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I-STUTE Project
- WP2.3 Data Centre Cooling
Project Review Meeting 4, Lancaster University, 2nd July 2014
Background
2
• Data centres estimated to use 2-3% of total electricity consumption in the UK and generate
3.3 million tonnes of CO2 annually.
• Data centre energy use and emissions projected to quadruple by 2020 without significant
efficiency improvement
• Typically, approx. 50% of data centre energy is used for cooling and humidification
• Extreme energy saving measures have resulted in as little of 7% of total energy being used
for purposes other than IT. These methods are not feasible in all cases, however, there is
potential for large energy savings
• Use of energy for IT load is also generally inefficient, due to: (i) resilience measures; (ii)
operating at low IT loads. There is therefore potential for large energy savings in IT power
usage
Plan for data centre project
3
• Phase 1 (July 2013 – Oct 2014) - Development of roadmap:
Tasks:
(1) Study of data centre industry – gathering information, networking/identification of key
players, current areas of research interest and review current data centre industry
(2) Identify new energy/carbon saving cooling technologies and strategies for use in data
centres, and establish methods for evaluating and scoring new technologies
(3) Review and evaluate each technology/strategy against defined criteria
(4) Identify technologies for detailed study/development in second phase of project
(5) Produce roadmap document
• Phase 2 (Oct 2014 – July 2016) – Detailed study of selected technologies
Overview of activities undertaken to date
4
• Gather information on data centres e.g. types, sizes, layout, operation, current
technologies, potential future technologies
• Networking – attending data centre industry events, identifying key players,
establishing contacts with data centre operators, manufacturers/suppliers and other
research teams
• Use of data centre modelling software (Romonet) to predict energy use, emissions
and costs for a conventional data centre, to develop baseline case
• Define criteria for evaluating current and future data centre cooling technologies
• Use of exergy analysis for rating of the energy performance of different data centre
cooling approaches and potential for energy recovery
Data centre cooling approaches
5
Air based (conventional)
Advantages – Effective. Fans, air conditioners and
chillers. New: free cooling and evaporative cooling,
higher operating temperatures
Disadvantages – Low heat carrying capacity, large
volumes, costly equipment, inefficient
Water based
Advantages – High heat capacity, pumped, small
volumes, efficient, low energy input
Disadvantages – Incompatible with electronics, only
recently used in data centres
Refrigerant based
Advantages – Electronics compatible, high heat
carrying capacity, particularly 2-phase. Pumped system –
low energy input
Disadvantages – not much experience of use in data
centres
6
Data centre cooling technologies
Air:
(i) Traditional – use of CRACs,
CRAHs and chillers around
perimeter of room, random
layout of racks
Improved efficiency air cooled
systems:
(ii) raised floor + hot/cold aisle
(iii) in-row cooling
(iv) contained hot or cold aisle
(v) air side economiser
(vi) direct air free cooling,
(vii) adiabatic free cooling
(viii) direct evaporative
(ix) indirect evaporative
(x) water side economiser
Water:
(i) Direct on-chip water
cooling
(ii) Conduction cold plate
cooling of server
(iii) Rear door water cooled
rack system
Refrigerant:
(i) Immersion cooling of
server boards
(ii) Spray cooling of chips
(iii) Direct on-chip 2-phase
pumped
(iv) Direct on-chip 2-phase
VC system
Future/blue sky:
(i) Thermoelectric
(ii) Thermionic tunnelling
(iii) Thermoacoustic
(iv) Stirling coolers
(v) Air cycle
(vi) Liquid air engine
(vii) Ionic wind
(viii) Porous media
7
Energy flows in data centres
• Main aim of conventional data centre cooling is
to remove heat from vicinity of microprocessors
and reject to outside ambient air
• Typical air-cooled data centre
configuration
Energy (electrical and mechanical) inputs,
heat outflows and typical temperatures
8
Sources of heat in server racks in data centres
• Heat generated in data centres is not just from microprocessors
• Typical power consumption/heat generation pattern for a data centre server rack
Source: Intel
9
Potential for heat energy recovery from server components
Parameter Processors Memory PCI Drives Motherboard PSU Fans DC loss Standby
% Power
consumption 30% 11% 3% 6% 3% 25% 9% 10% 2%
Operating
temperature 70°C 70°C 30°C 45°C 40°C 50°C 30°C 40°C -
Carnot
efficiency
(Tc=20°C)
0.15 0.15 0.03 0.08 0.06 0.09 0.03 0.06 -
Recoverable
energy
(100kW
input)
4.5 kW 1.65 kW 0.09 kW 0.48 kW 0.18 kW 2.25 kW 0.27 kW 0.60 kW -
• Main components from which heat could be recovered are:
(i) Processors; (ii) PSU; (iii) Memory
10
Quality of waste heat from data centres
• Data centres generate very large amounts of heat energy. This heat is generally
transferred to the surrounding environment and wasted
• This waste heat should be regarded as an energy source and exploited
• To determine the potential for re-use of waste heat dissipated from a data centre, an
exergy analysis is needed
• Different cooling methods/technologies produce different temperature heat output
streams with different exergies i.e. qualities
• It is planned to categorise a range of data centre cooling technologies in terms of both
energy saving potential and exergy maximisation of waste heat streams.
Exergy and degradation of energy
11
• Exergy measures the quality of a given energy source. It is defined as the maximum
potential of that energy source for doing work
• Electricity has an exergy value close to 100%. However, heat generally has a lower
exergy value that is related to its temperature
• Each process taking place in the data centre e.g. conversion of electricity to heat,
results in a loss of exergy
• Change in exergy (for a closed system) is given by:
1212
120121122
zzmgm
SSTVVPUUX
Change in Change in Work done Exergy Change in Change in
exergy internal destroyed kinetic potential
energy energy energy
Results of preliminary exergy analysis
12
Ambient temperature of 30°C (303K) assumed:
Cooling
medium
Cooling
method
Chip
temperature
Exergy remaining
after electrical
energy converted
to heat
Heat Energy transfer
from chip to coolant
(1st law efficiency)
Exergy
recovered in
coolant (2nd
law efficiency)
Net exergy
destroyed
per kW IT
Exergy
recovered
per kW
cooling
Air Fan 60°C 9.0% 93% 1.1% 1.01 0.32
Air Fan +CRAC 85°C 15.3% 93% 21.0% 0.90 0.60
Water Pump 60°C 9.0% 93% 5.0% 0.93 1.47
Water Pump 75°C 12.9% 83% 7.7% - -
Water Pump 85°C 15.3% 69% 8.4% 0.86 2.64
Refrigerant Pump 85°C 15.3% 99.7% 8.7% 0.83 12.1
Refrigerant VC 85°C 15.3% 92.5% 14.8% 0.86 0.79
Aims of heat recovery from data centres
13
• Need to maximise temperature of waste heat stream to enable greatest range of
applications
• Could use heat pump to boost waste heat temperature – but is this energy efficient?
• Ideally, want to recover energy in excess of that used for cooling method
• Probably best to use waste heat directly
Data centre waste energy recovery technologies
14
Waste
heat in Vapour Generator Turbine
Pump Condenser
Shaft Work
Heat out
Organic Rankine Cycle
Kyoto Wheel
Waste heat driven absorption chiller
Other waste heat uses include: domestic and
industrial space and water heating, district
heating, desalination, biomass processing,
piezoelectrics and thermoelectrics
Options for efficient heat recovery from server components
15
• Use of porous media evaporator
• Refrigerant could either be pumped or used with
vapour compression system
• Key to viability of waste heat recovery from data centres is to maximise coolant
temperature. This is likely to be best achieved by liquid cooling (minimise ∆T)
• Use of microchannel evaporator
• Again refrigerant may be either pumped or
used in vapour compression system
Next steps
16
• Finalise evaluation method for assessing new technologies for roadmap
• Evaluate and score energy/carbon saving technologies against defined criteria.
• Produce roadmap document, including:
- review of data centre industry
- detailed description of each of the technologies evaluated
- potential for waste heat and energy recovery
• Identify technologies for detailed study/development in second phase of project
Timescales for data centre project
17
Activities
Development of roadmap
Detailed study of selected
technologies
Duration
July 2013- Oct 2014
Oct 2014 - July 2016
Milestones
Finalise evaluation method – Jun 2014
Final report/roadmap – Oct 2014
Interim report – May 2015
Interim report – November 2015
Final report - July 2016
Recommendations – July 2016
Options for dissemination of results of project
18
• Present results at data centre industry conferences e.g. Uptime Institute conference in
USA, Data Centre Dynamics Conference UK, Europe or USA
• Present results at other relevant industry forums e.g. IMechE, CIBSE, IOR, SIRACH
• Journal papers e.g. ASHRAE or CIBSE journals