Energy and Carbon Impacts of ICT
- User Guide for the
SusteIT Footprinting Tool
Updated August 2009
Lisa Hopkinson and Peter James
SusteIT and University of Bradford
Contents
1.
2.
3.
4.
5.
6.
7.
Introduction ............................................................................................................................... 2
Description of the Tool .............................................................................................................. 2
Using the Tool ........................................................................................................................... 3
Results Displayed ..................................................................................................................... 5
Sheffield Worked Example ........................................................................................................ 6
Estimating the Number of Devices ............................................................................................ 6
Estimating the Power Rating of Devices .................................................................................... 7
7.1
Comparison with Energy Star 5 for Desktops .................................................................... 9
8. Estimating Server and High Performance Computing Air-Conditioning and Other Overheads 10
9. Estimating the Usage of Devices ............................................................................................. 11
10.
Assumptions........................................................................................................................ 12
11.
Disclaimer ........................................................................................................................... 16
12.
References .......................................................................................................................... 16
Acknowledgements
SusteIT wishes to thank Chris Cartledge for his analysis of the Sheffield ICT energy footprint, and all
his colleagues at the University of Sheffield who provided assistance and data, particularly Chris
Sexton, Cliff Woodcraft and Phil Riley.
© SusteIT, 2009
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1.
Introduction
This guide accompanies an Excel tool which is designed to help Further and Higher Education
(FHE) Institutions estimate the in-use energy consumption, costs and carbon footprint of their nonresidential ICT usage. It has been produced by the SusteIT project. This is funded by the Joint
Information Services Committee (JISC), and is co-managed by the Higher Education Environmental
Performance Improvement (HEEPI) project and SustainIT, an NGO (see www.heepi.org.uk and
www.sustainit.org). It can be used freely, provided that the source is attributed, and that the whole
spreadsheet, or it accompanying text, is not incorporated into other materials.
The tool uses three variables to calculate an energy footprint:
(1) Numbers of devices
(2) Power consumption data for individual types of device (watts, either measured or taken from
manufacturer’s data)
(3) Usage data of devices in a FHE setting (hours/year).
This in turn is used to estimate energy costs and carbon emissions associated with ICT usage. The
final results are designed to provide a reasonable estimate of the overall magnitude of
electricity/carbon used. They should be seen as a first step to highlight areas of high energy usage
within the ICT estate, or areas of uncertainty where further work is required to refine the data.
Please read section 11, Disclaimer, for some detailed caveats.
The current version of the tool, and the assumptions it contains, are largely based on a detailed
analysis of the energy footprint of non-residential ICT devices at the University of Sheffield.1 We
believe that this provides the most detailed analysis to date of ICT-related energy consumption in a
higher education institution. The Sheffield data is included in the tool for reference purposes, in the
worksheet “Sheffield worked example”.
The Sheffield analysis has been supplemented by ‘reality checks’ with other institutions to ensure
that the categories, and assumptions being used, are widely applicable. The tool has been updated
in the light of feedback from other institutions.
2.
Description of the Tool
The tool is a simple Excel spreadsheet which contains the following worksheets (numbered in the
spreadsheet):
1. Menu – to aid navigation and to measure progress in completing the various worksheets
2. Read Me – contains detailed step by step instructions (see Section 3 of this User Guide)
3. Assumptions – provides all the default figures and how they were derived (see Section 10
of this User Guide)
4. Sheffield Worked Example – contains a worked example for the University of Sheffield
(see Section 5 of this User Guide)
5. HPC – Enter data on departmental and central high performance computing plus
cooling/power supply overhead
Cartledge, C., 2008. Energy Impacts of ICT at the University of Sheffield, Bradford: SusteIT, July,
2008. Downloadable from www.susteit.org.uk.
1
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6. Server Rooms – Enter data on central and departmental servers plus storage and
cooling/power supply overhead
7. PCs and Monitors – Enter data on PCs, laptops, thin clients and monitors
8. Networks – Enter data on hubs, switches, routers and Power Over Ethernet
9. Phones – Enter data on PABX and VOIP phones power supply/cooling overhead for PABX
10. Imaging – Enter data on printers, copiers, scanners, faxes
11. AV – Enter data on projectors, OHP and plasma screens
12. Total and Analysis – Displays results for energy use, energy cost and carbon dioxide
emissions broken down by category of device
13. Energy Use – Provides graphic displays of energy use broken down by category of device
14. Energy Cost – Provides graphic displays of energy cost broken down by category of device
15. CO2 Emissions – Provides graphic displays of carbon dioxide emissions broken down by
category of device
16. ICT in the University – compares ICT energy, energy costs and carbon dioxide emissions
to total institutional non-residential electricity use, electricity costs and carbon dioxide
emissions
17. Tool – allows users to enter the data directly into a single sheet rather than individual sheets
if preferred. The data from the individual sheets is also fed into this sheet automatically.
Worksheets 2-4 above are informational only.
Worksheets 5 – 11 are the main worksheets requiring data input on numbers of devices and, where
available, data on power and usage. They each have a similar format.
Worksheet 12 displays results for worksheets 5-11 based on default assumptions for electricity
costs and carbon dioxide emissions. These defaults can be amended if required.
Worksheets 13-15 displays bar and pie charts of the results for worksheets 5-11.
Worksheet 16 require data input on the total (non-residential) electricity use, electricity costs and
carbon emissions for the institution and displays ICT as a proportion of those.
3.
Using the Tool
The tool can be used in two ways:
The ‘quick and simple’ method (blue area of worksheets 5-11).
This only requires a number (which can be estimated) for each of the different types of ICT device.
The spreadsheet then uses default assumptions of power ratings and usage (and default electricity
costs and carbon dioxide emissions) to estimate the total energy consumption (kWh/y), energy
costs (£) and carbon dioxide emissions (kg/kWh) of the ICT devices in the worksheet labelled “Total
and Analysis”.
The ‘thorough’ (and more accurate) method (yellow area of the worksheets 5-11).
In addition to numbers of devices, this enables users to enter institution-specific data on the power
rating of equipment, and typical usage hours. The assumptions used to obtain the default settings
for power and usage are described below, and also summarised in the worksheet labelled
“Assumptions”.
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Quick and Simple Method
Step 1: Working with relevant staff (IT management, energy management, print management,
academics, library/learning support, research staff) gather data on the number of ICT devices at
your institution.
Step 2: Use the “Menu” worksheet to navigate around the spreadsheet. For each individual
category of ICT device, go to the relevant worksheet and enter estimates of the number of ICT
devices at the university, including departmental devices. Use the “Menu” worksheet to measure
progress as you complete each individual worksheet.
Step 3: Once you have entered all the data in the worksheets 5-11, the tool will provide a
breakdown of ICT energy use by category and total energy consumption in the worksheet “Total and
Analysis” with graphical displays in the worksheets “Energy use”, “Energy Cost” and “CO2
Emissions”. If required you can amend the default electricity price and carbon dioxide emission.
Step 4: In the “ICT in the University” worksheet enter data on total institution (non-residential)
electricity use, electricity cost and electricity-related carbon emissions. Check the total ICT energy
consumption estimate against the total non-residential electricity usage for the institution to see if it
appears to be a reasonable proportion (e.g. between 10-50%). If very low or very high you may
need to check the assumptions used.
Once you have entered all the data, the tool will provide a breakdown of ICT energy use, energy
costs and carbon emissions in the worksheet “Total and Analysis” with graphical displays in the
worksheets “Energy use”, “Energy Cost” and “CO2 Emissions”.
Thorough Method
Step 1: Working with relevant staff (IT management, energy management, print management,
academics, library/learning support) gather data on the number, type and typical usage of ICT
devices at your institution.
Step 2: Use the “Menu” worksheet to navigate around the spreadsheet. For each individual
category of ICT device, go to the relevant worksheet and enter estimates of the number of ICT
devices at the university, including departmental devices in worksheets 5-11 for individual
categories. Use the “Menu” worksheet to measure progress as you complete each individual
worksheet.
Step 3: If your institution uses some form of powersave management to put computers into a lower
power mode (e.g. hibernate, sleep or standby) after a certain period or at a certain time, then you
need to estimate what proportion of PCs are affected, both in computer suites and in departments.
This will affect the usage hours in a particular energy mode (i.e. computers with powersave
management typically spend less time in active/idle mode). You will then need to adjust the usage
hours in active mode in the yellow area of the worksheet “PCs and monitors” accordingly (the hours
in standby mode will adjust automatically).
Step 4: Check the usage assumptions in the “Imaging” and “AV” worksheets and adjust in the
yellow area of the worksheet where necessary.
Step 5: Check if your institution has any data on the overheads as shown in Table 1 and amend the
default value where appropriate in the relevant worksheet.
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Table 1: Default values for the overheads used in the tool
Worksheet
Overhead
HPC
Cooling
HPC
Power supply
Servers
Storage and other equipment
Servers
Cooling
Servers
Power supply
PCs & Monitors
Cooling (for airconditioned computer
suites only)
Phones
PABX cooling and power supply
Cell
E8
E9
E7
E9
E10
H19
Default value
0.425
0.075
0.15
0.425
0.075
0
E6
0.1
Step 6: Check the tool's default figures for power ratings (watts) for the different devices in
worksheets 5-11 (see Table 6 for summary), and see if these appear reasonable based on the
typical devices used at your institution. If too low or too high, change the default settings in the
yellow area of worksheets 5-11. If you are unsure, estimate a range of energy consumption based
on separate calculations using low and high power ratings.
Step 7: Check the tool's default figures for usage (hours per year) for the different devices in
worksheets 5-11(see Table 7 for summary), and see if these appear reasonable based on usage
patterns at your institution. If too high or too low, change the default settings in the yellow area of
the tool. If you are unsure, estimate a range of energy consumption based on separate calculations
using low and high usage rates.
Step 8: In worksheet “Total and Analysis” check the default figures for electricity costs (p/kWh) and
carbon dioxide emission factor (kgCO2/kWh) and change if necessary. The former is based on a
typical figure for 2008/09 (including VAT). The latter is based on Defra’s 2008 conversion factor for
grid electricity which is a rolling average of the last five years and is updated annually. Institutions
with Combined Heat and Power (CHP) should use the conversion method in Defra’s Guidelines.
Step 9: In the “ICT in the University” worksheet enter data on total institution (non-residential)
electricity use, electricity cost and electricity-related carbon emissions. Check the total ICT energy
consumption estimate against the total non-residential electricity usage for the institution to see if it
appears to be a reasonable proportion (e.g. between 10-50%). If very low or very high you may
need to check the assumptions used.
Once you have entered all the data, the tool will provide a breakdown of ICT energy use, energy
costs and carbon emissions in the worksheet “Total and Analysis” with graphical displays in the
worksheets “Energy use”, “Energy Cost” and “CO2 Emissions”.
4.
Results Displayed
Once the required data has been entered in worksheets 5-11, the results will be displayed in
numerical form in the worksheet “Total and Analysis” or graphical format in worksheets ““Energy
use”, “Energy Cost” and “CO2 Emissions”. See examples below in Figure 1 and 2 for energy use.
© SusteIT, 2009
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Figure 1: Example Pie Chart of Energy Use
Figure 2: Example Bar Chart of Energy Use
E nerg y Us e
(kWh/y)
E nerg y Us e (kWh/y)
HP C
14%
26%
S ervers
PCs
17%
400,000
200,000
0
Networks
19%
20%
3%
H
S e PC
rv
er
s
Ne P C
tw s
T e .. .
le
Im ...
ag
in
g
AV
P hones
0%
Imaging
AV
5.
Sheffield Worked Example
This worksheet contains a worked example by Chris Cartledge from the University of Sheffield and
can be used for comparison purposes. See summary data for the university below.
Table 2: Summary of results from the University of Sheffield (Cartledge 2008)
Category
HPC
Servers
PCs & Monitors
Networks
Phones
Imaging
AV
Energy Total (Kwh/y)
1,208,617
1,520,736
4,164,477
687,362
202,356
835,659
61,598
TOTAL ICT ENERGY 8,680,806
& CARBON
6.
%
14%
18%
48%
8%
2%
10%
1%
Total CO2 (kg/y)
649052
816666
2236408
369127
108669
448765
33080
100%
4,661,766
Estimating the Number of Devices
As a minimum the tool requires you to input the number of each type of ICT device at your
institution. However, this is not a straightforward exercise, since few institutions hold central records
of how many devices they have. Hence, you may need to ‘guesstimate’. You should liaise closely
with colleagues in IT management, procurement, print management, library/learning support
services, estates and academic departments to ensure the data is as accurate as possible.
The following are recommended as sources of data:
1.
2.
3.
High Performance Computing – IT research staff, estates (for air conditioning load)
Servers - IT management staff and Heads of research-intensive departments, estates
(for air conditioning load)
PCs and Monitors – IT management staff, library/support service staff, ICT procurement
staff. Interviews with selected departments. Estimates can also be made of the number
of IP addresses allocated to devices that are not network devices or printers. Institutions
with power management software should also be able to estimate the numbers of
devices connected.
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4.
5.
6.
7.
Networks – IT management staff, IT procurement staff
Phones – IT management staff, IT procurement staff
Imaging devices – print management staff, library/support services staff, central printing
staff or organisations, interviews with selected departments.
Audio-Visual equipment – library/support service staff, IT procurement staff, Head of
learning/teaching
Where appropriate it may be useful to contact support staff in key academic departments to
estimate the number of local devices or do walk-through surveys. If buildings have electricity submeters it would be worth checking the estimated energy consumption for that department’s ICT
equipment against the total electricity consumption of the building as a reality check.
If for some reason an estimate of numbers of devices is not obtainable, a very crude estimate of
numbers of devices can be obtained using the following simple rule of thumb estimates, very loosely
based on the University of Sheffield,:







7.
1 computer for every 8-10 students
1 computer for every 1 employee
2 phones for every 1 employee
1 laser printer for every 20 students
1 laser printer for every 5 employees
1 large photocopier (or MFD) for every 50 students
1 small photocopier for every 20-25 employees.
Estimating the Power Rating of Devices
The tool provides default figures for the power rating of different generic devices. Unless specified
these were based on measured figures obtained from the University of Sheffield. However, the
figures in the tool are rounded up, and therefore vary slightly from the figures in the Sheffield worked
example worksheet.
Due to the wide range of equipment that is potentially in use for a given category, even within a
single university or college, it is impractical to measure or estimate the energy usage associated
with each and every device. However, based on the most typical models in use, it is recommended
that users estimate or do some sample measurements of power. This is particularly important for
computers due to the fact these are likely to use the most electricity of any ICT equipment on
campus. Measurements are preferred due to the fact that the power measured frequently varies
from the manufacturers published figures (at Sheffield it was found that measured data is typically
lower).
At the University of Sheffield measurements were made with a proprietary power monitor.2 These
units are simple to use and give repeatable results except where the power being measured is
varying significantly or is very low.
For computers and imaging equipment in particular it is important to estimate/measure the power
consumption in different modes. For example, while devices tend to use most energy in “active”
mode, i.e. when being used intensively, they actually spend most of their time in lower energy
modes such as idle, hibernate, sleep or standby. However, finding out what the power consumption
Maplin Plug-in Mains Power and Energy Monitor, Reference L61AQ, about £28 at the time of
writing – see www.maplin.co.uk/Module.aspx?ModuleNo=38343&&source=14&doy=21m5.
2
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is in different modes and how quickly each device returns to each mode is not easy. The problems
are compounded by the fact that there are no universally agreed industry definitions of the different
power modes. Tables 3 and 4 below show the energy modes as defined by recent versions of
Energy Star. To compound matters further, even the same model of computer can have different
power consumption depending on the software and application running.
Table 3: Comparison of different energy/modes for computers as defined by Energy Star3
Mode
Energy Star computers, Version 5.0
Idle
The operating system and other software have completed loading, a user profile has
been created, the machine is not asleep, and activity is limited to those basic
applications that the system starts by default.
A low power state that the computer is capable of entering automatically after a
period of inactivity or by manual selection. A computer with sleep capability can
quickly “wake” in response to network connections or user interface devices with a
latency of ≤ 5 seconds from initiation of wake event to system becoming fully usable
including rendering of display. For systems where ACPI standards are applicable,
Sleep mode most commonly correlates to ACPI System Level S3 (suspend to RAM)
state.
The power consumption level in the lowest power mode which cannot be switched
off (influenced) by the user and that may persist for an indefinite time when the
appliance is connected to the main electricity supply and used in accordance with
the manufacturer’s instructions. For systems where ACPI standards are applicable,
Off Mode correlates to ACPI System Level S5 state.
Sleep
Off
Table 4: Comparison of different energy/modes for monitors as defined by Energy Star4
Mode
Energy Star Displays Version 5.0
On Mode
The operational mode of a display that is (i) connected to a power source, (ii) has all
mechanical (hard) power switches turned on, and (iii) is performing its primary
function of producing an image.
The operational mode of a display that is (i) connected to a power source, (ii) has all
mechanical (hard) power switches turned on, and (iii) has been placed into a lowpower mode by receiving a signal from a connected device (e.g. computer, game
console, or set-top box) or by cause of an internal function such as a sleep timer or
occupancy sensor. Sleep Mode is considered a “soft” low-power condition, in that
the display can be brought out of Sleep Mode by receiving a signal from a
connected device or by cause of an internal function.
The operational mode of a display that is (i) connected to a power source, (ii)
engaged by a power switch, and (iii) not providing any function. The user must
actuate a mechanical switch to bring the device out of Off Mode. If there is more
than one such switch, the tester shall use the most readily available switch.
Sleep Mode
Off Mode
For the analysis at the University of Sheffield the following power states were defined for PCs:
Intense - when the machine is actively doing arithmetic on a large dataset and writing results back
to disk.
Idle - after the PC has been booted up and is waiting for keyboard input.
Standby (for wake-on LAN) or Hibernate – electricity generally similar to off state.
Off - when the mains to the machine is powered up (and any power supply switch is on) but the
machine has not been powered on at the front panel.
3
4
EU Energy Star website. Available at: www.eu-energystar.org/en/index.html.
EU Energy Star website. Available at: www.eu-energystar.org/en/index.html.
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To simplify matters the tool defines only 2 energy states:
Active/idle – for PCs and imaging equipment, the active and idle energy states have been
combined, with the idle figures used as a proxy for active power consumption. In practice PCs are
rarely intensely used (for example when starting up, calculating a very large spreadsheet, searching
a huge file or rendering a 3-dimensional model). While at Sheffield the idle figures were adopted as
appropriate for energy in active mode, it was assumed that no time was spent actually in idle mode
because the devices were found to powerdown to lower energy modes very quickly. It is not clear
whether this is the case at other institutions.
Standby – this corresponds to the “Off” mode in the Energy Star definition or the “Off” state in the
Sheffield definition. The tool assumes that devices spent no time in a hard “off” state, i.e. they are
not switched off at the mains at night, weekends or vacation periods. Institutions that do switch off
devices at the mains during these times should adjust the total active/standby hours in the yellow
area of the tool accordingly – currently they add up to 8,760 hours per year (365*24). For example,
if a device is switched off at the mains for 4 weeks of the year then the total active/standby hours
should be adjusted to 8,064 hours (336*24).
7.1
Comparison with Energy Star 5 for Desktops
The latest version of the Energy Star desktop specification which came into effect 1 July 2005 uses
a method of testing and comparing the energy performance of computers, which focuses on the
typical electricity consumed by a product while in normal operation during a representative period of
time. The Total Energy Consumption (TEC) for desktops and notebooks is based on the following
formula:
ETEC = (8760/1000) * (Poff * Toff + Psleep * Tsleep + Pidle * Tidle)
where Px are power values in Watts, all Tx are time values in % of year, and ETEC is annual energy
consumption in kWh.
The time the computer spends in each operational mode is shown in the table below:
Table 5: Final Energy Star V 5.0: Operational Mode Weighting – Desktops and Notebooks
Desktop
Laptop
Conventional
Proxying (a)
Conventional
Proxying (a)
Toff
55%
40%
60%
45%
Tsleep
5%
30%
10%
30%
Tidle
40%
30%
30%
25%
(a) Proxying refers to a computer than maintains Full Network Connectivity as defined by Energy
Star.
For simplification the SusteIT tool does not include any allowance for time spent in sleep mode but
as this represents less than 10% of operational time in the Energy Star methodology is unlikely to
affect the results significantly.
The usage hours in the SusteIT tool also vary to match a typical institution’s patterns for different
devices. However for a standard desktop the default usage hours spent in idle mode in the SusteIT
tool (42% - see Table 5) is not dissimilar from the conventional desktop in Energy Star 5 (40%).
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8. Estimating Server and High Performance Computing AirConditioning and Other Overheads
In heavily serviced areas such as server rooms or high performance computer rooms, allowance
needs to be made of the electricity associated with cooling and power supply.
At Sheffield the central server room electricity is covered by uninterruptible power supplies (UPS)
that can report instantaneous power (or current) figures. Thus a measurement was obtained that
covered all the server support equipment. It was not possible to separate out the contribution from
the air-conditioning and UPS, so an overhead of 40% was used based on estimates of the power
rating of equipment and the Coefficient of Power (COP) of typical units in use.
However, figures in the literature suggest that the Sheffield overhead is unusually low. Indeed, one
supplier states that an overhead of 100% is more typical in data centres which have taken no
account of energy efficiency (Emerson, 2007). The default figure used in the tool is therefore a
‘compromise’ of 50%, based on figures of 40-45% for air-conditioning, and 5-10% for power losses
(see Section 7: Summary of Assumptions Used). Users can obviously adjust the figure if they have
taken special measure such as well designed hot aisle/cold aisle arrangements.
The tool applies a cooling overhead of zero to normal computer suites/rooms used by students on
the grounds that they are not normally air conditioned. If computer suites/rooms are air-conditioned
an overhead percentage needs to be made in the worksheet “PCs and Monitors” in the line labelled
“Aircon overhead for computer suites” (in cell H19). This in turn needs to be multiplied only by the
total energy of the computers and monitors in computer suites – the tool assumes as a default that
this is student managed PCs plus the same number of CRT monitors (see calculation in cell I19) but
this should be amended accordingly.
Table 6: Summary of default power rating for active/idle and standby modes used for all
devices in the tool
Device
Energy (kWh)
High Performance Computing
Departmental or central HPCs
Servers
Departmental or central servers
Other server equipment (e.g, storage, communications etc)
Computers
PCs and workstations– high performance
PCs medium performance – standard and managed
PCs- low power – standard and managed
Portable (laptops)
Thin clients
Monitors
CRT
LCD/TFT
Networks
Cabinet based edge switches
Cabinet based aggregation switches
Cabinet based core switches
Cabinet based wireless access points
Room based hubs
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Active/idle
Standby
300
n/a
300
15% of total server
power
n/a
100
60
30
30
7
2
2
2
2
7
70
35
5
2
50
100
600
16
4
n/a
n/a
n/a
n/a
n/a
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Room based unmanaged edge switches
Phones
PABX distributed
VOIP
Imaging
Central services
High volume copiers
High volume printers
Student photocopiers
Departmental
High/medium volume copiers/MFDs
Low/medium copiers/MFDs
Shared monochrome laser printers
Shared colour laser printers
Scanners
Faxes
Personal
Personal laser printer
Personal inkjet printer
MFD
Audio-visual
Projectors
OHP
Plasma screens
9.
25
n/a
2
8
1
8
1200
800
1000
30
15
30
1000
600
450
600
12
30
20
15
30
2
1 kWh per week
350
20
500
10
6
10
300
300
700
8
2
3
Estimating the Usage of Devices
Estimating the usage (number of hours per year each device spends in a particular power mode) is
perhaps the most difficult area of all, again due to the fact that this varies widely with device, user
(staff/student), department and time of year.
The tool assumes that some devices are “on” 24/7, 52 weeks a year, for example servers, high
performance computers, networks and phones. Usage assumptions for the remaining devices is
shown in Table 6.
At Sheffield it is assumed that for 52 weeks of the year devices are always “on” – either active/idle
or standby. This is the default in the tool however if institutions think a shorter (e.g. 48 week year) is
more appropriate (e.g. for 4 weeks of the year devices are turned off at the mains so drawing zero
Watts) then they should make the changes to the hourly figures accordingly (i.e. adjust the active
and standby usage in the yellow area of the tool so it totals, say, 8,064 hours rather than 8,760
hours per year). The difference in active usage hours between monitors and PCs is because most
monitors power down to standby after 20 minutes regardless of whether the PC is managed or not.
Usage figures for networked devices (PCs, printers) may be obtained using various administrative
software. For example at the University of Sheffield the manufacturer’s software for printers was
used to scan printers and obtain an estimate of the device type and number of pages printed over a
given period of time. This in turn was used to estimate hours of usage based on typical printer
speeds. Power management software can also be used to obtain figures on length of time each PC
is in low power mode. For unmanaged devices proprietary software can be installed to monitor
energy consumption and estimate average usage as a result.
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Table 7: Summary of default usage hours for all devices in the tool
Device
High
Performance
Computing
Departmental or central HPCs
Server Rooms
Departmental
or
central
servers
PCs
Standard PCs, low power
green
PCs
and
high
performance
PCs
and
workstations
Managed standard and student
(standard and green) and thin
clients
Monitors
All monitors
Networks
All devices
Phones
All devices
Imaging
Central High volume copiers
and printers
Student photocopiers
Departmental High/low volume
photocopiers/MFDs
Departmental networked laser
printers (b/w and colour)
Personal laser and inkjet
printers/MFDs
AV
Projectors/OHP
Plasma screens
Active
Usage
(hours per
week)
(a)
Standby
usage
(hours per
week)
(b)
Weeks
year
per
Standby
usage (hours
per year)
(c)
Active
usage
(hours per
year)
(a*c)
52
8,760
n/a
52
8,760
n/a
b*c)
70
98.5
52
3,640
5,120
40
128.5
52
2,080
6,680
40
128.5
52
2,080
6,680
52
8,760
n/a
52
8,760
n/a
40
128
52
2,080
6,680
19.2
57.7
52
1,000
3,000
10
158.5
52
520
8,240
10
158.5
52
520
8240
1.67
(i.e.
20
mins/day)
166.7
52
87
8673
25
143
40
52
520
8,760
8,240
n/a
10. Assumptions
Below are the different categories of ICT equipment and the assumptions used to obtain the default
data in the yellow area of the tool. The alphabetical numbering system refers to the reference in the
tool. This can also be found in the worksheet labelled “Assumptions”.
Text in italics indicates where the HEEPI tool assumptions deviate from the Sheffield data.
High Performance Computing (HPC)
For research-intensive institutions only:
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(a) Watts per unit: 300 W, based on measurements made on individual HPCs at University of
Sheffield of 270W rounded up.
(b) Aircon overhead: +50%. Based on general experience at universities of an air conditioning
overhead of 40-45% and power supply losses associated with the UPS of 5-10%.5 A median figure
of 50% was adopted to account for both. For well managed server rooms a lower overhead of 4045% may be used. At the University of Sheffield a figure of 40% was used.
(b1) Based on the range in (b) above a median value of 42.5% was used for the cooling overhead.
(b2) Based on the range in (b) above a median value of 7.5% was used for the power supply
overhead.
Server rooms
(c) Watts per unit: 300W, based on measurements made on individual High Performance
Computers (as a proxy for servers) at the University of Sheffield of 270W rounded up. At University
of Sheffield a total measured figure for all server equipment was available only with no breakdown
based on numbers of servers or equipment.
(d) Other server equipment. A figure of 15% of total server power was used based on Emerson
(2007) (see References below). At the University of Sheffield a total measured figure for all server
equipment was available only with no breakdown based on numbers of servers or equipment.
(e) Aircon overhead: +50%. Based on general experience at universities of an air conditioning
overhead of 40-45% and power supply losses associated with the UPS of 5-10%.6 A median figure
of 50% was adopted to account for both. For well managed server rooms a lower overhead of 4045% may be used. At the University of Sheffield a figure of 40% was used.
(e1) Based on the range in (e) above a median value of 42.5% was used for the cooling overhead.
(e2) Based on the range in (e) above a median value of 7.5% was used for the power supply
overhead.
PCs and Monitors
(f) Watts per unit for active/idle power consumption were based on measurements made on
individual computers at the University of Sheffield, rounded up. The idle power rating was adopted
as most PCs spend most of their time in this mode. Typically idle mode for a desktop can range
between 40-90W. Standby mode for a desktop is typically between 1-3 W. Laptop power is typically
lower. Power use for monitors was based on measurements at the University of Sheffield. Thin
client power was based on measurements of SunRay units without a monitor which use around 7W
on a 24/7 basis. Further details can be found in the accompanying report on the University of
Sheffield.
General consensus amongst delegates to Sustainable IT in Universities and Colleges - Energy
Efficient Configuration, Cooling & Power Supply in Data Centres, HEEPI event, University of
Cardiff, 19 June 2008.
6 General consensus amongst delegates to Sustainable IT in Universities and Colleges - Energy
Efficient Configuration, Cooling & Power Supply in Data Centres, HEEPI event, University of
Cardiff, 19 June 2008.
5
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(g) Hours per year in use for active/idle and standby were based on the following:
Managed computers (i.e. PCs are powered down automatically by the network after a certain time in
idle mode and hence spend more time in standby) are in active/idle mode for 40 hours per week, 52
weeks a year (i.e.2,080 hours/year), and in standby for the remaining hours of the year.
Unmanaged computers in computer suites and departments are in active/idle mode for 70 hours per
week, 52 weeks per year (i.e. 3,640 hours/year) (and in standby for the remaining time).
Laptops and monitors are active/idle for 40 hours per week, 52 weeks per year (i.e. 2,080
hours/year) as the default on most operating systems tends to power them down to standby after 20
minutes.
(g1) A cooling overhead can be added if computer suites are air-conditioned. The tool uses a default
value of zero as it assumes computer suites are not generally air-conditioned. However if computer
suites are air-conditioned it is suggested overheads of 30-50% can be used.
Networks
(h) Power usage for network equipment was based on measurements at the University of Sheffield,
rounded up.
Phones
(i) Watts per PABX distributed phone were based on measurements at the University of Sheffield of
1.75W, rounded up.
(j) An overhead of 10% for cooling and power supply was made for the extra electricity used by the
UPS units based on estimates at the University of Sheffield.
(k) Locally powered VOIP phones were assumed to use 8W per phone based on a CISCO IP phone
(5 W per phone and 3W per Ethernet port) (Cartledge, 2007). The University of Sheffield does not
have any VOIP phones.
Imaging Devices
Central Services
(l) High volume copiers power use in active and standby mode were based on the University of
Sheffield figures, rounded up, for a student photocopier. UK usage figures (MTP, 2007a) suggest
that a non-domestic copier is active for 27 hours a week and idle for 13 hours a week, therefore it
was assumed that central photocopiers are active/idle for 40 hours a week, 52 weeks a year (i.e.
2,080 hours/year). Assumed to be on standby for the remaining time.
(m) High volume printer power use in active and standby mode was based on MTP (2007) (see
References below) UK average stock figures for a 2007 non-domestic laser printer, rounded up. Onactive and on-ready power was weighted using a ratio of 1:3 to give a weighted power figure in
active/idle mode of 475 W. Usage was based on an assumption of active/idle mode for 40 hours per
week, 52 weeks a year. The remainder is assumed to be standby.
(n) Student photocopiers power rating was based on the University of Sheffield figures for Sharp
copiers, rounded up and estimated usage figures.
Departmental
(o) High/medium and low/medium volume copiers power rating was based on University of Sheffield
figures for Sharp departmental copiers, rounded up. The active/idle mode power consumption was
© SusteIT, 2009
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estimated from a fluctuating measured value as each sheet of paper is printed, while the standby
figure was measured. The devices were found to return to standby anywhere between 30 seconds
or 20 minutes after last use. It was assumed that devices would be copying for two hours a day, 5
days a week or 520 hours per year.
(p) Departmental shared laser printers (monochrome and colour) power rating was based on the
University of Sheffield measured figures for active and standby mode, rounded up. It was assumed
devices would be printing for two hours a day, 5 days a week or 520 hours per year, based on
experience at the University of Sheffield.
(q) Scanners power rating based on maximum sleep power rating for EU Energy Star scanners of
5W (EU Energy Star, 2006). Sleep mode is assumed to be similar to idle mode. Standby power was
assumed to be 2W. Usage was based on active use for 1 hours a day, 5 days a week, 52 weeks a
year, idle for 7 hours a day, 5 days a week, 52 weeks a year. Assumed to be on standby for the
remaining time. No figures available from the University of Sheffield.
(r) Fax power rating based on database for EU Energy Star faxes (EU Energy Star, 2008) which
typically use less than 1 kWh/week. Note that these are the most energy efficient faxes on the
market so this may be an underestimate of typical use. No figures available from the University of
Sheffield.
Personal
(s) Monochrome laser printer and inkjet printer power rating based on University of Sheffield
measured figures and estimated usage of 20 minutes active use per day, 5 days per week, 52
weeks per year (i.e. 87 hours per year).
(t) Personal MFD power rating based on MTP (2007) (see references below) UK 2007 stock
average figures for a domestic laser MFD. An average of ‘on-active’ and ‘on-ready’ power was used
for active mode, and ‘sleep/off’ for standby mode. Usage was assumed the same as (s) above.
Audio-Visual Devices
(u) Projectors and OHP power use based on manufacturer’s stated data for active use and
measured data for standby power for devices at the University of Sheffield, rounded up. Teaching
hours is based on 5 hours a day, 5 days per week for 40 weeks a year (i.e. 1,000 hours per year)
and using Space Management Group figures that central teaching space is used for around half the
time, it was assumed that AV equipment was used for around half the teaching time, i.e. 500 hours
a year.
(u1) Plasma screens based on power consumption for typical 61" plasma screen. However power
rating would need to be increased or decreased for larger and smaller screens respectively. E.g 84"
screen typically 1100W,42" screen typically 275W. Assumed that these are run 24/7 but adjustment
would need to be made for screens powered down with timer switches to standby. There are no
plasma screens at the University of Sheffield.
Electricity Costs
(v) Energy costs are based on a nominal electricity price of 12 p/kWh (incl. VAT)
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Carbon Dioxide Emissions
(w) Carbon dioxide (CO2) emissions are based on Defra's 2008 conversion factor of 0.53702
kg/kWh for grid electricity contained in Annex 3 of Defra’s Guidelines for Greenhouse Gas
Conversion Factors for Company Reporting (Defra 2008). This is a UK average figure. Note this
figure is a rolling average of the last five years and is updated annually. Institutions with on-site
renewable electricity should adjust this figure. Institutions with Combined Heat and Power (CHP)
should use the conversion method in Annex 2 of Defra’s Guidelines.
11. Disclaimer
This tool provides a broad assessment of electricity usage (and, by extension, electricity costs and
indirect carbon emissions) from Information and Communication Technology (ICT) in-use only,
within universities and colleges. Its aim is to identify the broad pattern of consumption, so that
improvement opportunities can be effectively targeted. Great efforts have been made to ensure that
the assumptions are reasonable for educational institutions. However, the wide variability in
numbers, types and usage of devices used in them means that the results are necessarily broadbrush. Also small changes in assumptions can lead to large differences in outcomes. Therefore,
users should not place too much reliance on the detail of the results and measurements are
recommended on a sample basis (for a few devices or a building) as a reality check. Alternatively a
sensitivity analysis could be done using minimum and maximum assumptions to obtain a range of
results.
Note the tool does not account for the following:








Energy consumed during equipment manufacture, disposal;
Energy used by IT equipment in student residences;
Energy used by non-ICT office machines (e.g. franking machines, money counters,
laminating machines),
Energy from computers incorporated into laboratory equipment,
Energy used by IT equipment in associated medical research centres or health trusts;
Energy associated with production of consumables (e.g. paper, ink);
Energy associated with any outsourced printing work,
Energy associated with any specialised ICT devices not listed in the tool.
12. References
Cartledge, C., 2007. IT Planning: Using less electricity. Presentation at UCISA Green IT workshop,
April 2007. http://www.ucisa.ac.uk/events/2007/forum_greenit.aspx
Cartledge, C. 2008. Sheffield ICT Footprinting Commentary. July 2008. Available at:
www.susteit.org.uk under tools.
Defra, 2008. Guidelines for Greenhouse Gas Conversion Factors for Company Reporting. Available
at: http://www.defra.gov.uk/environment/business/envrp/conversion-factors.htm [accessed June
2008]
Emerson, 2007, Energy Logic, Reducing Data Center Energy Consumption by Creating Savings
that
Cascade
Across
Systems.
White
Paper.
Available
at:
http://www.liebert.com/common/ViewDocument.aspx?id=880
© SusteIT, 2009
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EU
Energy
Star,
2006.
Imaging
specification.
Available
at:
http://www.euenergystar.org/downloads/legislation/20061228/l_38120061228en_annexC7_IE.pdf
EU Energy Star, 2008. Fax database. Available at: http://www.eu-energystar.org/en/en_033c.shtml
[Accessed June 2008].
Market Transformation Programme (MTP) (2007). Consultation on sustainable products - improving
the efficiency of energy-using products. Chapter 5. Improving the energy performance of information
and communication technology products, December 2007. http://www.mtprog.com/Whitepaper.aspx
Market Transformation Programme (MTP) (2007a). BNICT11: Developing ICT usage Profiles. V1.3,
July 2007. http://www.mtprog.com/ApprovedBriefingNotes/PDF/MTP_BNICT11_2007July10.pdf
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