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Continuous Optimisation

Continuous Optimisation. JISC Improved Sustainability Across Estates Through The Use of ICT Continuous Optimisation – an Imperial College estates initiative reducing the carbon consumption of plant & services, and how ICT infrastructure underpins it’s delivery.

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Continuous Optimisation

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  1. Continuous Optimisation JISC Improved Sustainability Across Estates Through The Use of ICT Continuous Optimisation – an Imperial College estates initiative reducing the carbon consumption of plant & services, and how ICT infrastructure underpins it’s delivery

  2. Continuous Optimisation - Content Content • Continuous Optimisation (ConCom) – what is it? • Background • Initiatives • Flowers building ‘night set-back’ • Air change rationalisation • Filter optimisation • How does ICT support Continuous Optimisation? • TREND system • Carbon Desktop • Real Time Logging

  3. Continuous Optimisation Continuous Optimisation (ConCom) – what is it?

  4. Continuous Optimisation - Background Background • Imperial College’s ‘Carbon Management Plan’ requires us to achieve a 20% reduction in carbon consumption by 2014. • 84,026 tCO2 reduced by 16,805tCO2 to 67,221tCO2 • Continuous Optimisation of plant & services, targeted to deliver 4,903tCO2 • This can only be achieved if we have: • Extensive control systems • Robust operational information • The cooperation of the academic community • As a Science, Engineering and Medicine focussed University, our research and teaching relies heavily on controlled environments.

  5. Continuous Optimisation - background • We are challenging how environments were originally commissioned by considering: • The original design, at sign-off • How the environments are now being used • The occupation strategy • What service strategies are really needed to provide, safe and productive environments, without compromising our research & teaching. • Through Continuous Optimisation (continuous commissioning ‘ConCom’), we are implementing: • Air change volume adjustments • AHU operational set-backs (temperature & time) • Introducing more efficient plant • Adjusting pump delivery to meet flow demands • Improving filter efficiencies • Introducing occupancy controls e.g. CO2 sensors, ‘user switches’

  6. Continuous Optimisation – Flowers building ‘night set-back’ Flowers Building ‘Night set-back’ Initiative

  7. Continuous Optimisation – Flowers building ‘night set-back’ Flowers Building ‘Night set-back’ Methodology • We identified Flowers building main air handling services were operating 24 hours a day, 7 days a week • Environmental conditions and operational dependencies were discussed with users • The four supply & extract air handling units were re-commissioned to ensure they could continue to operate to the original design • 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.

  8. Continuous Optimisation – Flowers building ‘night set-back’ Methodology (cont’d) • The energy profile for the building was then measured across a normal week • The new controls and motorised dampers were installed • The air supply pressure was then reduced from 400pa to 300pa • The air volume delivered overnight was reduced to an average of 6 air changes / hour, from 13, between 22.00hrs to 07.00hrs. • The energy profile for the building was measured throughout this process and checked in subsequent weeks. • Further commissioning followed; reducing air pressures, and extending the time to between 18.00hrs to 07.00hrs, more savings resulted.

  9. Continuous Optimisation – Flowers building ‘night set-back’ Savings • The base load has reduced from 280kW to 210 kW a 70kW saving • Day time air pressure was reduced, heating & cooling savings resulted • This realised overall savings of

  10. Continuous Optimisation – Flowers building ‘night set-back’ Electricity profile the week before the damper replacement and night setback initiation Dampers replaced (Mon 5th & Tues 6th October) Night set back initiated Wednesday 7th October kW 400 320 240 160 80 Base load has reduced from 280kW to 210kW

  11. Continuous Optimisation – Air change rationalisation Air Change Rationalisation

  12. Continuous Optimisation – Air change rationalisation Air Change Rationalisation • As part of our ConCom programme we challenge the air change strategy for each building, comparing the design, current operation and recommended standards. • CIBSE guidelines recommend 6 air changes / hr for laboratories. • We find that our environments are commissioned within significant excesses of this standard, often between 10 and 14 air changes / hr. • 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.

  13. Continuous Optimisation – Air change rationalisation • This approach can deliver significant savings through: • reduced fan motor speeds • reduced heating demands • reduced cooling demands • 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: 980,588 kWhrs, £31,450 275 tonnesCO2

  14. Continuous Optimisation – Air change rationalisation

  15. Continuous Optimisation – Air change rationalisation

  16. Continuous Optimisation – Air change rationalisation Carbon Desktop - Electricity demand profile for Transformer 40 - MCP3 at SAF. MCP 3 feeds AHUs 1,2,3, 4, 7,8,17,18,16,9 & 23.  A further £15K in heating and cooling savings using bin weather data.

  17. Continuous Optimisation – Filter Optimisation Filter Optimisation

  18. Continuous Optimisation – Filter Optimisation Filter Optimisation • Most air handling units (AHU’s) have integral filter strategies, applied primarily to supply, and for some applications, the extract. • Filter media provides significant resistance within the air flow path, resistance increases as filters become blocked. • Higher resistance of the filter, results in increased energy consumed by fan motor to provide the required air flow. • 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.

  19. Continuous Optimisation – Filter Optimisation

  20. Continuous Optimisation – Filter Optimisation

  21. Continuous Optimisation – Filter Optimisation

  22. Continuous Optimisation – Filter Optimisation S Flow bag Hi flow bag Opakfil Rigid bag 30/30 Pleated Panel

  23. Continuous Optimisation – How does ICT support Continuous Optimisation? How does ICT support Continuous Optimisation?

  24. Continuous Optimisation – TREND System TREND System (BMS) • Imperial College has the largest TREND Building Management System in the UK (original installation commenced1996). • Traditionally it has been used to monitor the operational status of plant & services and in particular, plant failure (replaced Sauter). • This system was stand alone with a ‘hard wired’ network, which as it grew, became less reliable and access speed slowed significantly. • 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. • 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.

  25. Continuous Optimisation – Flowers building ‘night set-back’ Electricity profile the week before the damper replacement and night setback initiation Dampers replaced (Mon 5th & Tues 6th October) Night set back initiated Wednesday 7th October kW 400 320 240 160 80 Base load has reduced from 280kW to 210kW

  26. Continuous Optimisation – Carbon Desktop Carbon Desktop

  27. Continuous Optimisation – Carbon Desktop

  28. Continuous Optimisation – Carbon Desktop Pre Set-Back Post Set-Back

  29. Continuous Optimisation – Carbon Desktop Pre Set-Back Weekly range = 0.4 tCO2

  30. Continuous Optimisation – Carbon Desktop Post Set-Back Weekly Range = 0.8 tCO2

  31. Continuous Optimisation – Real Time Logging Real Time Logging

  32. Continuous Optimisation – Real Time Logging Real Time Logging • Imperial College has spent over £1M in extending our metering capacity in the past 2.5 years. • 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. • We are introducing ‘Real Time Logging’ utilising meters with radio interfaces linking to an accessible website. • This allows us to run real time trials e.g. AHU fan motors with filter changes and verify savings.

  33. Continuous Optimisation – How does ICT support Continuous Optimisation? • The use of these approaches, provide fundamental support to our ConCom programme and help to: • Raise awareness within the academic community • Demonstrate improved sustainable performance • Validate data and savings

  34. Academic Community Building Management ICT Services Continuous Optimisation How are we achieving improved sustainability TOGETHER

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