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WPs 2.1, 2.2, 2.3, 2.4, 2.5
Graeme Maidment
i-STUTE cooling based projects
WP2.1. and WP2.2 Supermarket refrigeration
WP2.3 . Data centres
WP2.4. Transport refrigeration
WP2.5. Integrated heating and cooling
Cost of ownership
Carbon/ energy
Materials, resources & waste
Integration
WP 2.1 and 2.2 Retail refrigeration Background
• 40-70% of energy in supermarkets used for refrigeration
• UK retail refrigeration ~ 9-10 TWh/year
– ~75% chilled, ~25% frozen • 1.5% of UK energy used by retail
• ~7.3 Mt CO2 (~26% direct, ~74% indirect)
• Temperature control, carbon emissions increase at consumer end of cold chain
Deliverables
• Refrigeration road map
• State of the art display cabinet
1 http://www.igd.com/index.asp?id=1&fid=1&sid=7&tid=26&cid=941
WP 2.1 Retail chilling and freezing
• WP2.1.1 – Technologies will be initially investigated and sifted
• WP2.1.2 – In parallel with WP2.1 technologies will be investigated with a proof of concept prototype
• WP2.1.3 – Non technical barriers preventing uptake, will be assessed ie customer reaction, implementation, cost-benefit, incentives
• WP2.1.4 –A trial of the prototype in-store with ASDA WP
s
Road map
• Road map updated:
• Includes:
– Updated refrigeration
– HVAC
– Cooking
– Food prep
– Heating
The model
• Supermarket model further developed
• Store modelled - ASDA Weston-Super-Mare
• Typical large supermarket
• Model can be adapted to different store sizes and configurations
Road map model
• Asda (WSM) - electrical energy use in 2014 2874 MWh/year
• Refrigeration:
– Store power meters 1309 MWh/yr
– Predicted 1157 MWh/yr (-11.6%)
Unmetered • Some unmetered energy (not possible to
quantify): – Customer cafe
– Staff cafe
– Outside (lights)
– Offices
– Lighting (not sales area)
– Frost protection
– ?
Carbon savings – direct + indirect
Carbon savings - direct
Carbon savings - indirect
MACs
• Divided into:
– Retrofit
– Refit
– New store
• Sequential impact of technologies considered
• CO2 conversion factor = 0.4943 kgCO2e
• Payback time = 2 years
MACC – retrofit
MACC – re-fit
MACC – new store
MACs • Almost all retrofit technologies have negative cost
per tonne of CO2 abated
• Less re-fit options have negative cost per tonne of CO2 abated but still several (note that very little difference between options in terms of order apply technologies)
• Costs for re-fit options more expensive in terms of cost per tonne of CO2 abated
• New store – much higher cost per tonne of CO2 abated
Best technology cabinet
• Epta cabinet obtained
• Chilled multi-deck (open fronted)
• Remotely operated
• Will be tested to identify best technologies to apply
• EN23953 test
WP2.1 Deliverables
• Contact with CSEF, agreed to create dynamic supermarket model with team at Brunel
• Keynote for ICEF12 (Quebec)
• Opportunity to publish book from road map work
• Paper published at IIR conference
• Peer reviewed paper on technological options (IJR)
WP 2.2 Retail refrigeration
• Not started yet
• A blank sheet of paper
WP2.3 - Data Centre Cooling
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Background • Data centres currently account for approx. 2-3% of
total electricity consumption in the UK
• Typically, approx. 50% of data centre energy is used for cooling and humidification
• Data centres are generally air cooled and the
heat dissipated to ambient
• Limited focus on heat recovery
Deliverables • Roadmap/report on cooling
• Detailed investigation - integrated cooling, heat
recovery and heat transfer.
Options for waste heat recovery from data centres 1
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Heat recovery from CRAC/CRAH return air in data centre
Heat recovery from chilled water in data centre
Options for waste heat recovery from data centres 2
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Waste heat recovery from liquid cooled data centre
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Data centre test facility Overall aims: 1. Construct a test facility to simulate a conventional server rack producing 5-
10 kW of heat 2. Focus initially on air cooled data centres 3. Apply a range of thermal management approaches i.e. cooling methods
and waste heat recovery approaches 4. Evaluate the quantity and quality of waste heat recovered in each case 5. Estimate the potential energy, carbon and cost savings
Options for air flow management for test facility
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• Underfloor (plenum) cold air supply • Cold air containment (using 2nd plenum)
• Cold air supply above floor • Cold air containment using duct and plenum
• Cold air supply above floor • Cold air containment using expanding duct
• Cold air supply above floor (uncontained) • Hot air containment using plenum and duct
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Overall design for test facility
• Water will be pumped to a dry cooler outside the laboratory
• Heat will be rejected to ambient air
• However, heat carried in water could be recovered
• Heat flow meter will be used to quantify the recovered heat
(Note: initially cold air containment will be used in data centre room)
New cooling method for data centres
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• A new cooling method for data centres - the use of mains water - CIBSE
• Mains water properties:
(i) temperature between 5 - 20°C
(ii) distributed trunk water main across London
(iii) increasing mains supply temperature by 1°C requires 100 MW heat
(iv) 5-6°C could be added i.e. 500-600 MW
• Could replace mechanical chillers in many applications e.g. data centres, London underground stations, large buildings
Benefits of using mains water for cooling
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• Large energy, carbon and cost savings–
• trunk water mains located close to many sites - low CAPEX
• Raising temperature of water mains reduces leakage, saving water and costs
• Higher mains water temperature reduces energy input for DHW
• cost savings digging up roads
Potential energy, carbon and cost savings c.f. conventional cooling
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Data Centres London Underground Stations
Minimum Average Maximum Minimum Average Maximum
Heat output/cooling rate required (MW) 0.25 2.80 28.09 0.50 1.50 2.50
∆t (°C) (for a single trunk main) 0.2 2.23 22.37 0.40 1.19 1.99
Operating hours per year (h) 8760 8760 8760 6570 6570 6570
Total cooling required per year (MWh) 2,190 24,528 246,111 3,285 9,855 16,425
Annual electricity use (MWh) 1,095 12,264 123,056 1,643 4,928 8,213
Cost savings on electricity per annum (£) £109,500 £1,226,400 £12,305,566 £164,250 £492,750 £821,250
Carbon savings per annum (tonnes) 488 5,463 54,819 732 2,195 3,659
Assumptions: • Typical heat output/cooling rates for single data centre or underground station • All cooling currently provided by air conditioning systems with a COP of 2 • LU stations require cooling for 18 h per day; data centres require 24 h cooling • Cost of electricity £0.10 per kWh • Carbon factor of 0.44548 kg/kWh
Next steps
• Construction and commissioning of data centre test facility
• Detailed feasibility study of potential for using mains water for large scale cooling
• Establish cooling trials using mains water
• PhD study on use of mains water for cooling applications
WP 2.3 Current and Future Deliverables
• Two conference paper abstracts to CIBSE Technical Symposium (April 2016),
• Advising Govt - data centre emissions
• Construction and commissioning of data centre test facility, by April 2016
• Conduct tests and determine waste heat recovery for a range of configurations (from May 2016)
• Work on mains water cooling trial for LU/ data centre 2016
• Establish PhD project on use of mains water cooling, by April 2016
• Internal report on cooling of data centres – October 2014
• Initial internal heat recovery report – December 2014
• Dissemination – paper on data centre waste heat recovery - CIBSE technical symposium April 15
• Journal paper on heat recovery accepted
• Roadmap on data centre cooling – finalise and publish report by 1st Nov 2015
Background • UK primary food distribution by RRT uses 40% more
energy than non-refrigerated vehicles • Environmental Impact
• Indirect emissions - • Transportation - 2 Mtonnes of indirect CO2
emissions from the engine alone. • Refrigeration - ????
• Direct emissions - • RRT units leak up to 30% of their total
refrigerant charge per year
• System Durability & Reliability
Deliverables • Development of a model to investigate direct and
indirect emissions • Optimising system performance
WP2.4 refrigerated road transport (RRT)
Research Plan 1. Investigate different types RRT vehicle
technologies
2. Analyse maintenance and leakage records to:
a) Identify problematic components/ sources of refrigerant leakage
b) Suggest generic solutions for leak tight systems
3. Develop a model to; a) Estimate direct/ indirect carbon emissions b) Evaluate the effectiveness of various
concepts
4. Measure actual RRT data
5. Validate and optimise model
6. Industry report & PhD thesis
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Analyse maintenance and leakage records
• MS Excel Based • Captures essential information
• Itemizes and maps each fault to
distinct categories and sub-components.
• Easily sort data and analyse to determine where leaks or faults are commonly found.
A refrigerant leakage and analysis tool
has been developed
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A sample analysis of RRT service records showed that the bulk of the faults (i.e. 40%) were located in the condenser.
RRT System Performance Model Development
A model to predict the performance of RRT systems.
• Preliminary steady state model. • MS Excel based.
• last-mile RRT vehicle -urban distribution.
• Calculates refrigeration heat loads and
emissions.
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PHASE 1
Results • refrigeration system account for 4% -
24% of the fuel for motive work • field data suggest a range of 15-25%
(Hutchins, 2007).
Future work will include:
• Revising the model assumptions based on actual data measurements.
• Developing PHASE 2 of the model to incorporate transient parameters.
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Refrigeration Performance Model - System Details
• 3 last mile RRT Sprinters instrumented
• Fleetboard – engine and road/ location profile
• Refrigeration fuel use
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Collecting data and analysis
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Project Schedule
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Today
Develop Model - May 2014 - Mar 2016
Data Collection & Analysis- May 2015 – Mar 2016 • Instrument transport refrigeration unit- Oct 2015
• Start data analysis – Nov 2015
Next immediate steps
• Continue to design and test methodology for data collection on the refrigeration unit.
• Continue to collect data from the RRT system (i.e. insulated box and
refrigeration units).
• Conduct data analysis on the road performance of home delivery refrigerated vehicles
WP 2.4 Deliverables
• Developed a steady state model and leakage analysis tool
• Delivered conference paper and oral presentation at the 24th IIR -ICR 2015- Aug 2015
• Drafted journal paper
• Feedback from the refrigerant leakage analysis tool influenced
Manufacturer to change their system design to minimize leakage
• Initiated research survey and collection of operational data:
– Obtained signed NDA for the collection of data from Fleet Owner
– Gained the support of Transport Temperature Control Engineers
– Initiated collection of operational data. Three (3) refrigerated vehicles
have been instrumented with temperature recorders to monitor the insulation boxes.
• Initiated methodology design to collect data from the transport refrigeration unit
Background
• To investigate the interactions of underground railway tunnels and ground heat exchangers
• To investigate the potential indirect use of waste heat from the tunnels to heat buildings above
ground.
Deliverables
• Development of a model
• Case study materials
INTERACTIONS
2. Project time line with the key milestones
Stage 1 & 2 Stage 3 Stage 4 Stage 6 Stage 7
• Preliminary 2D model has been developed • A 3D model development is currently ongoing
3. Key achievements
• Preliminary 2D model has been developed
• The up to date work has been presented on the 24th IIR Congress on Refrigeration,
in August 2015 in Yokohama, Japan.
• A manuscript was accepted for publication in September 2015.
• 3D model development has started.
• An abstract was submitted to the 2016 CIBSE Technical Symposium in September
2015.
4. Results
2D model geometry
Analysis
2D simulation results of different parallel running tunnels
Start of the 3D modelling work…
5. Immediate next steps
• Further development of the 3D model.
• Draft a manuscript for the 2016 CIBSE Technical Symposium (Subject to abstract
acceptance).
WP 2.5 Deliverables
• Finalise 2D model development– July 2015
• Conference paper presentation – August 2015
• Summary report on the 2D modelling work – September 2015
• Journal paper publication accepted– September 2015
• Abstract submitted for CIBSE Tech Sym – April 2016
Questions