Jisc con optimisation, improved sustainability across the estate through use of ict

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Jisc con optimisation, improved sustainability across the estate through use of ict

  1. 1. Continuous Optimisation<br />JISC <br />Improved Sustainability Across Estates Through The Use of ICT<br />Continuous Optimisation – an Imperial College estates<br />initiative reducing the carbon consumption of plant & services, and how ICT infrastructure underpins it’s delivery<br />
  2. 2. Continuous Optimisation - Content<br />Content<br />Continuous Optimisation (ConCom) – what is it?<br />Background<br />Initiatives <br />Flowers building ‘night set-back’<br />Air change rationalisation<br />Filter optimisation<br />How does ICT support Continuous Optimisation?<br />TREND system<br />Carbon Desktop<br />Real Time Logging<br />
  3. 3. Continuous Optimisation <br />Continuous Optimisation (ConCom) – what is it?<br />
  4. 4. Continuous Optimisation - Background<br />Background<br />Imperial College’s ‘Carbon Management Plan’ requires us to achieve a 20% reduction in carbon consumption by 2014.<br />84,026 tCO2 reduced by 16,805tCO2 to 67,221tCO2<br />Continuous Optimisation of plant & services, targeted to deliver 4,903tCO2<br />This can only be achieved if we have:<br />Extensive control systems<br />Robust operational information<br />The cooperation of the academic community<br />As a Science, Engineering and Medicine focussed University, our research and teaching relies heavily on controlled environments.<br />
  5. 5. Continuous Optimisation - background<br />We are challenging how environments were originally commissioned by considering:<br />The original design, at sign-off<br />How the environments are now being used<br />The occupation strategy<br />What service strategies are really needed to provide, safe and productive environments, without compromising our research & teaching.<br />Through Continuous Optimisation (continuous commissioning ‘ConCom’), we are implementing:<br />Air change volume adjustments<br />AHU operational set-backs (temperature & time)<br />Introducing more efficient plant<br />Adjusting pump delivery to meet flow demands<br />Improving filter efficiencies<br />Introducing occupancy controls e.g. CO2 sensors, ‘user switches’<br />
  6. 6. Continuous Optimisation – Flowers building ‘night set-back’<br />Flowers Building ‘Night set-back’<br />Initiative<br />
  7. 7. Continuous Optimisation – Flowers building ‘night set-back’<br />Flowers Building ‘Night set-back’<br />Methodology<br />We identified Flowers building main air handling services were operating 24 hours a day, 7 days a week<br />Environmental conditions and operational dependencies were discussed with users<br />The four supply & extract air handling units were re-commissioned to ensure they could continue to operate to the original design<br />This helped establish that new motorised dampers and controls would be required to manipulate the air pressures and volumes, while ensuring that dedicated equipment areas continued to receive 24hr ventilation / cooling.<br />
  8. 8. Continuous Optimisation – Flowers building ‘night set-back’<br />Methodology (cont’d)<br />The energy profile for the building was then measured across a normal week<br />The new controls and motorised dampers were installed<br />The air supply pressure was then reduced from 400pa to 300pa<br />The air volume delivered overnight was reduced to an average of 6 air changes / hour, from 13, between 22.00hrs to 07.00hrs.<br />The energy profile for the building was measured throughout this process and checked in subsequent weeks.<br />Further commissioning followed; reducing air pressures, and extending the time to between 18.00hrs to 07.00hrs, more savings resulted.<br />
  9. 9. Continuous Optimisation – Flowers building ‘night set-back’<br />Savings<br />The base load has reduced from 280kW to 210 kW a 70kW saving<br />Day time air pressure was reduced, heating & cooling savings resulted<br />This realised overall savings of <br />
  10. 10. Continuous Optimisation – Flowers building ‘night set-back’<br />Electricity profile the week before the damper replacement and night setback initiation<br />Dampers replaced (Mon 5th & Tues 6th October)<br />Night set back initiated Wednesday 7th October<br />kW<br />400<br />320<br />240<br />160<br />80<br />Base load has reduced from 280kW to 210kW<br />
  11. 11. Continuous Optimisation – Air change rationalisation <br />Air Change Rationalisation<br />
  12. 12. Continuous Optimisation – Air change rationalisation <br />Air Change Rationalisation<br />As part of our ConCom programme we challenge the air change strategy for each building, comparing the design, current operation and recommended standards.<br />CIBSE guidelines recommend 6 air changes / hr for laboratories.<br />We find that our environments are commissioned within significant excesses of this standard, often between 10 and 14 air changes / hr.<br />Working closely with users, we measure the current air changes, and then gradually adjust the fan-sets, optimising their delivery but without compromising the business need or safety.<br />
  13. 13. Continuous Optimisation – Air change rationalisation <br />This approach can deliver significant savings through: <br />reduced fan motor speeds<br />reduced heating demands<br />reduced cooling demands<br />An example of this approach in the Sir Alexander Fleming building, where we focussed on 3 of the main AHU’s has already delivered annual savings: <br />980,588 kWhrs, £31,450 275 tonnesCO2<br />
  14. 14. Continuous Optimisation – Air change rationalisation <br />14<br />
  15. 15. Continuous Optimisation – Air change rationalisation <br />15<br />
  16. 16. Continuous Optimisation – Air change rationalisation <br />Carbon Desktop - Electricity demand profile for Transformer 40 - MCP3 at SAF.<br />MCP 3 feeds AHUs 1,2,3, 4, 7,8,17,18,16,9 & 23.  <br />A further £15K in heating and cooling savings using bin weather data.<br />16<br />
  17. 17. Continuous Optimisation – Filter Optimisation<br />Filter Optimisation<br />
  18. 18. Continuous Optimisation – Filter Optimisation<br />Filter Optimisation<br />Most air handling units (AHU’s) have integral filter strategies, applied primarily to supply, and for some applications, the extract. <br />Filter media provides significant resistance within the air flow path, resistance increases as filters become blocked.<br />Higher resistance of the filter, results in increased energy consumed by fan motor to provide the required air flow.<br />Initial trials (Carbon Trust Funded) in the SAF building have shown, that by using filter media (e.g. HiFlo bag filters) with a larger surface area, significant savings can be achieved on fan motor power.<br />
  19. 19. Continuous Optimisation – Filter Optimisation<br />19<br />
  20. 20. Continuous Optimisation – Filter Optimisation<br />20<br />
  21. 21. Continuous Optimisation – Filter Optimisation<br />21<br />
  22. 22. Continuous Optimisation – Filter Optimisation<br />22<br />S Flow bag<br />Hi flow bag<br />Opakfil Rigid bag<br />30/30 Pleated Panel<br />
  23. 23. Continuous Optimisation – How does ICT support Continuous Optimisation?<br />How does ICT support Continuous Optimisation?<br />
  24. 24. Continuous Optimisation – TREND System<br />TREND System (BMS)<br />Imperial College has the largest TREND Building Management System in the UK (original installation commenced1996).<br />Traditionally it has been used to monitor the operational status of plant & services and in particular, plant failure (replaced Sauter).<br />This system was stand alone with a ‘hard wired’ network, which as it grew, became less reliable and access speed slowed significantly.<br />To overcome these issues and future demand we now run the BMS over the Cat 3 network, which assures capacity, improves access and has increased reliability.<br />This approach has allowed us to widen access via a web link, and start utilising it’s potential for improving sustainability through better control and awareness.<br />
  25. 25. Continuous Optimisation – Flowers building ‘night set-back’<br />Electricity profile the week before the damper replacement and night setback initiation<br />Dampers replaced (Mon 5th & Tues 6th October)<br />Night set back initiated Wednesday 7th October<br />kW<br />400<br />320<br />240<br />160<br />80<br />Base load has reduced from 280kW to 210kW<br />
  26. 26. Continuous Optimisation – Carbon Desktop <br />Carbon Desktop<br />
  27. 27. Continuous Optimisation – Carbon Desktop <br />
  28. 28. Continuous Optimisation – Carbon Desktop <br />Pre Set-Back<br />Post Set-Back<br />
  29. 29. Continuous Optimisation – Carbon Desktop <br />Pre Set-Back<br />Weekly range =<br />0.4 tCO2<br />
  30. 30. Continuous Optimisation – Carbon Desktop <br />Post Set-Back<br />Weekly Range = 0.8 tCO2<br />
  31. 31. Continuous Optimisation – Real Time Logging<br />Real Time Logging<br />
  32. 32. Continuous Optimisation – Real Time Logging<br />Real Time Logging<br />Imperial College has spent over £1M in extending our metering capacity in the past 2.5 years.<br />Despite this investment, this growth generally doesn’t extend itself to individual items of plant, which can make assessment of actual load, and any beneficial improvements difficult to monitor.<br />We are introducing ‘Real Time Logging’ utilising meters with radio interfaces linking to an accessible website.<br />This allows us to run real time trials e.g. AHU fan motors with filter changes and verify savings.<br />
  33. 33. Continuous Optimisation – How does ICT support Continuous Optimisation?<br />The use of these approaches, provide fundamental support to our ConCom programme and help to:<br />Raise awareness within the academic community<br />Demonstrate improved sustainable performance<br />Validate data and savings<br />
  34. 34. Continuous Optimisation<br />Academic Community<br />Building Management<br />ICT Services<br />How are we achieving improved sustainability<br />TOGETHER<br />

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