IT Footprint Tool User Guide and Assumptions

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. Introduction...... 2 2. Description of the Tool...... 2 3. Using the Tool...... 3 4. Results Displayed...... 5 5. Sheffield Worked Example...... 6 6. Estimating the Number of Devices...... 6 7. 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...9 9. Estimating the Usage of Devices...... 11 10. Assumptions...... 12 11. Disclaimer...... 15 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.

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 non- residential 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 6. Server Rooms – Enter data on central and departmental servers plus storage and cooling/power supply overhead 1 Cartledge, C., 2008. Energy Impacts of ICT at the University of Sheffield, Bradford: SusteIT, July, 2008. Downloadable from www.susteit.org.uk. © SusteIT, 2009 2 www.susteit.org.uk

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”.

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.

Table 1: Default values for the overheads used in the tool Worksheet Overhead Cell Default value

HPC Cooling E8 0.425 HPC Power supply E9 0.075 Servers Storage and other equipment E7 0.15 Servers Cooling E9 0.425 Servers Power supply E10 0.075 PCs & Monitors Cooling (for airconditioned computer H19 0 suites only) Phones PABX cooling and power supply 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.

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% S ervers 26% P C s 400,000 17% Networks 200,000 0 0% P hones 20% Imaging 19% 3% 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 Energy Total (Kwh/y) % Total CO2 (kg/y) HPC 1,208,617 14% 649052 Servers 1,520,736 18% 816666 PCs & Monitors 4,164,477 48% 2236408 Networks 687,362 8% 369127 Phones 202,356 2% 108669 Imaging 835,659 10% 448765 AV 61,598 1% 33080

TOTAL ICT ENERGY 8,680,806 100% 4,661,766 & CARBON 6. 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. High Performance Computing – IT research staff, estates (for air conditioning load) 2. Servers - IT management staff and Heads of research-intensive departments, estates (for air conditioning load) 3. 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. 4. Networks – IT management staff, IT procurement staff

5. Phones – IT management staff, IT procurement staff 6. Imaging devices – print management staff, library/support services staff, central printing staff or organisations, interviews with selected departments. 7. 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 sub- meters 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,:

 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. 7. 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 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

2 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. © SusteIT, 2009 7 www.susteit.org.uk

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. Sleep 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. Off 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.

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. Sleep 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) has been placed into a low- power 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. Off Mode 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.

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.

To simplify matters the tool defines only 2 energy states:

3 EU Energy Star website. Available at: www.eu-energystar.org/en/index.html. 4 EU Energy Star website. Available at: www.eu-energystar.org/en/index.html. © SusteIT, 2009 8 www.susteit.org.uk

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%).

8. Estimating Server and High Performance Computing Air- Conditioning 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)

Active/idle Standby High Performance Computing Departmental or central HPCs 300 n/a Servers Departmental or central servers 300 n/a Other server equipment (e.g, storage, communications etc) 15% of total server power Computers PCs and workstations– high performance 100 2 PCs medium performance – standard and managed 60 2 PCs- low power – standard and managed 30 2 Portable (laptops) 30 2 Thin clients 7 7 Monitors CRT 70 5 LCD/TFT 35 2 Networks Cabinet based edge switches 50 n/a Cabinet based aggregation switches 100 n/a Cabinet based core switches 600 n/a Cabinet based wireless access points 16 n/a

Room based hubs 4 n/a Room based unmanaged edge switches 25 n/a Phones PABX distributed 2 1 VOIP 8 8 Imaging Central services High volume copiers 1200 30 High volume printers 800 15 Student photocopiers 1000 30 Departmental High/medium volume copiers/MFDs 1000 30 Low/medium copiers/MFDs 600 20 Shared monochrome laser printers 450 15 Shared colour laser printers 600 30 Scanners 12 2 Faxes Personal 1 kWh per week Personal laser printer 350 10 Personal inkjet printer 20 6 MFD 500 10 Audio-visual Projectors 300 8 OHP 300 2 Plasma screens 700 3 9. 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.

Table 7: Summary of default usage hours for all devices in the tool Device Active Standby Weeks per Active Standby Usage usage year usage usage (hours (hours per (hours per (hours per per year) week) week) year) (a) (b) (c) (a*c) b*c) High Performance Computing Departmental or central HPCs 52 8,760 n/a Server Rooms Departmental or central 52 8,760 n/a servers PCs Standard PCs, low power 70 98.5 52 3,640 5,120 green PCs and high performance PCs and workstations Managed standard and student 40 128.5 52 2,080 6,680 (standard and green) and thin clients Monitors All monitors 40 128.5 52 2,080 6,680 Networks All devices 52 8,760 n/a Phones All devices 52 8,760 n/a Imaging Central High volume copiers 40 128 52 2,080 6,680 and printers Student photocopiers 19.2 57.7 52 1,000 3,000 Departmental High/low volume 10 158.5 52 520 8,240 photocopiers/MFDs Departmental networked laser 10 158.5 52 520 8240 printers (b/w and colour) Personal laser and inkjet 1.67 (i.e. 166.7 52 87 8673 printers/MFDs 20 mins/day)

AV Projectors/OHP 25 143 40 520 8,240 Plasma screens 52 8,760 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:

(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 40- 45% 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 40- 45% 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.

(g) Hours per year in use for active/idle and standby were based on the following: 5 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. © SusteIT, 2009 13 www.susteit.org.uk

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. On-active 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 estimated from a fluctuating measured value as each sheet of paper is printed, while the standby © SusteIT, 2009 14 www.susteit.org.uk

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)

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 broad- brush. 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

EU Energy Star, 2006. Imaging specification. Available at: http://www.eu- energystar.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