Data Centre Regulation

Transcription

1 WPs 2.1, 2.2, 2.3, 2.4, 2.5 Graeme Maidment

2 i-stute cooling based projects WP2.1. and WP2.2 Supermarket refrigeration Cost of ownership WP2.3. Data centres Integration Carbon/ energy WP2.4. Transport refrigeration WP2.5. Integrated heating and cooling Materials, resources & waste

3 Background WP 2.1 and 2.2 Retail refrigeration 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

4 WPs 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

5 Technologies investigated 77 technologies evaluated at last meeting New technologies added: Ejectors Flooded evaporators 2-stage compression Turbine expansion machines Fan motor outside cabinet Lights outside cabinet Defrost drain traps Integral distributed system Thermostatic flow control Air deflectors/guides Improved axial fans Diagonal fans Defrosts (additional information) Dual port TEV/TXV Glazing (additional information) Efficient HE design Hydrophilic and hydrophobic coating on evaporator

6 Supermarket model further developed Store modelled - ASDA Weston- Super-Mare Typical large supermarket Model can be adapted to different store sizes and configurations Further information obtained from City Holdings (ASDA contractors) However, stalled recently due to contact leaving company The model

7 Results

8 Results Emissions per year: Direct = tco 2e Indirect = tco 2e Ratio indirect : direct = 1.1 High direct as very high refrigerant charge (~1000 kg in cabinet circuits) Leakage rate medium (~10% per year) Therefore effect of changes to refrigerant have high impact on CO 2e emissions

9 DIRECT EMISSIONS Results

10 INDIRECT EMISSIONS Results

11 DIRECT (grey bubble) AND INDIRECT EMISSIONS (open bubble) Results

12 Next steps Need further data and clarification from ASDA: Cooking appliances Some costs for applying technologies Some data still is not logical Based on current information possible to halve emissions with paybacks of less than 3 years If technologies with less than 3 year paybacks were applied and assuming application of: Cheapest options with best paybacks Minimum savings applied Simplest option (where more than one option available) the carbon savings would be: ~50-65%

13 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 Peer reviewed paper on technological options (IJR)

14 WP2.3 - Data Centre Cooling 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. 14

15 Roadmap There are 4 main approaches to data centre cooling: Remote air cooling: - Using CRACs or CRAHs/chilled water. Also air and water economisation Local air cooling: - Close coupled cooling e.g. rack rear door chilled water heat exchanger Direct liquid on-chip cooling: - Water or dielectric cold plate heat exchanger in direct contact with electronic components Total immersion liquid cooling: - Whole server board immersed in dielectric liquid 15

16 Roadmap Comparison of 4 main cooling approaches: Cooling Method Remote air Local air Liquid directto-chip Liquid immersion Characteristics Coolant(s) (P) Air (P) Air (P) 60/70% Liq (S) R/G/W/Chw (S) Chw (P) 30/40% Air (P)100% Liq Typical inlet-return Air: C Air: C Liq:40-60 C temperatures Chw:10-20 C Chw:10-20 C Air: C Liq: C Heat capacity of primary coolant Low Low High High T Chip to coolant High High Low Low Heat recovery Air Air Air possible? Chw Chw Liq Liq Heat reuse value Low Low High High 16

17 Future trends: Roadmap 1. Increasing data centre efficiency: - Growth in data centre capacity, size and processing speed to meet user needs big data, internet of things (IoT). - Increasing numbers of high performance computing (HPC) and hyperscale servers, and development of exascale data centres 2. Greater utilisation of IT server resources: - Increased IT work levels, server consolidation and virtualisation, move to cloud - Software defined data centres (SDDC) 3. Chip and server architecture development: - Further miniaturisation of ICs down to 1 nm scale by 2020s - Adoption of 3D architecture e.g. vertical chip stacking with microchannel liquid cooling, especially for memory chips Microliquid heat sinks between 17 stacked dies

18 Data centres and District heating networks Currently supply only 2% of heat demand in UK by district heating UK government plans to substantially expand district heating networks making use of waste heat sources e.g. data centres London plans to build a low temperature heat network supply temperature 70 C (London Mayor reports, 2012; 2013) Data centre waste heat could be upgraded via heat pumps to contribute heat at this temperature 18

19 Distribution of data centres across UK Largest number of (colocation) data centres is in London (approx 75) Majority are concentrated in central London, along the Thames 19

20 London heat use and district heating networks (Map from: map/) Yellow lines indicate existing heat networks, red lines indicate proposed heat networks (Map from: 20

21 Detailed investigation of cooling and waste heat recovery in data centres Objectives: To construct a test facility to simulate a conventional IT server rack (~5kW) To investigate a range of cooling methods, environmental conditions and waste heat recovery systems To evaluate the quantity and quality of recovered waste heat, for different cooling methods To investigate the carbon and cost implications of increasing waste heat temperature to e.g. 70 C using heat pumps 21

22 Details of IT server rack test facility 1 x 42U standard server rack ~2 m (h) x 0.6 m (w) x 1.07 m (d) 42 x 1U servers, total weight approx. 500 kg (10-15 kg per server) Linux operating system and benchmarking software to provide adjustable, constant heat generation for all servers IT servers instrumented with thermocouples, velocity and humidity sensors. Measurement of total energy input to servers and cooling equipment and heat recovered 22

23 Next steps Activities Duration Deliverables Due date Finalise, format and publish roadmap report Publish journal paper on waste heat recovery from data centres Construct data centre test facility and commission Experimental testing of cooling and heat recovery methods May- June 2015 Roadmap report 1 st July 2015 May-June 2015 Journal paper 1 st July 2015 May-Dec 2015 Dec 2015-end of project Operational facility Report on test facility construction First interim report Additional interim reports Final report 1 st Dec st Feb st May 2016 TBC End of project 23

24 WP 2.3 Deliverables Internal report on cooling of data centres October 2014 Initial internal heat recovery report December 2014 Report/roadmap of Future technologies with input from Robert Tozer March 2015 Dissemination paper on data centre waste heat recovery to be presented to CIBSE technical symposium April 2015 at UCL Journal paper on heat recovery drafted Detailed heat recovery study commences January 2016

25 WP2.4 refrigerated road transport (RRT) Background UK primary food distribution by RRT uses 40% more energy than non-refrigerated vehicles Environmental Impact Indirect emissions - Transportation - 2 Mtonnes of indirect CO 2 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

26 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 26

27 Project Plan flow chart PhD Thesis Conduct Prelim Study & Data Analysis I Develop Model Collect Data & Analyse Validate & Optimize Model Report for Transport Industry 27

28 Model Development Refrigeration Performance 2. A preliminary model to predict the performance of RRT systems has been developed. MS Excel Mathematical model Focuses on typical last-mile RRT vehicle (i.e. small vans to medium rigid refrigerated trucks) used for urban distribution. 28 Calculates relative proportion of various refrigeration heat loads and corresponding indirect carbon emissions: i. Wall transmission ii. Natural infiltration due to gaps, cracks iii. Door infiltration iv. Product load v. Other loads such as evaporator fans

29 Refrigeration Performance Model - System Details 29

30 Challenges and Solutions Common solutions include: Oversize unit; use door protection; employ a hybrid system Planned approach: Determine optimum design For the average load profile Typical annual duty cycle 30 Issues with direct drive RRT units: Large amount of heat entering during door openings Refrigeration system stop working when vehicle stops => system is off when load at its highest Running time between stops may be short => time insufficient for temp pull-down

31 Project Schedule Today Develop Model - May Jan 2016 Data Collection - Meeting with Fleet Owner (Data Supplier) May 2015 Initiate data collection Jun 2015 Data Analysis- Aug Jan

32 WP 2.4 Deliverables Internal report on leakage - Feb 2014, August 2014 LSBU Registration document -RES2 June 2014 Summer school conference June 2014, June 2015 Internal report on modelling platforms- August 2014 LSBU Literature review internal report-res 3B Oct 2014 Internal report on modelling platforms- August 2014, Nov 2014 Ethics application approval -Jan 2015 LSBU Annual Report RES 4 April 2015 Impact Hubbard have changed their system design to minimize leakage.

33 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

34 2. Project time line with the key milestones Stage 1 & 2 Stage 3 Stage 4 Stage 6 Stage 7 Currently ongoing

35 Results Figure 1 Annual temperature distribution within soil Figure 3 Numerically simulated tunnel and ground surface temperatures Figure 2 BHE wall temperatures versus tunnel proximity

36 WP 2.5 Deliverables Internal reports April July and November 2014, February 2015 Summer school conference, Poster June 2014 Registration document RES2 September 2014 Literature review internal report October 2014 Internal report on modelling platforms - November 2014 Registration document RES3 February 2015 Conference paper submission February 2015 Manuscript submission to a Journal March 2015 Registration document RES4 March 2015

37 Questions