (HTIB) 1,580 730 6,450 Internet Phone Device 365 8,395 0 Mobile (non

- smart) Phone 110 NA 8,650 Portable DVD or Blu

- ray disc player 58 b 1,402 c 0 d /7,30 0 e
Portable Game Devices 204 b 2,738 c 3,103 d /2,920 e Portable media/MP3 Player/CD Player 657 NA 8,103 Portable Wireless Speaker 146 b 219 c 0 d /4,015 e Printer+MFD (multi

- functional device) 103 1,212 7,445 Projector 694 613 7,453 Radio 620 NA 8,140 S canner (stand

- alone) 146 NA 8,614 Soundbar 1,580 f 730 f 6,450 f Telephone Answering Device 8,760 NA NA Video Cassette Recorder (VCR) 1,497 NA 7,263

a Notably high uncertainty for this value. b Hours/year the device spends charging. Calculated as a pr oduct of charges/year and charge time (DOE 2012a).

c Hours/year the device spends in maintenance state, i.e. the device is fully charged but still connected to its charger (DOE 2012a). d Time in hours/year the device charger spends plugged into an electr ical socket but without any device connected to it (“No Battery” in DOE spreadsheet 2012a).

e Time in hours/year the device charger spends unplugged (DOE 2012a). f Usage in all operational modes for Soundbar is taken the same as for HTiB because of a si milar usage pattern for these audio systems (see HTiB usage).

### 111

Table 3

- 86 : References for annual usage by mode estimates for other products

.
Product Sources AV Receiver with surround sound processor FhCSE ( 2011) Bluetooth Headset DOE (2012a), DOE (2012b) Blu

- ray player FhCSE (2011) Boombox Bensch et al. (2010) Camcorder NA Copy machine (stand

- alone) FhCSE (2011) Cordless phone Bensch et al. (2010) Digital camera Roth and McKenney(2007) Digital pictur e frame Bensch et al. (2010) DVD Player LBNL (2013) eReader DOE (2012a), DOE (2012b) External Storage Device Bensch et al. (2010)
Fax Machine (stand

- alone) Bensch et al. (2010) Handheld GPS DOE (2012a) , DOE (2012b) Wireless Headphone DOE (2012a) , D OE (2012b) Home Theater in a Box (HTIB) Roth and McKenney (2007) Internet Phone Device Roth et al. (2006) Mobile (non

- smart) Phone Bensch et al. (2010) Portable DVD or Blu

- ray disc player DOE (2012a) , DOE (2012b) Portable Game Devices DOE (2012a) , D OE (2012b) Portable media/MP3 Player/CD Player Bensch et al. (2010) for CD players Portable Wireless Speaker DOE (2012a) , DOE (2012b) Printer+MFD (multi

- functional device) FhCSE (2011) Projector FhCSE (2011) Radio Bensch et al. (2010) Scanner (stan d

- alone) Bensch et al. (2010) Soundbar Assumed the same as HTIB usage Telephone Answering Device Bensch et al. (2010) Video Cassette Recorder (VCR) Bensch et al. (2010)

### 112

Table 3

- 87 : References for instal led base estimates for other products

.
Product Sources AV Receiver with surround sound processor CEA (2013a) Bluetooth Headset CEA (2013a) Blu

- ray player CEA (2013a) Boombox Roth and McKenney (2007), CEA (2013b) Camcorder CEA (2013a) Copy machine (st and

- alone) FhCSE (2011) Cordless phone Scaled 2010 estimate (FhCSE 2011) based on ratio of landline subscriptions in 2010 and 2013 (Marketingcharts 2012, Axvoice 2012 ) Digital camera CEA (2013a) Digital picture frame CEA (2010), CEA (2013b) DVD Player CEA (2013a) eReader CEA (2013a) External Storage Device CEA (2013a)
Fax Machine (stand

- alone) DOE/EIA RECS (2009) Handheld GPS CEA (2013a) Wireless Headphone CEA (2013a) Home Theater in a Box (HTIB) Koenig (2013)
Internet Phone Device FCC (2011), C EA (2013b) Mobile (non

- smart) Phone CEA (2013a) Portable DVD or Blu

- ray disc player CEA (2013a) Portable Game Device CEA (2013a) Portable Headset Audio CEA (2010), CEA (2013b) Portable media/MP3 Player/CD Player CEA (2013a) Portable Wireless Speaker CEA (2013a) Printer+MFD (multi

- functional device) CEA (2013a) Projector Extrapolated to U.S. from German data (Statistica 2011) Radio Bensch et al. (2010) Scanner (stand

- alone) RASS (2009) Soundbar CEA (2013a) Telephone Answering Device DOE/EIA RECS (2009), CEA (2013b) Video Cassette Recorder (VCR) Bensch et al. (2010), CEA (2013b)



### 3.14.1 References Axvoice. 2012. “US telecom industry from 2010 to 2015.” May. http://blog.axvoice.com/us

- telecom

industry

- from

- 2010

- to

- 2015

- a

- research

- by

- axvoice/

. Bensch, I., S. Pigg, K . Koski and R. Belshe. 2010 . “Electricity Savings Opportunities for Home Electronics and Other Plug

- In Devices in Minnesota Homes

– A technica l and behavioral field assessment.” Final Report by the Energy Center of Wisconsin, ECW R eport 257

- 1 . May. http://www.sta te.mn.us/mn/externalDocs/Commerce/CARD_Plugging_into_Savings_Study_0527100 14507_MN_Home_Elect_Devices.pdf

. CEA

. 2010

. “12 th 

### Annual hou sehold CE Ownership and Market P otential.” CEA Market Research Report

. Consumer Electronics Association

. May

. CEA. 2013 a. “15 th 

### Annual CE Ownership and Market Potential Study.” CEA Market Research Report, April, 2013. Consumer Electronics Association.
CEA. 2013b. “U.S. Consumer Electronics Sales & Forecasts 2009

- 2014.” CEA Market Research Report, July, 2013. Consumer Elect ronics Association

. DOE. 2012a. “ Rulemaking for Battery Chargers and External Power Supplies Energy Conservation Standard

. Energy Use Analysis Spreadsheet .” Feb. 17, 2012. http://www.regulations.gov/#!documentDetail;D=EERE

- 2008

- BT

- STD

- 0005

- 0084

.

### 113

DOE. 2012b. “ Test Results for External Power Supply Energy Conservation Standards Preliminary Analysis

. http://www.regulations.gov/#!documentDetail;D=EERE

- 2008

- BT

- STD

- 0005

- 0080

. Apr. DOE/EIA RECS. 2009. “Residential Energy Consumption Survey (RECS)

– Computers & other electronics: Table HC5.1 Computers and Other Electronics in U. S

. Homes, By Housing Unit Type, 2009 .” http://www.eia.gov/consumption/residential/data/2009/#undefined

. FCC. 2011. “Local telephone competition: status as of Jun. 30, 2010 .” Federal Communications
Commission. Mar. http://hraunfoss.fcc.gov/edocs_public/attachmatch/DOC

- 305297A1.pdf

. FhCSE. Urban, Bryan, K urt Roth, and Verena Tiefenbeck. 2011. “Energy C onsumption of C onsumer E lectronics in U.S. H omes in 2010.” Final Report to the Consumer Electronics Association. http://w ww.ce.org/CorporateSite/media/Government

- Media/Green/Energy

- Consumption

- of

- CE

- in

U

- S

- Homes

- in

- 2010.pdf . Dec.

Foster Porter, S., L

. Moorefield, P

. May‐Ostendorp

. 2006

. “ Final Field Research Report .” Final Field Research Report by Ecos Consulting to the Cal ifornia Energy Commission

. 31 Oct. Koenig, S. 2013. Personal Communication. Consumer Electronics Association, Director of Industry Analysis . Oct.
LBNL 2008. “Low

- Power Mode Energy Consumption in California Homes.” Pier Final Project Report prepared by Lawr ence Berkeley National Laboratory for California Energy Commission Public Interest Energy Research Program. Sept. http://www.energy.ca.gov/2008publications/CEC

- 5 00

- 2008

- 035/CEC

- 500

- 2008

- 035.PDF

. LBNL. 2013. “Field data collection of miscellaneous electrical loads in Northern California: initial results.” Lawrence Berkeley National Laboratory Final Report, LBNL

- 6115E. Jul. Marketingcharts. 2012. “Landline Phone P enetration Dwindles as Cell

- Only Households Grow.” Jul. http://www.marketingcharts.com/wp/traditional/landline

- phone

- penetr ation

- dwindles

- as

- cell

- only

households

- grow

- 22577/

. McAllister, J. and A. Farrell. 2004. “Power in a Portable World: Usage Patterns and Efficiency Opportunities for Consumer Battery Chargers”, Proc

. ACEEE Summer Study on Energy Efficiency in Buildings , 22

- 27 August, Pacific Grove, CA.
Meister, B.C., C

. Scruton,V

. Lew, L

. ten Hope and M

. Jones

. 2011 . “Office Plug Load Field Monitoring Report.” Final Field Project Report b y Ecos Consulting to the Califo rnia Energy Commission . Apr. http://www.energy.ca.gov/2011publications/CEC

- 500

- 2011

- 010/CEC

- 500

- 2011

- 010.pdf

. RASS

. 2009

. “Massachusetts Residential Appliance Saturation Surv ey (RASS).” Prepared by Opinion Dynamics Corporation for Cape Light, National Grid, Nstar Electric Unitil, Western Massachusetts Electric Company . Apr. http://www.env.state.ma.us/dpu/docs/electric/09

- 64/12409nstrd 2af.pdf

. Roth, K. and K

. McKenney . 2007. “Energy Consumption by Consuer Electronics (CE) in U.S. Residences.” Final Report by TIAX LLC to the Consumer Electronics Association (CEA). Dec. http://www.ce.org/pdf/ Energy%20Consumption%20by%20CE%20in%20U.S.%20Residences%20%28January%202007%29.pdf Roth, K., R. Ponoum, and F. Goldstein. 2006. “U.S. Residential Information Technology Energy Consumption in 2005 and 2010.” Final Report by TIAX LLC to the U.S. Department of Energy, Building Technology Program. Mar.

SELINA

. 2010

. “ S tandby and Off

- mode E nergy L osses I n N ew A ppliances Measured in Shops: Consumption Monitoring Campaign of Standby a nd Off

- Mode Energy Losses in New E quipments .” 30
Jun. http://www.selina

- project.eu/files/ Measurements%20of%20standby%20energy% 20losses %20in%20new%20equipment.pdf

.

### 114

Statistica

. 2011

. “ Beamer, Projektoren im Haushalt: Anzahl der Personen, bei denen ein Beamer bzw. Projektor zur Darstellung von Fernseh

- oder Computerbildern im Haushaltvorhanden ist, von 2008 bis 2010 (in Millionen ).” Available (in German) at : http://de.statista.com/statistik/daten/studie/169550/ umfrage/beamer

- projektoren

- im

- haushalt/

. Wood, R.W. 2011. P ersonal Communication. Eastman Kodak Company. Sept.

### 115



# 4 Conclusions

We used a bottom

- up approach to characterize U.S

. residential consumer electronics (CE) energy consumption in 2013

. Our effort focused on the 17 priority products listed in Table 4

- 1

. In addition, we developed preliminary estimates for 29 other CE categories

. For each CE category, we used a range of sources to develop estimates for the installed base and average power draw and annual usage by mode

.

Table 4

- 1 : Consumer e lectronics analyzed in further detail

.

Audio

- Visual Equipment Computers & Peripherals
Home Audio Speaker Dock Compact Stereo System Televisions Video Game Consoles Set Top Boxes Cable Standalone Satelli te Telco Desktop PC Portable PC Computer Speakers Computer Monitor Smart Phone Tablet Computer Networking Equipment Integrated Access Device Modem
Router



### We estimate that residen tial CE consumed about 1 69 TWh of electricity in 2013 , an amount equal to 12 % of residential electricity consumption and 8 .4 % of residenti al primary 38 

### energy consumption
, respective ly (see Figure 4

- 1 and Figure 4

- 2 ; DOE/EIA 2014a,b, DOE 2012 39 

### )

. For comparison, DOE (2012)

est imates that “computers” and “electronics” accounted for just under 15 percent of residential electricity consumption in 2010.

Figure 4

- 1 : Residential electricity consumption in 2013 by major end uses (DO E 2 012 , Current Study)

.

38 Residential primary energy is the total energy content of the fuel required to meet all end uses. Primary energy includes fuel s consumed at the home, e.g., natural gas and oil for space and water heating, and fuel consumed at the power plant to generate electricity and to overcome transmission and distribution losses

. On average, a power pla nt must consume an average of 3 .1 kWh of primary energy to deliver 1kWh to a building (DOE 2012).

39 Breakdown of electricity consumption based on DOE 2012, percentage of residential primary energy consumption from DOE/EIA 201 4a,b. 17% 2.9% 6.7% 8.8% 9.4% 9.6% 12%

12% 21%

0% 5% 10% 15% 20% 25% Other (non-CE) Cooking Wet Cleaning Space Heating Refrigeration Water Heating Consumer Electronics

Lighting Space Cooling

Percentage of Total Residential Electricity Consumption in 2013

### 116

Figure 4

- 2 : Residential primary energy consumption in 201 3 by major end uses (DOE 2012 , Current Study)

.



### As with the prior two residential CE energy consumption studies (Roth and McKenney 20 07, FhCSE 2011) , three product c ategories accounted for a majority of residential CE AEC, televisions (30%), set

- top boxes (18%), and computers ( 13%; see Figure 4

- 3 ).

Figure 4

- 3 : Residential CE electricity consu mption by category

. 13% 3.2% 4.9% 6.5% 8.4%

8.4% 13% 15% 28%

0% 5% 10% 15% 20% 25% 30% Other (non-CE) Cooking Wet Cleaning Refrigeration Consumer Electronics

Lighting Water Heating Space Cooling Space Heating

17% 0.4% 0.4% 1% 1% 2% 2% 2% 2% 3% 3% 3% 3% 6%

7% 9% 9% 30%

0% 10% 20% 30% Other CE Devices

Tablet Smart Phone Speaker Dock STB - Standalone Computer Speaker

Modem STB - Telco Internet Access Device

Portable PC Compact Stereo System Router and other Computer Monitor STB - Satellite Video Game Console STB - Cable Desktop PC Television

Percentage of Total Residential CE Energy Consumption

### 117

The unit electricity consumption (UEC) of the categories studied in more detail varies greatly among categories (see Figure 4

- 4 ).

Figure 4

- 4 : Unit electricity consumption for the CE categories evaluated in detail

. 

### As in prior studies, active modes accounted for a large majority of residential CE AEC (70%; see Figure

4

- 5 ), although the UEC breakdown by mode varied significantly among ca tegories (see Figure 4

- 6 ).

Figure 4

- 5 : AEC by operational mode for the categories evaluated in detail

. 12 4.5 6.1 19 42

45 53 55 58 59 62 75 88 106 112 128 166 186

0 50 100 150 200 Other CE Devices Smart Phone Tablet Speaker Dock Computer Speaker STB - Standalone Portable PC Modem Computer Monitor Router and other Internet Access Device Compact Stereo System Video Game Console

STB - Telco STB - Satellite STB - Cable Television Desktop PC

Unit Energy Consumption [kWh/year]



### Active 70% Idle 12% Sleep 11% Off

7%

### 118

Figure 4

- 6 : Breakdown of U EC by operational modes for the categories evaluated in detail

.


## 4.1 Key Trends Although the installed base of CE in homes increased to 3.8 billion devices in 2013 from 2.9 billion in 2010, o ur estimate for residential CE electricity consumption is 12 percent l ower than that for 2010 (Urban et al. 2011). T o a large extent, t his decrease reflects a few key trends for televisions and computers; together, these two categories account for about 43 percent of residential CE AEC

.

4.1.1 Televisions
Since the first evaluation of CE energy consumption (for 2006; Roth and McKenney 2007), televisions have always accounted for the largest portion of CE energy consumption. For the first time in over a decade, the number of plugged

- in TVs has decreased significantly, with a shift fr om CRT to LCD TVs contributing to more than a 20% decline in their estimated AEC from 2010 to 2013

. Around 90 % of the
40 mil lion TVs sold per year are flat

- panel LCD displays (CEA 2013b) , and these have overtaken CRTs as the most prevalent display technolo gy deployed in homes. Our best understanding of this installed base decrease of about 50 million TVs plugged in within the last month is that a large portion of older, less

efficient CRT display s have been removed from service

. Since our only indication of this change come from our phone survey, there remains some uncertainty in its precise magnitude

.

Total a ctive TV usage has remained fairly consistent over time , while per

- TV on

- time has increased
somewhat from 2010. Active

- mode power draw has continued t o decrease (from an average of 104 W in 2010 to 90 W) , even while average screen size continues to increase (34 inches in 2013, up from 29 0% 20% 40% 60% 80% 100% Video Game Console Speaker Dock Computer Speaker Desktop PC STB - Satellite Compact Stereo System

STB - Cable STB - Telco Smart Phone Portable PC STB - Standalone

Tablet Computer Monitor

TVs Internet Access Device Router and other Modem Active Idle Sleep Off/Standby

### 119

inches in 2010 [Urban et al. 2011] and 26 inches in 2006 [Roth and McKenney [ 2007 ] ) , owing to the greater efficiency of newer displays.

4.1.2 Computers We evaluated three computer types as well as smart phones in more depth. Overall, the estimated total AEC of all computers has decreased by 25 percent since 2010. A migration of the installed base to much less energy

- intensive tablet computers (i.e., about nine

- fold less than portable ; see Figure 4

- 4 ) and application of more refined methods to evaluate computer usage are the main drivers for this decrease.

The plugged

- in installed base of both desktop and portable computer decreased from 2010 to 2013 (desktop: 101 to 88 million, portable: 132 to 93 million. We believe that this is due to the 25

- fold increase in the ownership of tablets, from 4 million (Urban et al. 2011) to 100 million (CEA 2013a).

Inc luding tablet computers, the installed base of all com puters categories in 2013 was 19 percent higher
than in 2010.

We also estimated lower annual hours spent in active mode for both desktop (13%) and portable (36%) computers in 2013 than in 2010. This pr imarily reflects refinements in the CE Usage Survey and models that we think improve the accuracy of our estimates for time in operational modes for desktop PCs. Specifically, the current approach increases the precision the survey questions posed by asking about three times of day (morning, afternoon, and evening). This provides a richer representation of usage throughout the whole day than in Urban et al. (2011). In addition, we think that breaking the day into more discrete time periods increases t he accuracy of peoples’ responses for total computer usage.

One consequence of the decreased installed base of desktop and portable computers is a 27 percent decrease in the installed base of monitors. In addition, our estimate of active

- mode usage (tied t o the enhanced computer usage models described above) decreased by 36 percent. That, combined with a decrease in the average power draw in all modes (due to the rise of LED backlit monitors since 2010; DisplaySearch 2014) resulted in a 40 percent decrease in UEC. Taken all together, the estim ated monitor AEC decreased by 54 percent.

### 120



# References

CEA

. 2010a

. “12th Annual household CE Ownership and Market Potential.” CEA Market Research Report

. Consumer Electronics Association

. May

. CEA

. 2010b

. “U.S

. Consum er Electronics Sales & Forecasts 2006

- 2011 .” CEA Market Research Report

. Jul

. CEA. 2013a. “15th Annual CE Ownership and Market Potential Study.” CEA Market Research Report, April, 2013. Consumer Electronics Association.
CEA. 2013b. “U.S. Consumer Electroni cs Sales & Forecasts 2009

- 2014.” CEA Market Research Report, July, 2013. Consumer Electronics Association. DisplaySearch. 2014. “Quarterly Desktop Monitor Shipment and Forecast Report, 2011

- 13”.

DOE

. 2012

. “2011 Buildings Energy Data Book .” Prepared for th e Building Technologies Program, Energy Efficiency and Renewable Energy, U.S

. Department of Energy by D&R International, Ltd

. Mar

. DOE/EIA. 2014a. “ Electric Power Monthly : Table 5.1. Retail Sales of El ectricity to Ultimate Customers”. U.S. Department of E nergy, Energy Information Administration. Feb. 21

. DOE/EIA. 2014b. Annual Energy Outlook 2014 Early Release: Energy Consumption by Sector and Source

. U.S. Department of Energy, Energy Information Administration. Retrieved Mar. 6.
FhCSE. Urban, Bryan, K urt Roth, and Verena Tiefenbeck. 2011. “Energy C onsumption of C onsumer E lectronics in U.S. H omes in 2010.” Final Report to the Consumer Electronics Association. http://www.ce.org/CorporateSite/media/Government

- Media/Green/Energy

- Consumption

- of

- CE

- in

U

- S

- Homes

- in

- 2010.pdf . Dec.

Kawamoto, K., J

. Koomey, B

. Nordman, R

. Brown, M.A

. Piette, M

. Ting, and A

. Meier

. 2001

. “Electricity used by o ffice equipment and network equipment in the U.S.: Detailed report and appendices .” Lawrence Berkeley National Laboratory Final Report, LBNL

- 45917

. Feb

. Roth, K., F

. Goldstein, and J

. Kleinman

. 2002

. ”Energy Consumption by Office and Telecommunications Equ ipment in Commercial Buildings

- Volume I: Energy Consumption Baseline .” Final Report by Arthur
D

. Little, Inc

. to Office of Building Equipment (DOE)

. Jan

. Roth, K., R

. Ponoum, F

. Goldstein

. 2006

. “U

. S

. residential information technology energy consumption in 2005 and 2010.” Final Report by TIAX LLC to the U.S

. Department of Energy, Building Technology Program

. Mar

. Roth, K

. and K

. McKenney

. 2007

. “Energy Consumption by Consuer Electronics (CE) in U.S

. Residences .” Final Report by TIAX LLC to the Consumer E lectronics Association (CEA)

. Dec

. http://www.ce.org/pdf/Energy%20Consumption%20by%20CE%20in%20U.S.%20Residences%20%28J anuary%202007%29. pdf

. Roth, K., K

. McKenney, R

. Ponoum, and C

. Paetsch

. 2008

. “Residential Miscellaneous Electric Loads: Energy Consumption Characterization and Savings Potential in 2006 and Scenario

- based Projections for 2020 .” Final Report by TIAX LLC to U.S

. Departmen t of Energy.

### 121



# Append ix A

– CE Usage Survey s As part of this study, the CEA funded phone survey s that asked respondents questions about CE installed
in their household and h ow they are used

. The questions ultimately posed were developed by
Fraunhofer CSE in close consultation with the CEA Market Research Team, which regularly performs surveys on a variety of topics

. CEA is a member of the Marketing Research Association (MRA) and adheres to the MRA’s Code of Marketing Research Standards. The CEA employed the services of Opinion Research Corporation (ORC) to conduct telephone interviewing. The telephone interviewing employed industry standard random

- digit dialing and computer assisted telephone interviewing (CATI).

A total of five surveys were administered vi a dual

- frame telephone interview to a random national sample of U.S. adults. Specific fielding dates and sample sizes are:

 Video Game Consoles

- February 27

- March 2, 2014. 654 interviews were from the landline sample and 350 interviews from the cell phone sample.

 Home Audio Devices

- December 19

- 22, 2013. 679 interviews were from the landline sample and 352 interviews from the cell phone sample.

 Desktop and Portable Computers

- December 19

- 22, 2013. 679 interviews were from the landline sample and 352 i nterviews from the cell phone sample.

 Mobile Devices

– Smart phones and Tablets

- December 19

- 23, 2013. 661 interviews were from the landline sample and 350 interviews from the cell phone sample.

 Televisions

- November 14

- 17, 2013. 654 interviews wer e from the landline sample and 350 interviews from the cell phone sample.

As is common practice i n survey research, the data were weighted to reflect the known demographics of the population under study. In this survey, weights were applied to cases bas ed on gender, age, race and geo graphic region. As a result, the s e data can be generalized to the entire U.S. adult population. All findings presented in this report derived from the surveys were based on weighted data.

Subsequently, we processed the respo nses received in category

- specific models to estimate the installed base of CE and CE usage

. The category

- specific models are discussed in their respective sections, with the more involved computer and monitor usage models described in Appendix B.

The com plete phone survey script s fielded follow

. 

## A.1 Personal Computers (Desktops and Portables)

On another subject...

C1 Thinking about the following COMPUTER products you may have in your home, please indicate how many were

PLUGGED INTO an electrical outlet in Y OUR HOME at some point during the PAST MONTH. If you do not have this product, please tell me.

(RECORD A NUMBER FOR EACH. RANGE IS 0

- 10, DON’T KNOW/NOT SURE, DO NOT HAVE THIS PRODUCT)

A. Personal desktop computer
B. Personal portable computer, such as notebooks , laptops or netbook computers

### 122 IF ANY COMPUTER WAS PLUGGED IN, C1A OR B (1

- 10), CONTINUE.

ALL OTHERS SKIP TO NEXT SECTION.

IF C1A (1

- 10), ASK ‘A’ (PRIMARY DESKTOP) SERIES.

IF C1A (2

- 10), ASK ‘B’ (SECONDARY DESKTOP) SERIES.

IF C1B (1

- 10), ASK ‘C’ (PRIMARY P ORTABLE) SERIES.

IF C1B (2

- 10), ASK ‘D’ (SECONDARY PORTABLE) SERIES.

C2

- C5 PROGRAMMING NOTE:

ASK ‘A’ (PRIMARY DESKTOP) SERIES BEFORE MOVING ON TO ‘B’ (SECONDARY DESKTOP) SERIES, ETC.

[DISPLAY IF C1A (1

- 10)]

The next set of questions are about DESKTOP COMP UTERS in your household, including those used in home offices [DISPLAY IF C1A (2

- 20)] (starting with the PRIMARY or MOST USED DESKTOP COMPUTER). [DISPLAY IF C1A (2

- 10) BEFORE ‘B’ SERIES]

Now, for the next set of questions, please think about the SECONDARY DESKTOP COMPUTER in your household.

[DISPLAY IF C1B (1

- 10) BEFORE ‘C’ SERIES]

The next set of questions are related to PORTABLE COMPUTERS, such as notebooks, laptops or netbook computers in your household [DISPLAY IF C1B (2

- 20)] (starting with the PRIMARY or MOST USED PORTABLE COMPUTER).

[DISPLAY IF C1B (2

- 10) BEFORE ‘D’ SERIES]

Now, for the next set of questions, please think about the SECONDARY PORTABLE COMPUTER, such as notebooks, laptops or netbook computers in your household.

C2 I’d like to ask you abo ut how long the [INSERT] computer is used by YOU OR OTHERS in your household. Please consider all activities such as email, searching the Internet, watching videos, gaming, playing music, etc. Also please include time when the computer is doing any of th ese activities even if no one is at the computer.

How much time was the [INSERT] computer used YESTERDAY during the following times? Please answer in hours and
minutes.

(RECORD A NUMBER. RANGE FOR A IS 0

- 24, DON’T KNOW; RANGE FOR B IS 0

- 59, DON’T KNOW. SEPARATE PUNCH FOR EACH FOR ‘NOT USED’)

01 During the MORNING hours, before 12:00 noon 02 During the AFTERNOON hours, between 12:00 and 5:00 pm 03 During the EVENING hours, between 5:00 pm and when you go to sleep at night 04 In ONE SESSION OR SITTING of use, BEFORE the EVENING 05 In ONE SESSION OR SITTING of use, in the EVENING 06 Over the whole day

A. HOURS
B. MINUTES

a. Primary desktop b. Secondary desktop

c. Primary portable d. Secondary portable

### 123

C3 After you or someone in your household finishes a session or sitting, that is, one instan ce of use, how often is the

[INSERT] computer...

(READ ENTIRE LIST BEFORE RECORDING ONE ANSWER)

01 Always
02 Often
03 About half of the time
04 Occasionally
05 Or, never 99 DON’T KNOW

A. Left ON, during the DAYTIME
B. Put into STANDBY or SLEEP, during the DAYTIME
C. TURNED OFF or SHUT DOWN, during the DAYTIME
D. TURNED OFF or SHUT DOWN, OVERNIGHT

a. Primary desktop b. Secondary desktop

c. Primary portable d. Secondary portable

C4 Think of a time you were the FIRST person of the day to use the [INSERT] computer. What did you do to begin using it ?

(READ LIST UNTIL STOPPED. RECORD ONE ANSWER)

01 The computer and monitor were already ON showing the previous screen image 02 The computer was already ON, but the monitor was off. You pressed a key or moved the mouse, and

INSTANTLY the computer was READY 03 Y ou [DISPLAY FOR C

- D SERIES ONLY] (opened the computer lid,) pressed a key, moved the mouse or

pressed a POWER button, and after a FEW SECONDS the computer was ready to use 04 You pressed the POWER BUTTON on the computer, and WAITED more than 15 seconds until it was ready to

use 99 DON’T KNOW

a. Primary desktop b. Secondary desktop

c. Primary portable d. Secondary portable

C5 How many of the following devices, if any, does the [INSERT] computer have connected to it?

(RECORD A NUMBER. RANGE IS 0

- 99, DON’T KNOW)

A. LCD f lat monitors including LED. DO NOT COUNT displays that are built in to the computer, such as the

screen on a laptop, netbook or all

- in

- one desktop
B. CRT or Tube monitors
C. Computer speaker systems without Subwoofer
D. Computer speaker systems with Subwoofer

a. Prim ary desktop b. Secondary desktop

c. Primary portable d. Secondary portable



## A.2 Home Audio

A1 For each of the following AUDIO products, you may have in your home, please indicate how many were PLUGGED

INTO an electrical outlet in YOUR HOME at some point in the PAST MONTH. If you do not have this product, please tell me.

### 124 (RECORD A NUMBER FOR EACH. RANGE IS 0

- 10, DO NOT HAVE THIS PRODUCT, DON’T KNOW/NOT SURE)

A. Speaker dock that has a plug

- in connection for an MP3 player, smartphone or tablet
B. Shelf stereo system, also called Mini or Compact stereo systems

IF HAVE ANY SPEAKER DOCKS, A1A (1

- 10), CONTINUE.

ALL OTHERS SKIP TO INSTRUCTIONS BEFORE A4

Now, please answer the next few questions about a speaker dock that has a plug

- in connection that you use with your MP3 playe r, smartphone or tablet. [DISPLAY IF A1A (2

- 10)] (Please answer thinking about your PRIMARY speaker dock, meaning the one you or your household uses MOST OFTEN.)

A2 About how long did you or others in your household use your PRIMARY speaker dock to listen to any audio YESTERDAY?

Please give your answer in hours and minutes.

(RECORD A NUMBER FOR EACH. RANGE FOR A IS 0

- 24, DON’T KNOW, RANGE FOR B IS 0

- 59, DON’T KNOW)

A. Hours
B. Minutes

A3 After you finished using your speaker dock YESTERDAY, how did you tur n it OFF? If you did not use your speaker dock yesterday, please answer about the LAST DAY YOU USED IT.

(READ LIST UNTIL STOPPED. RECORD ONE ANSWER)

01 The power switch or remote control
02 It turns off automatically if you leave it for more than 20 minutes without any audio playing
03 You did not turn it off, you left it on
04 Or, there is no power switch on the speaker dock
99 DON’T KNOW

IF HAVE ANY SHELF STEREO SYSTEMS, A1B (1

- 10), CONTINUE.

ALL OTHERS SKIP TO NEXT SECTION

Now, please answer the next few quest ions about a shelf stereo system, also called a Mini or Compact stereo system. [DISPLAY IF A1B (2

- 10)] (Please answer thinking about your PRIMARY shelf stereo system, meaning the one you or your household uses MOST OFTEN.)

A4 About how long did you or oth ers in your household use your PRIMARY shelf stereo system to listen to any audio YESTERDAY?

Please give your answer in hours and minutes.

(RECORD A NUMBER FOR EACH. RANGE FOR A IS 0

- 24, DON’T KNOW, RANGE FOR B IS 0

- 59, DON’T KNOW)

A. Hours
B. Minutes

A5 A fter you finished using your shelf stereo system YESTERDAY, how did you turn it OFF? If you did not use your shelf

stereo system yesterday please answer about the LAST DAY YOU USED IT.

(READ LIST UNTIL STOPPED. RECORD ONE ANSWER)

01 The power switch or re mote control

### 125 02 It turns off automatically if you leave it for more than 15 minutes without any audio playing
03 You did not turn it off, you left it on
04 Or, there is no power switch on the stereo system
99 DON’T KNOW



## A. 3 Mobile Devices (Smartphones and Tablets)

On another subject...

M1 Thinking about all the devices you may have in your home, how many of each of the following did YOU USE in the PAST MONTH? If you do not have this product, please tell me.

(RECORD A NUMBER FOR EACH. RANGE IS 0

- 20, DON’T KNOW/NOT SU RE, DO NOT HAVE THIS PRODUCT)

A. Smartphones, such as an iPhone, Android, Windows Phone, etc.
B. Tablet computers, such as an iPad, Kindle Fire, Galaxy, etc.

IF USED EITHER DEVICE, M1A OR M1B (1

- 20), CONTINUE WITH INSTRUCTIONS BELOW.

ALL OTHERS SKIP TO NEXT SEC TION

ASK ‘B’ (PRIMARY TABLET) SERIES IF M1B (1

- 20)

ASK M2C (SECONDARY TABLET) IF M1B (2

- 20)

M2

- M6 PROGRAMMING NOTE:

ASK ‘A’ (SMARTPHONE) SERIES BEFORE MOVING ON TO ‘B’ (PRIMARY TABLET) SERIES.

ASK M2C (SECONDARY TABLET) AFTER M2A/B SERIES, BUT NOT FOR M3

- M6

[DISPLAY IF M1A (1

- 20)]

For the next few questions, please think about the smartphone that YOU USE MOST OFTEN.

[DISPLAY IF M1B (1

- 20) BEFORE ‘B’ SERIES]

Now, for the next set of questions, please think about the primary tablet that YOU USE MOST OFTEN.

[ DISPLAY IF M1B (2

- 20) BEFORE M2C]

For the next question, please think about the secondary tablet that YOU USE SECOND MOST OFTEN.

M2 How much time did you or someone else in your household USE your [INSERT] YESTERDAY?

(RECORD A NUMBER. RANGE FOR A IS 0

- 2 4, DON’T KNOW; RANGE FOR B IS 0

- 59, DON’T KNOW)

A. HOURS
B. MINUTES

a. Smartphone b. Primary tablet

c. Secondary tablet

M3 How many TIMES LAST WEEK did you or someone else in your household plug in and CHARGE your [INSERT]? Please include any time charging at home or an ywhere else. Also, please include any times you have charged more than once in a day.

(RECORD A NUMBER. RANGE IS 0

- 70, DON’T KNOW)

### 126 a. Smartphone b. Primary tablet

M4 Thinking about the LAST TIME YOU charged your [INSERT], what was the battery level...

[RECORD ON E ANSWER]

01 Fully charged 02 75% to 99% charged 03 50% to 74% charged 04 25% to 49% charged 05 1% to 24% charged 06 Or, fully drained
99 DON’T KNOW

A. Just BEFORE you charged it
B. Just AFTER you charged it

a. Smartphone b. Primary tablet

M5 Now, thinking only about YESTERDAY, or the LAST DAY YOU charged your [INSERT] before today, for how much time was your [INSERT] plugged in for charging through the following power sources? Please answer in hours and minutes.

(RECORD A NUMBER. RANGE FOR A IS 0

- 24, DON’T KNOW; RANGE FOR B IS 0

- 59, DON’T KNOW)

01 Using the original brand name charger that came with your device
02 Using a replacement or aftermarket charger, a car charger, or a USB port charging from a computer, speaker

system, etc.

A. HOURS
B. MINUTES

a. Smartphone b. Primary tablet
[ASK IF M5 (01

- 02) A (1

- 24) OR M5(01

- 02)B (1

- 59)]

M6 Again, thinking only about YESTERDAY, or the LAST DAY YOU charged your [INSERT], how much time was your

[INSERT]’s CHARGER PLUGGED INTO THE WALL, regardless of whether the device was connected to the charger or not? Pleas e answer in hours and minutes.

(RECORD A NUMBER. RANGE FOR A IS 0

- 24, DON’T KNOW; RANGE FOR B IS 0

- 59, DON’T KNOW)

A. HOURS
B. MINUTES

a. Smartphone b. Primary tablet



## A.4 Televisions How many of each of the following devices were PLUGGED INTO an electrical outlet in your home at some point during the PAST MONTH?

(RECORD NUMBER FOR EACH. RANGE IS 0

- 20, DON’T KNOW/NOT SURE)

[DO NOT RANDOMIZE ITEMS]

01 Televisions
02 Amplifier or home speaker systems, such as external speakers for a TV or a stereo system. Do not include

portable stereos or speakers used with computers.

### 127 03 Digital media streaming device which streams video content from the Internet or networked computer, such as Apple TV, Roku or Chromecast. Do not count Blu

- Ray or DVD players that have this feature.

[ASK IF V1A (1

- 20)]

V2 Please think about all the different TVs in your household and the ways in which you receive television programming

such as cable, satellite, fiber to the home, Internet or an antenna that may mount on your roof or an antenna that sits

on or near the TV.

In which of the following ways, if any, do you receive television programming on the TVs in your home?

(READ LIST. RECORD AS MANY AS APPLY. WAIT FOR YES OR NO FOR EACH. IF YES TO MORE THAN ONE OF RESPONSES
1

- 3, SAY: ‘Please confirm tha t you subscribe to more than one service’)

[DO NOT RANDOMIZE ITEMS]

01 Cable TV service 02 Satellite TV service 03 Fiber to the home TV service, such as Verizon Fios or AT&T U

- verse 04 Antenna TV service 05 Internet TV service 98 I DON’T RECEIVE PROGRAMMING ON ANY OF M Y TVS 99 DON’T KNOW

IF TELEVISION WAS PLUGGED IN DURING PAST MONTH, V1A (1

- 20), CONTINUE.

ALL OTHERS SKIP TO INSTRUCTIONS BEFORE V13

IF ONLY ONE TELEVISION, V1A (1), ONLY ASK FOR PRIMARY.

IF TWO TELEVISIONS, V1A (2), ASK FOR PRIMARY AND SECONDARY.

IF THR EE TELEVISIONS, V1A (3

- 10), ASK FOR PRIMARY, SECONDARY, THIRD,

IF FOUR OR MORE TELEVISIONS, V1A (4

- 20), ASK FOR PRIMARY, SECONDARY, THIRD, AND FOURTH

The next questions are about TELEVISIONS in your household, starting with the PRIMARY, or most

- watched T V.

[SHOW IF V1A (2

- 20)]

For the next few questions, please answer for up to four TVs owned by your household. Please consider the one used the MOST the PRIMARY TV, the one used the SECOND most the SECOND TV, the one used the THIRD most as the THIRD TV an d the one used the FOURTH most as the FOURTH TV.

ASK V3

- V8 ‘A’ SERIES BEFORE GOING TO THE ‘B’ SERIES, ETC.

V3 Is the [INSERT] television that you own a . . .

(READ ENTIRE LIST BEFORE RECORDING ONE ANSWER.]

[DO NOT RANDOMIZE LIST OR ITEMS]

01 LCD or LED F lat

- panel TV 02 Plasma Flat

- panel TV 03 Tube TV, also known as a direct

- view CRT 04 Front or Rear Projection TV

### 128 99 DON’T KNOW/NOT SURE

A. Primary
B. Second
C. Third
D. Fourth

V4 What is the approximate screen size IN INCHES of the [INSERT] TV that you own? If you are not sure , please use your

best estimate.

(RECORD NUMBER. RANGE IS 5

- 72, DON’T KNOW/NOT SURE)

(PROBE FOR BEST GUESS BEFORE ACCEPTING DON’T KNOW)

A. Primary
B. Second
C. Third
D. Fourth

V5 What is the age IN YEARS of the [INSERT] TV that you own? If you are not sure, pleas e use your best estimate.

(RECORD NUMBER. RANGE 1

- 50, DON’T KNOW/NOT SURE)

(IF RESPONDENT SAYS THE TV IS NEW, AS IN LESS THAN ONE YEAR, RECORD AS 1. PROBE FOR BEST GUESS BEFORE ACCEPTING DON’T KNOW)

A. Primary
B. Second
C. Third
D. Fourth

PROGRAMMING NOTE: THIS W ORDING SHOULD ONLY BE DISPLAYED DURING THE ‘A’ SERIES (PRIMARY TELEVISION)

Next, I am going to ask you a couple of questions about how you and those in your household use the TVs you currently have plugged into an electrical outlet. I am going to use two terms that I will define for you.

The first term is ‘turned on’. ‘Turned on’ means that the television’s power is in the ON mode regardless of whether someone is actually using it. For example, a TV is turned on when there is a picture on the screen or s ound being emitted, as well as when it has a screen saver on while waiting for users.

The second term is ‘active use’. ‘Active use’ means that the television is on AND being used by someone. For example, when a TV is in active use, someone is using it to watch TV, a movie, play games or is actively listening to the TV.

V6A Now, thinking of the [INSERT] TV that you own, during the PAST 24 HOURS, how much time was it turned on? If you

are not sure, please give your best estimate.

(RECORD NUMBER. RANGE FO R HOURS (a) IS 0

- 24, DON’T KNOW AND RANGE FOR MINUTES (b) IS 0

- 59, DON’T KNOW)

A. Primary
B. Second
C. Third
D. Fourth

a. Hours b. Minutes

[ASK FOR EACH V6A A

- D ([a (HOURS) IS 1

- 24] OR [b (MINUTES) IS 1

- 59)]]

### 129

[IF V6A A

- D a (0), AUTOPUNCH V6B A

- D a AS 0]

V6B A nd during the PAST 24 HOURS, how much time was the [INSERT] TV in active use? If you are not sure, please give your best estimate.

(RECORD NUMBER. RANGE FOR HOURS (a) IS 0

- ANSWER GIVEN IN V6A, DON’T KNOW AND RANGE FOR MINUTES (b)
IS 0

- 59, DON’T KNOW)

A. Primary
B. Second
C. Third
D. Fourth

a. Hours b. Minutes

V7 Which of the following devices, if any, are connected to your [INSERT] television?

(READ LIST. RECORD AS MANY AS APPLY. WAIT FOR YES OR NO FOR EACH)

[DO NOT RANDOMIZE LIST]

01 Recei ver or set

- top

- box with DVR functionality 02 Receiver or set

- top

- box WITHOUT DVR functionality 03 Digital media streaming device with DVR functionality 04 Digital media streaming device WITHOUT DVR functionality
98 NONE OF THESE 99 DON’T KNOW

A. Primary
B. Second
C. Thir d
D. Fourth

[ASK FOR EACH MENTION, V7A

- D (01

- 02)]

V8 Which of the following features, if any, does your receiver or set

- top box connected to your [INSERT] television have?

(READ LIST. RECORD AS MANY AS APPLY. WAIT FOR YES OR NOT FOR EACH)



### 01 Ability to record shows in one room and play them back in another room 

### 02 Ability to pause and rewind LIVE TV in one room and resume viewing in another room 

### 03 Ability to record FIVE or more shows at once 98 NONE OF THESE 99 DON’T KNOW

A. Primary
B. Second
C. Third
D. Fourth

V9A and V1 0 OMITTED

IF A DIGITAL MEDIA PLAYER WAS PLUGGED IN DURING PAST MONTH, V1C (1

- 20), CONTINUE.

ALL OTHERS SKIP TO INSTRUCTION BEFORE V13

### 130

The next questions are about streaming video from your digital media streaming device which streams video content from the Internet or networked computer, such as Apple TV, Roku or Chromecast. For this section, DO NOT count Blu

- Ray or DVD players that have this feature.

V11 Please think of the most recent occasion when you were the FIRST person in your household to use the di gital media

streaming device, to watch streaming video. Did you need to turn ON the digital media streaming device, for example, by using a remote control or power switch?

01 YES 02 NO 99 DON’T KNOW

V12 How long did you or anyone in your household watch stre aming video content YESTERDAY using a DIGITAL MEDIA

STREAMING DEVICE such as Apple TV or Roku? Please do not include video content streamed on other devices such as the computer including tablets and laptops, Smart TV or DVD/Blu

- Ray player.

(RECORD NUMBE R. RANGE IS 0

- 24 HOURS AND 0

- 59 MINUTES, DON’T KNOW)

IF HOME SPEAKER SYSTEM WAS PLUGGED IN DURING PAST MONTH, V1B (1

- 20), CONTINUE.

ALL OTHERS SKIP TO NEXT SECTION

IF ONLY ONE HOME SPEAKER SYSTEM, V1B (1), ONLY ASK FOR PRIMARY.

IF TWO HOME SPEAKER SYSTEMS , V1B (2), ASK FOR PRIMARY AND SECONDARY.

IF THREE HOME SPEAKER SYSTEMS, V1B (3), ASK FOR PRIMARY, SECONDARY AND THIRD.

IF 4 OR MORE HOME SPEAKER SYSTEMS, V1B (4

- 20), ASK FOR PRIMARY, SECONDARY, THIRD, AND FOURTH

The next questions are about HOME SPEAKER S YSTEMS, starting with the PRIMARY or most used HOME SPEAKER SYSTEMS. Home speaker systems include speakers that are used with TVs, such as ‘Home Theater Systems’, ‘sound

- bars,’ amplifiers or stereo systems. They do NOT include portable stereos or speaker s used with computers.

ASK V13 AND V14 IN SEQUENCE FOR EACH SPEAKER SYSTEM

V13 Please think of the most recent occasion you used the [INSERT] HOME SPEAKER SYSTEM for the FIRST TIME THAT

DAY. Did you need to turn ON the speaker system, for example, by usin g a remote control or power switch?

01 YES 02 NO 99 DON’T KNOW

A. Primary
B. Secondary
C. Third
D. Fourth

V14 How long was the [INSERT] speaker system used YESTERDAY, by you or anyone else in your household?

(RECORD NUMBER. RANGE IS 0

- 24 HOURS (a) AND 0

- 59 MINUTES (b) , NOT USED DON’T KNOW)

A. Primary
B. Secondary
C. Third
D. Fourth

a. Hours b. Minutes

### 131



## A.5 Video Game Consoles

E1 For each of the following VIDEO GAME CONSOLES, please indicate how many you or someone in your household

owns.

(RECORD NUMBER FOR EACH. RANGE IS 0

- 10, DON’T KNOW)

[RANDOMIZE ITEMS]

A. Microsoft Xbox
B. Microsoft Xbox 360
C. Microsoft Xbox One
D. Sony PlayStation 2
E. Sony PlayStation 3
F. Sony PlayStation 4
G. Nintendo GameCube
H. Nintendo Wii
I. Nintendo Wii U

IF OWN ANY VIDEO GAME CONSOLE, E1A

- I (1

- 10), CONTINUE.

ALL O THERS SKIP TO NEXT SECTION

E2

- E7 PROGRAMMING NOTES:

ASK FOR UP TO 4 CONSOLES, E1A

- I (1

- 10), WITH PRIORITY ON:

1. E1B (MICROSOFT XBOX 360)

2. E1H (NINTENDO Wii)

3. E1E (SONY PLAYSTATION 3)

4. E1D (SONY PLAYSTATION 2)

IF NECESSARY, ASK FOR REMAINING I TEMS (A, C, F, G, I) ACCORDING TO LEAST FILL PRIORITY

NOTE: MORE THAN ONE OF THE SAME CONSOLE CAN BE ASKED ABOUT IN THIS SEQUENCING, AND SHOULD ALWAYS TAKE GREATER PRIORITY BEFORE A NON

- PRIORITY SYSTEM IS CONSIDERED

ASK E2

- E7 FOR ONE ITEM BEFORE MOVING ON TO E2

- E7 FOR THE NEXT ITEM

E2 Please indicate in what year your [INSERT ITEM] was purchased or received as a gift, if you got it BRAND NEW.

(RECORD YEAR FOR EACH. RANGE IS 2000

- 2014, WAS NOT BRAND NEW, DON’T KNOW)

[RANDOMIZE ITEMS]

A. Microsoft Xbox
B. Microsof t Xbox 360
C. Microsoft Xbox One
D. Sony PlayStation 2
E. Sony PlayStation 3
F. Sony PlayStation 4
G. Nintendo GameCube
H. Nintendo Wii
I. Nintendo Wii U

i. First console

### 132 ii. Second console
iii. Third console iv. Fourth console

[ONLY DISPLAY BEFORE FIRST SERIES]

The next few questions will be about the USAGE of your video game console.

Next, we will ask you about HOW you and those in your household use your gaming console(s), in one of the following states:

 TURNED ON

— the gaming console’s power is in the ON mode REGARDLESS of whether someone is actually using it. This includes time when the console is paused.

 ACTIVE USE

— the gaming console is ON AND BEING USED by someone. For example, when a gaming console is in active use, someone is using it to play games, watch a movie, etc.

 TURNED OFF

— the gaming console is OFF. You turned OFF your gaming console manually or by using a voice command.

E3 How much time did your [INSERT ITEM] spend YESTERDAY in each of the following states? Please give your answer in hours and minutes. If you did not use y our [INSERT ITEM] yesterday, please say so.

(RECORD A NUMBER. RANGE FOR A IS 0

- 24, DON’T KNOW; RANGE FOR B IS 0

- 59, DON’T KNOW)

[RANDOMIZE ITEMS]

07 Turned on 08 Actively used

C. HOURS
D. MINUTES

a. Microsoft Xbox b. Microsoft Xbox 360

c. Microsoft Xbox One d. Sony PlayStation 2

e. Sony PlayStation 3 f. Sony PlayStation 4
g. Nintendo GameCube h. Nintendo Wii
i. Nintendo Wii U

i. First console ii. Second console
iii. Third console iv. Fourth console

[ASK IF E3 A OR B IS 1 OR MORE FOR ‘ACTIVELY USED’

- 02]

E4 During the [INSERT E3A] [DISPLAY IF E3A (1

- 24)] ( hours and) [INSERT E3B] [DISPLAY IF E3B (1

- 59)] (minutes) your

[INSERT ITEM] was actively used YESTERDAY, approximately how much of this time was used to do each of the following? If you are not sure, please use your best estimate. Please give your answe r in hours and minutes.

(RECORD A NUMBER. RANGE FOR A IS 0

- ANSWER FROM E3A (02), DON’T KNOW; RANGE FOR B IS 0

- 59, DON’T KNOW)

[RANDOMIZE ITEMS]

01 Play games 02 Stream media from the video game console or Internet 03 DVD and/or Blu

- Ray playback

### 133 A. HOURS
B. MINUTES

a. Mic rosoft Xbox b. Microsoft Xbox 360

c. Microsoft Xbox One d. Sony PlayStation 2

e. Sony PlayStation 3 f. Sony PlayStation 4
g. Nintendo GameCube h. Nintendo Wii
i. Nintendo Wii U

i. First console ii. Second console
iii. Third console
iv. Fourth console

E5 Thinking about the last time when you we re the FIRST PERSON to ‘actively use’ the [INSERT ITEM] on a day, which statement best describes your gaming console?

(READ ENTIRE LIST BEFORE RECORDING ONE ANSWER)

01 It was already turned ON and ready to use 02 It was turned OFF and you needed to turn it on to use it 99 DON’T KNOW

A. Microsoft Xbox
B. Microsoft Xbox 360
C. Microsoft Xbox One
D. Sony PlayStation 2
E. Sony PlayStation 3
F. Sony PlayStation 4
G. Nintendo GameCube
H. Nintendo Wii
I. Nintendo Wii U

i. First console
ii. Second console iii. Third console
iv. Fourth console

E6 Does your [INS ERT ITEM] automatically turn off after a sustained period of inactivity?

[RANDOMIZE ITEMS]

01 YES 02 NO 99 DON’T KNOW

A. Microsoft Xbox
B. Microsoft Xbox 360
C. Microsoft Xbox One
D. Sony PlayStation 2
E. Sony PlayStation 3
F. Sony PlayStation 4
G. Nintendo GameCube
H. Nintendo Wii

### 134 I. N intendo Wii U

i. First console
ii. Second console iii. Third console
iv. Fourth console

[ASK FOR EACH MENTION E6A

- I (01)]

E7 After approximately how many hours does the [INSERT ITEM] automatically turn off?

(RECORD A NUMBER. RANGE IS 1

- 24, DON’T KNOW)

[RANDOMIZE ITEMS ]

A. Microsoft Xbox
B. Microsoft Xbox 360
C. Microsoft Xbox One
D. Sony PlayStation 2
E. Sony PlayStation 3
F. Sony PlayStation 4
G. Nintendo GameCube
H. Nintendo Wii
I. Nintendo Wii U

i. First console ii. Second console
iii. Third console
iv. Fourth console

### 135



# Appendix B

– Energy and Usage Models

We discuss in detail several models used to calculate the usage time and energy consumption for desktop and portable computer, smart phones, tablets, and video game consoles.



## B.1 Energy Models

— Personal Computers (Desktops and Portables) In this appendix, w e describe the energy model used to calculate the unit and annual energy consumption for d esktop and p ortable personal computers ( PCs )

.
We reference specific questions in the survey to obtain values certain variables in the energy model.
These are indicate d in bold green, e.g., <C5.A> references survey question 5, sub

- question A in the computer survey. See Appendix A.1 for the survey questions.

Table B

- 1 : Variables directly measured in the CE Usage Survey

.

Survey Question Purpos e Measure Variable
C1.# Number of plugged

- in ... Installed base Count C2. A Desktop PCs
C2. B Portable PCs
C2.## Usage time ... Usage time Time (hh:mm)
C2. 01 During the morning hours (before 12 noon)

C2. 02 During the afternoon hours (between 12 and 5pm)

C2. 03 During the evening hours (between 5pm and when

you go to sleep at night)
C2. 04 In one session of use, before the evening

C2. 05 In one session of use, in the evening

C2. 06 Over the whole day

C3.# Frequency that the PC is ... Manu al power management (PM)
routines Probability
C2. A Left on, during the daytime
C2. B Put into sleep, during the daytime
C2. C Turned off, during the day time
C2. D Turned off, at night

C4 Initial state of the PC for the day Auto PM settings Choice
C5.# Number of devices connected to PC ... Indirect accounting of AIO desktop PCs Count C2. A LCD monitors C2. B CRT monitors C2. C Speakers with out subwoofer

- C2. D Speakers with subwoofer

-



### B.1.1 Plugged

- In Install Base
The installed base is calculated from the total sum of desktop or portable PCs reported by each respondent ( and ), and weighted to the U.S. household distribution. ∑
∑

### 136

where

 is the sum of weights of each survey response to all U.S. households

 is the number of U.S. households

 is the set of survey responses

 is weight of the th survey response

 is number of desktop PCs reported by the th survey response <C5.A>

 is number of desktop PCs reported by the th survey response <C1.B>

We also distinguish All

- in

- One (AIO) desktop PCs from tower desktop PCs by noting, for each primary or secondary P C, if the PC has no monitor (LCD or CRT) connected to it, i.e., < C5.A=0 and
C5.B=0 >

.

B.1.2 Operational Modes

PCs can enter different operational modes with different power draws after various time durations. We previously defined the mo des used in our energy model (see Section 3.4 ). We declare these as variables in this model (see Table B

- 2 ).

Table B

- 2 : Variables for power draw and time threshold of various operational modes

. Operati onal Mode Active Short Idle Long Idle Sleep Off

Power Draw
Time Threshold



### We define the threshold time durations after which the low er power modes are triggered in Table B

- 3

. These thresholds are calculated based on the ENERGY STAR specification and as measured in the ENERGY STAR Qualified Product List (QPL) ( EPA 2013 ).

Table B

- 3 : T ime Threshold s at the start of a post

- session after which the PC enters various operational modes

.

Time Threshold ENERGY STAR Spec. (minutes) Default in QPL (minutes) Representative

Desktops Portables Desktops Portables § Average Median Average Media n † 0 0

5

- - - - 5 5
15 25 15 23 10 15 10
30 13 30 112 25 30 25
60 *

- - - - 60 60 ‡ § We choose shorter time threshold s for portable PCs which are consistent with their behavior to conserve energy when occasionally running on battery. † Z ero

- valued variable introduced for consistency in some equations

. ‡ I nfinity

- valued variable introduced for consistency in some equat ions

. * A ssumed, specified for our analysis

.


### B.1.2.1 Operational Modes for External Power Supplies of Portable PCs
Portable PCs have additional operational modes due to their external power supplies (EPS) which charge the portable PC batteries, from which the PCs may be unplugged, and which may be unplugged from the wall socket altogether. This leads to increased energy consumption for charging, and decreased energy

### 137

consumption when the portable PC is unplugged. In our model, we calculate the time spent in these

m odes as a fraction of the usage time of the portable PC in various base operational modes (see Table

B

- 4 ; see Section B.1.7.2 for more details)

. These modes are originally defined by DOE (2012).

Table B

- 4 : Variables for power draw and portion of time of various operational modes for portable PCs due to their external power source (EPS)

.

Base Portable PC Mode Active, Short Idle, and Long Idle Off

EPS Mode Charging (Active) C harging (Off) Off Unplugged EPS Unplugged

Portable PC + EPS Power Draw
% time of PC mode in EPS mode


### where

 W, i.e., no power draw

 ( )



B.1.3 Usage Modeling

We expect usag e to vary at different times of the day. Therefore, we identify several day periods and model the usage and energy consumption for each period. Then, we sum them to get the total usage and energy consumption for the whole day, and, ultimately, the UEC for the whole year and AEC for the
installed base.

B.1.3.1 Day Periods
Based on our analysis of the amount of computer usage across a day ( ATUS 2012 ), w e model computer usage by period during the day: Pre

- Evening (morning and afternoon), Evening, and Night

. Restrictin g to Home/Yard ( TEWHERE = 1) , we considered activities with potentially major components of computer usage [ TRCODE ]:

 Financial management [ 20901 ], n=355

 Work, main job [ 50101 ], n=9720

 Work, other job(s) [ 50102 ] , n=370

 Playing Games [ 120307 ], n=1381

 Comput er use for leisure (exc. Games) [ 120308 ], n=1902

 Computer use (Volunteering) [ 150101 ] , n=157

### 138

Figure B

- 1 : Probability density of performing activities related to using computers ( ATUS 2012 )

. 

### From Figure B

- 1 , we can estimate default boundaries and durations for the three day periods. However, some survey responses indicated that the active use duration within certain periods exceed the defined bounds. Therefore, we allow for the day periods to be adju stable by formulas presented in Table B

- 5

.

Table B

- 5 : Time durations for different day periods

.

Day Period Formula Default Example Survey Response

Range Duration

[ h ours] Reported Adjusted
( ) 7am

- 5pm 10 11 11 ( ) 5pm

- 11pm 6 7 7 11pm

- 7am 8

- 6


### The time periods sum to 24 hours in a whole day, i.e.,

Next, we describe how we compute energy consumption for the pre

- evening, evening, and night periods. The calculation s for the pre

- evening and evening periods are similar and will henceforth be called daytime periods.

B.1.3.1.1 

### Sample Energy Consumption across D aytime Periods


### For daytime periods, we model the number of active use sessions, which include “micro

- breaks” within each session, and post

- sessions between them. After each session, the PC may gradually go into a lower power operational mode. The minimum p ower mode depends on the automatic power management (PM) settings, and whether household occupants manually put the PC into sleep or turn it off. We model the night period as having no active use sessions, so its energy consumption is only due to automatic PM settings and manual power management. Figure B

- 2 shows two examples of the energy consumption as calculated by the energy usage model. 0% 2% 4% 6% 8% 10%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 % U.S. Population

Computer Usage Start Time (Hour)

### 139 Based on power draw by mode, survey responses of usage duration for each session and h ow many sessions per day period. Left: PC left on during the day time, PM auto

- hibernate. Right: PC left on during the daytime, PM long idle enabled, manually put to sleep at night.

Figure B

- 2 : Examples of energy consumption m odeling for a day.



### B.1.3.2 Daytime Periods
We model usage in the day time (pre

- evening and evening) as consisting of active use sessions separated by post

- session periods. The number of sessions is:

where

 is the total usage duration in the daytime period <C2.01, C2.02, C2.03>

 is the typical session duration <C2.04, C2.05>

B.1.3.3 Usage Session

We assume that users t ake a “micro

- break” after one hour during each active use session (OSHA 1997, UC Berkeley 2014). We assume that each break lasts about 10 minutes (average of short and long idle thresholds). This gives 5 minutes for short

- idle mode to activate and 5 minute s to be in that mode. The usage time for each operational mode in each session computed as :

Daytime: Usage Session



### where

 ( ) ⌊ ⌋ is the number of breaks per session

### 140  is the active usage time threshold until a short break

B.1.3.4 Post

- Session

A p ost

- Session is defined as the following unused period unti l the next a ctive usage session. This calculation only applies if there is at least one active use session in the daytime period, i.e.,
. See Section B.1.3.5 for how we calculate for cases with no active session. Eac h post

- session is defined
with:

⌈ ⌉

where

 is the duration of the daytime pe riod ( or )

After a usage session, i.e., post

- session, the PC may enter into lower power modes after a series of time thresholds. These depend on the total time of the post

- session before the next usage session, and the power management routines (manual user behavior) and automated settings.

B.1.3.4.1 

### Manual Power Management Routines

We asked U.S. adult s how often they manually turned their PC off or put it to sleep < C3> to get measures for the following variables:

 is the probability of manually switching OFF after each daytime use <C3.C, C3.D>

 is the probability of manually putting computer into SLEEP during daytime <C3.B>

 is the probabilit y of leaving computer ON after use during daytime <C3.A>

We map numeric probability values from discrete option values in the survey responses with:

{

̅

where

 ̅ is the average of the probability metric

 { }

### 141

B.1.3.4.2 

### Automated Power Management Settings Modes



### The automate d power management settings, , measured in < C4 > is defined as:

{

Note that is enabled by using auto

- hi bernate under advanced power management settings 40



### . Also, it is not defined in ENERGYSTAR, so there would not be a default time for it to activate.

B.1.3.4.3 

### Usage Time by Operational Mode in Post

- Session

The usage time for each operational mode in each post

- session is:

Daytime: Post

- Session

( ) ( ) ( ) ( ) ( )



### where

, , , , and are the time durations the PC is in active, short idle, long idle, sleep, and off modes, respectively, in a post

- session. These are functions of and

:
( ) ( ) ( ( ) ) ( ) ( ) ( ) ( ) ( ( ) ) ( ) ( ) ( ) ( ) ( ( ) ) ( ) ( )
( ) ( ) ( ( ) ) ( ) ( )
( ) ( ) ( ( ) ) ( ) ( )

B.1.3.5 Non

- Session

If the re is no active use session during a daytime period, then power draw depends only on the power management settings. We define one “non

- Session” for that period with the following characteristics:

[ ] {

40 For example, in Windows XP: http://www.microsoft.com/resources/documentation/windows/xp/all/proddocs/en

us/pwrmn_automatic_hibernation.mspx?mfr =true

### 142 Daytime: Non

- Session

( ) ( ) ( ) ( )



### where

 is the total duration for the daytime period, { }

B.1.3.6 Total Usage by Operational Mode in Daytime Period
Combining the usage time for all sessions and post

- sessions, we get the total usage by operational
mod e for the daytime period:

Daytime

{ }



### B.1.4 Pre

- Evening Period
To determine the usage time in the eveni ng period, we use the calculations for daytime periods with the following substitutions:

 <C2.03>

 <C2 .01, C2.02 >



B.1.5 Evening Period
To determine the usage time in the evening period, we use the calculations for daytime periods with the following substitutions:

 <C2.03>

 <C2.05>



B.1.6 Night Period
We assume that the computer is not actively used at night , so this period does not have any sessions
and power dra w depends only on the power management settings. Since we asked U.S. adult s only

### 143

whether or not they turned off the PC at night, we estimate the probability of leaving the PC on or putting it to sleep at night based on the ratio between leaving on a nd sleep for the day: ( )

Therefore, we calculate the time in operational modes at night as:

Night

( ) ( ) ( ) ( )



### where

 is the probability of leaving the PC on at night

 is the probability of putting the PC to sleep at night

 is the probability of manually turning the PC off at night <C3.D>

 ( ) { ( )

 ( ) is the empirical probability distribution of power management modes

B.1.7 Whole Day
The usage time and energy consumption for desktop and portable PCs differ slightly due to the external power modes of portable PCs.

B.1.7.1 Desktop PC
The usage time for the whole day is the sum of the energy consumption for the pre

- evening, evening,

an d night sessions for desktop PCs are:

Whole Day

— Desktop PCs : Usage Time



### B.1.7.2 Portable PCs
For portable PCs, we model additional operational modes due to the external power supply (EPS) and apply the following adjustments to calcu late the usage time for several modes:

### 144  ( ) the total time

spent charging during active

- idle and off modes.

 where we scale the time in off mode by down to accommodate for the times in additional modes: charging (off), unplugged, EPS unplugged




The usage times for the following modes are unchanged:

, , , and

.
We define the total time plugged in for the whole day as:

Who le Day

— Portable PCs : Usage Time



### This excludes the time when the EPS is unplugged from the wall socket, , i.e.,

Also, note that the usage time for charging overlaps with active and off modes, i.e.,

B.1.8 References ATUS. 2012. “ American Time Use Survey

— 2012 Microdata Files .” Jun. 20, 2013. United States Department of Labor. http://www.bls.gov/tus/datafiles_2012.htm . Retrieved Oct. 30, 2013. UC Berkeley. 20 14. “Safe Computer Use Tips.” University of California Ergonomics. http://ergo.berkeley.edu/services /computer_use.php . Retrieved Mar. 7, 2014.
DOE. 2012. “ Rulemaking for Battery Chargers and External Power Supplies Energy Conservation Standard

. Energy Use Analysis Spreadsheet .” Feb. 17, 2012. http://www.regulations.gov/#!documentDetail;D=EERE

- 2008

- BT

- STD

- 0005

- 0084 . Retrieved Feb. 6, 2014.

EPA. 20 13. “ENERGY STAR Computer Specification Version 5.2

— Qualified Product List.” Sept. 6, 2013. http://www.energystar.gov/products/specs/computer_specification_version_6_0_pd . Retrieved Sept. 16, 2013. OSHA (Occupational Safety and Health Administration). 1997. “Working Safely wit h Video Display Terminals.” U.S. Department of Labor. https://www.osha.gov/Publications/osha3092.pdf . Retrieved Sept. 16, 2013. UC Berkeley. 20 14. “Safe Computer Use Tips.” University of Califo rnia Ergonomics. http://ergo.berkeley.edu/services/computer_use.php . Retrieved Mar. 7, 2014.

### 145



## B.2 Energy Usage Models

— Mobile Devices (Tablets and Smartphones)

In this appendix, w e describe th e energy model used to calculate the unit and annual energy consumption for mobile devices: tablets and smartphones

.
We reference specific questions in the survey to obtain numeric values certain variables in the energy model. These are indicated in bold g reen, e.g., <M1.A> references survey question 1, sub

- question A in the mobile survey. See Append ix A

– CE Usage Survey s for the survey questions.

Table B

- 6 : Variables directly measured in the CE Usage S urvey

.

Survey Question Purpose Measure Variable
M1.# Number of plugged

- in ... Installed base Count M2. A Smartphones
M2. B Tablets
M2 Usage time over the whole day Usage time Time (hh:mm)
M3 Number of charge sessions / week Charge cycles Count
M4.# Battery life level ... Charge cycles 0

- 100
M4. A Before charging
M4. B After charging
M5.## Time device is plugged into ... Charger preference Time (hh:mm)
M5. 01 Original charger
M5. 02 Other chargers
M6 Plugged

- in time of charger Unplugged mode Time (hh:mm)



### B.2.1 Plugged

- In Install Base
The installed base is calculated from the total sum of desktop or portable PCs reported by each respondent ( and ), and weighted to the U.S. household distribution. ∑
∑

where

 is the sum of weights of each survey response to all U.S. households

 is the number of U.S. households

 is the set of survey responses

 is weight of the th survey response

 is number of smartphones reported by the th survey response <M1.A>

 is number of tablets reported by the th survey response <M1.B>

B.2.2 Energy Consumption
We model the energy consumption by how much energy is consumed to charge the battery, how much is consumed while idle, and how much is consumed because the batter y charger is left plugged into the wall socket after charging. Specifically, we consider the following modes:

### 146  Charging: when replenishing the battery of the mobile device to its fully capacity with an

additional energy loss due to the inefficiency in the c harger.

 Idle: when the mobile device has its screen off, is connected to its charger, but not charging. The power draw in this mode is higher than the standby power draw when the mobile device is running on its battery unplugged from the charger.

 Unplugged : when the mobile device is unplugged from its charger, but the charger is still plugged into the wall socket. The power draw is solely due to the charger.

 BC Unplugged: when the charger is unplugged from the wall socket. The power draw is 0W.

B.2.2.1 Charging

Th e energy consumed for charging the mobile devices depends on how many times it is charged, and how much it is charged each time from before charging (pre

- charge) to after charging (post

- charge), represented by the battery level (state of charge). The energ y consumption for charging per day, , is calculated as:

Charging : Energy Consumption

( ) ( )



### where

 is the number of full charge cycles per day as the average sum of p artial charge cycles

 the number of times the mobile device is charged per week <M3>

 the average battery level before a typical instance of charging <M4.A>

 the average battery level after a typical instance of charging <M4.B>

and where is the energy used for each charging session, which depends on how much energy is needed to fully charge the battery, which charger is used (original or others), and the efficienc y of the chargers, with

 the representative battery capacity in Wh

 the repres entative original wall charger efficiency while charging

 the representative charger efficiency of other chargers (e.g., a ftermarket charger, counterfeit charger, USB port of a computer or speaker system, in car 12V )

 the portion of time (%) spent charging with the representative

original wall charger

 the portion of time of charging with the representative other wall charger

### 147  the time plugged into the original wall charger <M5.A>

 the time plugged into other charger s <M5.B>

B.2.2.2 Usage
Although not directly used in our energy model, we asked U.S. adult s about how much they used their mobile devices yesterday <M2> . To validate our charging energy model, we found a moderate correlation between usage, and number of cha rge sessions ( r =0.25) and number of full charge cycles ( r =0.23).

B.2.2.3 Idle
The energy consumption when the mobile device is idle (plugged into the charger with screen off) is

Idle : Energy Consumption



### where

 is the number of full charge cycles per day

 is the power draw in idle mode weighted for the portion of time using the original and other charges with and power draws, respectively

 is the time spent per day idle mode

 is the time spent per day charging the battery

 is the time to fully recharge the battery from 0

- 100%

B.2.2.4 Un plugged
The power draw of battery chargers with the device unplugged may account for a relatively significant portion of the mobile device energy consumption. We therefore account for this by evaluating the time that the chargers are left plugged into the wall after charging.

The energy consumption of the mobile device when unplugged from the charger is

Unplugged : Energy Consumption

{



### where

### 148  is the power draw of the representative original charger with the mobile device

unplugged

 is the power draw of the representative alternative charger (others)

 is the amount of time yesterday the original charger wa s plugge d into the
wall while not charging

 is the amount of time yesterday the original charger wa s plugged into the wall (with and without charging) <M6>

 is the plugged

- in time for other chargers after charging, where w e assume that other chargers are plugged i n for the same amount of time as the original charger if they are
used

B.2.2.5 Representative Weights for Mobile Device and Charger Models

We estimate the representative weights, , from an analysis of the usage share of popular mobile device models (see



### Table B

- 10 for smartphones and Table B

- 7 for tablets). Usage share is similar to installed base, but refers to the distribution of device models by their usage popularity instead of survey reported ownershi p. We refer to data sources which measured app usage or website visits of unique users to get an estimate for the usage share of mobile device models.

The representative battery and chargers depend on the estimated usage share, , of various popular mobile devices and their respective chargers: ∑ ∑ ∑

where

 is the set of models of the mobile device category, e.g., { }

 is the battery capacity of the th mobile device model

 is the efficiency of the original charger of the th mobile device model

We represent t he efficiency of other char gers by an average of several documented aftermarket chargers: ∑

where

 is the efficiency of the th alternative charger

We calculate the representative power draws as:

### 149 ∑ ∑

where

 is the power draw of the th original charger with the mobile device unplugged

 is the power draw of the th alternative charger with the mobi le device unplugged; we assume equal weighting, for lack of data regarding the usage share of alternative chargers.

Table B

- 7 : Usage share of popular tablet models used to derive weights, , to estimate the representative battery capacity and power draw values for tablets.

Usage Base Share

Dec 13 Dec 13 Dec 13 Sep 13 Sep 13 Jun 13 Dec 13 Aggre

gate Represent

ative Weights Model OS Mix

- Panel 2014b Fiksu

2014 Stat

Counter 2013b Chitika

2013 Local

ytics 2013 Magid
2013 CEA 2014 *

iPad mini 2 iOS 0.8% 1.1%

79% - - - 0.7%

- iPad Air iOS 3.0% 4.3%

- - - 2.7%

- iPad mini 1 iOS 16% 21%

81% - - 21% † 14% 16% iPad 4 iOS 14% 20%

- - 20% † 13% 15% iPad 3 iOS 15% 16%

- - 18% † 12% 14% iPad 2 iOS 32% 37%

- - 40% † 26% 30% iPad 1 iOS 3.4% 0.3%

- - 1.4%

- Kindle Fire HD Android

- - 8.0% 6.7% 56% 31% 42% ‡ 5.1% 10% Kindle Fire HD 8.9” Android

- - 22% ‡ 11% 5.5% Samsung Galaxy (7

- 8") Android 13% - 4.0% 5.1% 15% 19% 23% ‡ 2.9% 5.8% Samsung Galaxy (>8) Android

- 12% ‡ 6.2% 3.1% B&N NOOK HD/HD+ Android 1.9%

- 0.6% 1.1% 17% 8.0% 0.9%

- Google Nexus 7 Android

- - 2.3% 1.6% 14% 8.0% 1.2%

- Microsoft Surface Windows

- - 0.5% 1.0%

- 5.0% 0.6%

- Other

- - - 5.8% 3.5%

- 19% 2.8%

- * Usage share estimated b ased on distribution of all tablets by screen sizes (32% for 7

- 8”, 68% for 8.9

- 10.1”). † Estimates normalized to 100% for iOS tablets only (16% for 7

- 8”, 59% for 8.9

- 10.1”). ‡ Estimates normalized to 100% for Android tablets only (16% for 7

- 8”, 8.6% for 8.9

- 10.1”).

Table B

- 8 : Representative battery capacity and power draw estimates determined by a weighted average of the most popular tablet models.

Tablet Model Screen Size

[inches] Release

Year Represent

ative Weights Battery

C apacity * [Wh] Charger

Efficiency [%] Battery

Recharge Time [hr] † Power Draw [W]

Idle ‡ Unplugged §

iPad mini 1 7.9 2012 16% 16.5 75% a 4.1 0.27 a 0.09 iPad 4 9.6 2012 15% 32.4 84% a 5.1 0.14 a 0.08 iPad 3 9.6 2012 14% 43.0 81% a 5.5 0.65 a 0.08 e
iPad 2 9.6 2011

- 13 30% 25.0 81% a 3.5 0.41 a 0.08 Kindle Fire HD 7” 7.0 2012 10% 16.5 75% e 3.1 0.27 e 0.10 Kindle Fire HD 8.9” 8.9 2012 5.5% 22.2 81% e 4.5 0.40 e 0.10 Galaxy Tab 3 7.0” 7.0 2013 5.8% 14.8 75% e 3.6 e 0.27 e 0.02 Galaxy Tab 3 10.1” 10.1 2012 3 .1% 25.9 81% e 5.0 0.40 e 0.09 Representative

- - - 25.6 76% 4.2 0.27 0.08
* Battery capacity estimates from iFixit (2012

- 2013). † Recharge time estimates from Tom’s Hardware (2012) § Average metered power draw from 10 measurements with a Yokogawa W210 power meter on Jan. 27, 2014.

### 150 a Source: Apple environmental reports (Apple 2012).

e No data for estimate, estimated based on mean of smaller (7

- 8”) and larger (≥8.9”) screens of iPad models.

Table B

- 9 : Representative power dr aw estimate determined by the average of several aftermarket tablet chargers.

Charger Model Charger Efficiency [%] Power Draw [W]

Unplugged Source
AmazonBasics Wall Charger (2.1A)

- 0.16 Measurement Trent NT90C 10W 5V/2A Dual USB Ports

- 0.07 Measurement Counterfeit iPad 66% 0.10 Shirriff 2012
KMS 69% 0.18 Shirriff 2012 Representative 68% 0.13 Average

Table B

- 10 : Usage share of popular smartphone models used to derive weights, , to estimate the representative battery capacity and power draw values for smartphones.

Usage Base Share
Jan 14 Dec 13 Dec 13 Sep 13 May 13 Q2 2013

Aggregate Represent

ative Weights Chitika
2014 Mix

Panel
2014a Stat

Counter 2013a com Score 2013 Magid

2013 Nielsen

2013 Model OS

iPhone 5S iOS

- 13% 60% 41% 41% 40% 6.0% 9.4% iPhone 5 iOS

- 36% 16% 25% iPhone 4S iOS

- 27% 12% 19% iPhone 4 iOS

- 19% 8.7% 14% iPhone 5C iOS

- 4.5% 2.0%

- iPhone Other iOS

- 1.8 % 0.8%

- Samsung Galaxy S4 Android 24%

- 16% 25% 26% 24% 5.4% 14% Samsung Galaxy S3 Android 34%

- 7.7% 20% Samsung Galaxy S2 Android 8.4%

- 1.9%

- Samsung Galaxy S Android 1.9%

- 0.4%

- Samsung Galaxy Note 3 Android 3.8%

- 0.9%

- Samsung Galaxy Note 2 Android 8.6%

- 1.0%

- Samsung Galaxy Note Android 0.9%

- 0.2%

- Samsung Galaxy Other Android 8.3%

- 1.9%

- Samsung Other Android 10%

- 2.4%

- HTC Android

- - 2.8% 7.1% 9% 17% 6.7%

- Motorola Android

- - 2.6% 6.8% 9% 10% 6.3%

- LG Android

- - 3.1% 6.6% 7% 5.6% 6.4%

- RIM BlackBerry

- - 3.6%

- - 3.0% 5.3%

- Other

- - - 12% 14% 11% 6.8% 9.9%

-

Table B

- 11 : Representative battery capacity and power draw estimates determined by a weighted estimate of the most popular smartphone models.

Smartphone Model Year Released Representative

Weights Battery

Capacity * [Wh] Charger

Efficiency [%] Battery

Recharge Time [hr] † Power Draw [W]

Idle Unplugged §

iPhone 5S 2013 9.4% 5.9 75% a

- 0.09 0 .02 iPhone 5 2012 25% 5.5 75% a 1.8 0.71 0.21 iPhone 4S 2011 19% 5.3 75% a 1.7 0.64 0.21 iPhone 4 2010 14% 5.3 75% a

- 0.35 0.21 Samsung Galaxy S4 2013 14% 9.9 77% 2.9 0.43 e 0.02 f Samsung Galaxy S3 2012 20% 8.0 77% 2.5 0.43 0.01 Representative

- - 6.5 7 6% 2.1 0.50 0.13
* Battery capacity estimates from iFixit (2012

- 2013). † Recharge time estimates from Tom’s Hardware (2012)

. § Average metered power draw from 10 measurements with a Yokogawa W210 power meter on Jan. 27, 2014.

### 151 a Source: Apple environme ntal reports (Apple 2012

- 2013).

e No data for estimate, so assumed similar to Galaxy S3.

f No data for estimate, but its charger is rated for 10W which is similar to tablets, so we assumed it is similar to the Samsun g Galaxy Tab 3.

Table B

- 12 : Representative power draw estimate determined by the average of several aftermarket smartphone chargers.

Charger Model Charger Efficiency [%] Power Draw [W] Source

Unplugged Kyocera SSW

- 2001

- 0.06 Measurement Counterfeit iPhone 63 % 0.38 Shirriff 2012 Monoprice 72% 0.08 Shirriff 2012 Belkin 66% 0.23 Shirriff 2012 Smartphone dataset 63% 0.11 DOE 2012 Representative 67% 0.19 Average



### B.2.2.6 Whole Day Energy Consumption
The total energy consumption for the whole day is:

This estimate applies to the primary smartphones and primary tablets. However, we do not directly ask about charging behavior for secondary tablets. We estimate their energy con sumption by assuming that the energy consumption between primary and secondary tablets follows the same ratio as usage time for the devices, i.e.:

where

 is the usage time per day for the primary tablet <M2b>

 is the usage time per d ay for the secondary tablet <M2c>

B.2.3 References Apple. 201 0 . “iP hone 4 Environmental Report.” Jun. 24 , 201 0

. http://www.apple.com/environment/reports/docs/i Phone_4_Product_Environmental_Report.pdf

. Retrieved Oct. 9, 2013. Apple. 201 1 . “iP hone 4S Environmental Report.” Oct. 4 , 201 1

. http://images.app le.com/environment/reports/docs/iPhone4S_Product_Environmental_Report_201 1.pdf

. Retrieved Oct. 9, 2013. Apple. 2012 a . “iPad 2 Environmental Report.” Mar. 7, 2012. http://images.apple.com/environment/reports/docs/iPad2_Product_Environmental_Report_2012.p df

. Retrieved Sept. 19, 2013. Apple. 2012 b . “iPad 3 Environmental Report.” Mar. 7, 2012. http://images.apple.com/environment/reports/docs/iPad_Product_Environmental_Report_March20 12.pdf

. Retrieved Sept. 19, 2013. Apple. 2012 c . “iPad 4 Environmental Report.” Oct. 23 , 2012. http://images.apple.com/environment/reports/docs/iPad_Retina_PER_oct2012.pdf

. Retrieved Sept. 19, 2013.

### 152

Apple. 2012 d . “iPad mini Environmental Report.” Oct. 23 , 2012. http://images.apple.com/environment/reports/docs/iPadmini_PER_oct2012.pdf

. Retrieved Sept. 19, 2013. Apple. 201 2e . “iP hone 5 Environmental Report.” Sept. 12 , 201 2

. http://images.apple.com/environment/reports/docs/iPhone5_product_environmental_report_sept2 012.pdf

. Retrieved Oct. 9, 2013. Apple. 201 3 . “iP hone 5S Environmen tal Report.” Sept. 10 , 201 3

. http://images.apple.com/environment/reports/docs/iPhone5s_product_environmental_report_sept 2013.pdf

. Retrieved Oct. 9, 2013.
CEA. 2014. “Consumer Outlook on Tablets

– Jan. 2014 Edition.” Jan. 2014. Consumer Electronics Association.
Chikita. 2013. “ Third Quarter End Tablet Update: iPad Usage Share at 81%, Other Tablets See Share
Increases .” Oct. 22, 2013. http://chitika.com/insights/2013/Q3

- tablet

- update . Retrieved Jan. 24, 2014.
Chikita. 2014. “ Samsung Status Report: Galaxy S III & IV Users Generate 57.7% of Samsung Smartphone Web Traffic in North Ame rica .” Jan. 14, 2014. http://chitika.com/insights/2014/samsung

- update

. Retrieved Jan. 17, 2014.
comScore. 2013b. “ MobiLens Sep 2013

- Top Smartphone OEMs .” Nov. 5, 2013. http://www.comscore.com/Insights/Press_Releases/2013/11/comScore_Reports_September_2013_ U.S._Smartphone_Subscriber_Market_Share . Retri eved Jan. 22, 2014.
DOE. 2012. “ Rulemaking for Battery Chargers and External Power Supplies Energy Conservation Standard

. Energy Use Analysis Spreadsheet .” Feb. 17, 2012. http://www.regulations.gov/#!documentDetail;D=EERE

- 2008

- BT

- STD

- 0005

- 0084 . Retrieved Feb. 6, 2014.
Fiksu. 2014. “ iPad, iPhone, and iOS 7 Adoption Trackers .” Dec. 23, 2013. http://www.fiksu.com/iOS

- 7

- iPhone

- 5s

- 5c

- Usage

- Tracker#ipad

- usage . Retrieved Jan. 21, 2014.
iFixit. 2010. “ iPhone 4 Teardown

. ” http://www.ifixit.com/Teardown/iPhone+4+Teardown/ 3130/1

. Retrieved Oct. 23 , 2013.
iFixit. 2011a. “ iPad 2 Wi

- Fi EMC 2415 Teardown

. ” http://www.ifixit.com/Teardown/iPad+2+Wi

Fi+EMC+2415+Teardown/5071/2#s22967

. Retrieved Oct. 4 , 2013.
iFixit. 2011b. “ iPhone 4S Teardown

. ” http://www.ifixit.com/Teardown/iPhone+4S+Teardown/6610/1

. Retrieved Oct. 23 , 2013.
iFixit. 2012a. “ iPad 3 4G Teardown

. ” http://www.ifixit.com/Teardown/iPad+3+4G+Teardown/8277/3#s33152

. Retrieved Oct. 4 , 2013.
iFixit. 2012b. “ iPad 4 Wi

- Fi Teardown

. ” http://www.ifixit.com/Teardown/iPad+4+Wi

Fi+Teardown/11462/1

. Retrieved Oct. 4 , 2013.
iFixit. 2012c. “ iPad mini Wi

- Fi Teardown

. ” http://www.ifi xit.com/Teardown/iPad+mini+Wi

Fi+Teardown/11423/2

. Retrieved Oct. 4 , 2013.
iFixit. 2012d. “ iPhone 5 Teardown

. ” http://www.ifixit.com/Teardown/iPhone+5+Teardown/10525/2

. Retrieved Oct

. 23 , 2013.
iFixit. 2012e. “ Kindle Fire HD Teardown

. ” Sept. 14, 2012. http://www.ifixit.com/Teardown/Kindle+Fire+HD+Teardown/10457/1

. Retrieved Oct. 4 , 2013.
iFixit. 2012f. “ Sam sung Galaxy S3 Teardown

. ” http://www.ifixit.com/Teardown/Samsung+Galaxy+S+III+Teardown/9391/1

. Retrieved Oct. 23 , 2013.

### 153

iFixit. 2012g. “ Samsung Galaxy Tab 3 7.0 3G Teardown

. ” http://www.ifixit.com/Teardown/Samsung+Galaxy+Tab+3+7.0+3G+Teardown/17357/2

. Retrieved
Oct. 4 , 2013.
iFixit. 2013a. “ iPhone 5S Teardown

. ” http://www.ifixit.com/Teardown/iPhone+5s+Teardown/17383/1

. Retrieved Oct. 21 , 2013.
iFixit. 2013b. “ Kindle Fire HD 8.9. ” http://www.ifixit.com/Guide/Kindle+Fire+HD+8.9

- Inch+Battery+Replacement/12922

. Retrieved Oct. 4 , 2013.
iFixit. 2013c. “ Samsung Galaxy S 4 Teardown

. ” http: //www.ifixit.com/Teardown/Samsung+Galaxy+S4+Teardown/13947/1#s46407

. Retrieved Oct. 23 , 2013.
iFixit. 2013d. “ Samsung Galaxy Note 10.1 Teardown

. ” http://www.ifixit.com /Teardown/Samsung+Galaxy+Note+10.1+Teardown/10144/2

. Retrieved Oct. 4
, 2013. Localytics. 2013. “ Top Android Tablet Share (Global) .” Nov. 7, 2013. http://www.localytics.com/blog/2013/fonblets

- and

- phablets

- samsung

- has

- share

- of

- android

- mobile

devices/ . Retrieved Jan. 24, 2014. Magid. 2013. “ US Tablet Owners, by Model, 2013 .” Jun. 19, 2013. http://www.emarketer.com/Article/With

- More

- Models

- on

- Market

- How

- Tablets

- Stacking

Up/1009982 . Retrieved Sept. 20, 2013.
MixPanel. 2014a. “ iPhone Models .” Dec. 23, 2013. https://mixpanel.com/trends/#report/iphone_models . Retrieved Jan. 21, 2014.
MixPanel. 2014b. “ Top tablets .” Dec. 23, 2013. h ttps://mixpanel.com/trends/#report/top_tablets/from_date:

- 52,to_date:

- 30 . Retrieved Jan. 21, 2014.
Nielsen . 2013. “ Who's Winning the U.S. Smartphone Market? ” Aug. 6, 2013. http://www.nielsen.com/us/en/newswire/2013/whos

- winning

- the

- u

- s

- smartphone

- market

- .html

. Retrieved Oct. 22, 2013.
Shirriff. 2012. “ A dozen USB chargers in the lab: Apple is very good, but not quite the best .” Oct. 27, 2012. http://www.righto.com/2012/10/a

- dozen

- usb

- chargers

- in

- lab

- apple

- is.html . Retrieved Oct. 7, 2013.
StatCounter. 2013a. “ Top Mobile Vendors in the United States .” Dec. 2013. http://gs.statcounter.com/#mobile_vendor

- US

- monthly

- 201309

- 201309

- bar . Retrieved Jan. 17, 2014
StatCounter. 2013b. “ Top Tablet Vendors in the United States .” Dec. 2013. http://gs.statcounter.com/#tablet

- vendor

- US

- monthly

- 201304

- 201312

. Jan. 24, 2014.

### 154



## B.3 Video Game Consoles

B.3.1 Installed Base
To estimate the installed base of video game co nsoles in the current study, we used the results from the CE Usage Survey (2013). In this survey we asked about the ownership of nine different video game consoles in U.S. households (see Appendix A. 5 Q

- E1). In the main body this study (see Section 3.13.1.1 ), we only presented the installed base of video game consoles available on the market before Jul. 2013. In this Appendix, we present an additional installed base estimate for Feb. 2014 that includes the recently released Sony PlayStation 4 and Microsoft Xbox One consoles ( Figure B

- 1 ).

Figure B

- 1 : Installed Base of video game consoles in Mar. 2014



### B.3.2 Usage of video game consoles including 8 th 

### generation models

Figure B

- 2 depicts our usage estimates for gaming consoles in Feb. 2014.

Figure B

- 2 : Turned ON and actively used time of video game consoles


### Figure B

- 3 present s the estimated breakdown of active

- all time among different activities. 6.1 33 5.7 22 23 5.1 42 1.6

0 10 20 30 40 50 Xbox Xbox 360 Xbox One PS 2 PS 3 PS 4 Wii Wii U

Microsoft Sony Nintendo

Millions

0 1 2 3 4 5 6 7

Xbox Wii U Xbox

One PS2 Xbox

360 PS3 Wii PS4

Left ON 5.9 3.3 2.0 2.9 1.9 1.8 2.4 1.3 Actively used 0.5 1.1 1.5 0.6 1.5 1.5 0.5 0.5 Hours

### 155

Figure B

- 3 : Distribution of active usage among gaming, video streaming and video playback by video game console platform



### B.3.3 Power Draw

Table B

- 13 summarize s the power draw values for the PlayStation 4 (PS4), included estimated pre

launch power draw (Sony 2013) and measured power draws by NRDC (2013). With the exception of

active

- media and networked standby modes, these two sources are consistent.

Table B

- 13 : PS4 Power Draws (Sony 2013, NRDC 2013)

.

Mode Manufacturer Power Draw [W] NRDC (2013) Power Draw [W]
Active

- gaming 135 a 137 Active

- media 110 b 90 d Navigation 85 88 Peripheral charging 10 c

- Peripheral charging enabled 7

- Networked standby 3.1 8.8 Standby <0.5 0.5

a Average measured while playing “Motorstorm Apocalypse

. ” b Average of power used for playback of audio CD, DV D, Blu

- ray, and media streaming.

c PS4 peripherals can be recharged while the console is powered

- d own

. d Power Draw measured while streaming Netflix

.



### Table B

- 14 presents the comparison of power draw data received from Microsoft (Calland 2014, middle column) with power measurements performed by NRDC (2013). The data from the two sources are mostly consistent, with the exception of the Standby power mode, where the measured power draw is
almost three

- times higher than the power draw provided by Microsoft.

Table B

- 14 : Xbox One Power Draws (Calland 201 4, NRDC 2013)

.

Mode Manufacturer Power Draw [W] NRDC (2013) Power Draw [W]
Active

- gaming 121 110 Active

- video playback (DVD) 80

- Active

- video streaming 72 74 Navigation 72 72 Connected Standby 18 a 18 Standby 0.45 a 1.3

a Xbox One shipped with "Conn ected Standby " enabled

-- wake

- on

- lan, wake

- on

- voice and instant

- on (OS suspended to RAM). User can opt in to "energy saving" (0.5 watt) standby mode. 0% 20% 40% 60% 80% 100%

Xbox Xbox 360 Xbox
One PS 2 PS 3 PS 4 Wii Wii U Active-Video playback

Active-Video streaming

Active-Gaming

### 156

B.3.4 Usage estimates

– Video Game Consoles
We reference specific survey questions to obtain values for varia bles in the usage model. These are indicated in bold green, e.g., <E1.1> references survey question 1, sub

- question 01 in the video game console survey. See Append ix A

– CE Usage Survey s for the survey questions. The following tab le includes the questions that we used in the energy model calculation (e.g. E3

– E5).

Table B

- 15 : Variables directly measured in the CE Usage Survey

.

Survey Question Purpose Measure Variable
E3.## Turned ON and Active Usage time ... Active and ON time Time (hh:mm)
C2. 01 Turned ON
C2. 02 Actively used
E4.## Distribution of active usage time... Usage time Time (hh:mm)
C2. 01 Play games

C2. 02 Stream media from t he video game console or Internet

C2. 03 DVD and/or Blu

- Ray playback

E5.## Initial state of the Video Game Console in the morning... Left ON 24 hours Probability
C2 01 1 It was already turned ON and rea dy to use
C2 02 It was turned OFF and you needed to turn it on to use it
C2 99 Don’t know



### B.3.4.1 Calculations of Time Spent in Operational Modes

Video game consoles have three primary op erational modes, i.e., active, navigation and standby

. In our study, the active mode includes time spent gaming, streaming video, and video playback (see Video Game Systems 3.13 ). We de clare these as variables in this model (see Table B

- 16 ).

Table B

- 16 : Variables for power draw and time threshold of various operational modes

.

Operational Mode Active

gaming Active

streaming Active

pla yback Navigation Standby

Power Draw Time in modes



### In the CE Usage Survey (2013), w e asked respondent to estimate the time each video game console was

on “yesterday” and was used for gaming, streaming video, and video playback.

Not infrequently, the sum of times spent in the different active

- use modes did not equal the active use
estimat e. Consequently, if is less than the sum of the time spent gaming, streaming, and video playback, we assumed that instead equaled that sum, i.e.:

 If then

. Similarly, we then adjusted the on

- mode time, , for each individual response if was less than

so that equals

.

### 157

To determine whether or not a video game console stayed on all the time, we analyzed each individual response to survey question <E5>
, i.e., whether or not the console was already o n the last time the respondent was the first person to use the console on a day. Our data analysis logic follows, where the

answer “

- 1” represents a “don’t know” reply by the respondent :

 If then and ;

 If then and

, i.e. video game c onsole was not used yesterday;

 If then and , where “average time” is the weighted average time video game console was actively used yesterday and is calculated as described above;

 If then before adjustments and before adjustments;

 If then ( ) and

. The weighted average hour s spent in on and active modes equals the sum of the individual responses, applying the appropriate survey weight, N w 

### , for each respondent: ∑

where

 is weight of the th survey response

 is number of survey responses

 is the number of a particular response

Finally, the time video game consoles spent in navigation mode was calculated as the difference between the time spent in on mode and the time video game consoles were actively used, i.e.,

.

B.3.5 References Calland, T. 2014. Personal Communication. Microsoft. Feb. Sony. 2013. Personal Communication. Dec. NRDC. 2013. “New PS4 and Xbox One Game Consoles: A Mixed Bag for Energy Efficiency.” Switchboard.
Dec. http://switchboard.nrdc.org/blogs/nhorowitz/new_ps4_and_xbox_one_game_cons.html

### 158



## B.4 Home Audio In this appendix, we present in

- store power mea surements of speaker docks and stereo shelf systems performed in Jan. 2014.

B.4.1 Speaker Docks

Table B

- 17 : Power d raw measurements of speaker docks

. Active Modes [W] Active iPhone Active Tuner Active Standby Off Min. Medium Max. Min. Medium Max. [W] [W] Stereo System 1 * 5.6 5.4 6.6 4.1 6.3 3.3 1.9 5.6 Stereo System 2 ** 3.3 4.5 7.8

- - 1.9 0.4 3.3 Stereo System 3 #

- - - - - - 1.1

- Wt . Avg. 5.0 5.2 6.9 4.1 6.3 3.0 1.3 5.0 Wt. Avg

. 4.8 3.0 1.3
* This speaker dock has a p lug

- in connection for an iPhone 5. Since we did not have an iPhone 5 available when making the measurements, we were unable to measure power draw in active modes.



### B.4.2 Shelf Stereo Systems

Table B

- 18 : Power d raw measurements of shel f stereo systems

. Active Modes [W] Active iPhone Active Tuner Active Standby Off Min. Medium Max. Min. Medium Max. [W] [W] Stereo System 1 * 14 15 28 12 14 40 13 0.3 Stereo System 2 ** 12 13 52 12 15 70 10 0.1 Stereo System 3 # 18 19 28 18 18 53 13 0.5
Wt . Avg. 15 16 34 14 15 51 12 0.3 Wt. Avg

. 17 12 0.3

* Output power = 220W.

** Output power = 500W. # Output power = 700W.