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

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

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

Continuous Optimisation - Background Background Imperial College’s ‘Carbon Management Plan’ requires us to achieve a 20% reduction in carbon consumption by ,026 tCO 2 reduced by 16,805tCO 2 to 67,221tCO 2 Continuous Optimisation of plant & services, targeted to deliver 4,903tCO 2 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.

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. CO 2 sensors, ‘user switches’

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

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.

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.

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 SavingskWh£CO2 Tonnes Night Set Back273,00023, Reduce daytime pressure218,40018, Heating & Cooling70,1756, Add weekends28,0802, Total589,65544,416315

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

Continuous Optimisation – Air change rationalisation Air Change Rationalisation

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.

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, tonnesCO 2

Continuous Optimisation – Air change rationalisation 14 Floor area served m2Volume served m3/s FloorAHU 1AHU 2AHU 3AHU 1AHU 2AHU ,700 2,577 Air delivered (design) m3/s Air delivered (measured 2010) m3/s Air Delivered (setback) m3/s ACH (design) ACH (measured 2010) ACH (setback)

Continuous Optimisation – Air change rationalisation 15

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. 16

Continuous Optimisation – Filter Optimisation Filter Optimisation

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.

Continuous Optimisation – Filter Optimisation 19 Bag Filters % installed at the IC (approx) Energy Rating Comparative Cost per filter (£) Details S Flo - WU series30%E£19.73 Basic economic bag ~ 300mm deep S Flo – WP series50%E£18.23 Basic economic bag ~ 500+mm deep Opakfil Green20%A£60.68 Energy efficient “rigid” bag Used at SAF Hi Flo – M series0%A£48.05 Energy efficient – high surface area bag Not used anywhere at IC yet.

Continuous Optimisation – Filter Optimisation 20 NoMeasure Implement Immediately? Energy Savings (kWh/yr) CO2 Savings (tonnes/y r) Energy Cost Savings (£/yr) Total Life Cycle Cost Savings - LCC (£/yr) SAF 1Replace HEPAs (H13 to H10) YES50,43027£3,278 SAF 2 Replace standard G4 panels with 30/30 panels (implemented) YES64,34735£4,183£2,574 SAF 3 Replace Opakfil Bags with Hi Flo and remove Panels NO - TRIAL REQ’D138,3255£9,129£8, ,10267£16,590£13,889 NoMeasure Energy Savings (kWh/yr) CO2 Savings (tonnes/y r) Energy Savings (£/yr) Total Cost Savings LCC (£/yr) All filters measures above 2,271,7651,156£146,710£87,008

Continuous Optimisation – Filter Optimisation 21 No Measure Implement Immediately? Savings CurrentProposed Energy (kWh/yr) CO2 (tonnes/yr) Cost (£/yr) Total Life Cycle Cost - LCC (£/yr) 1HEPAs H13HEPAs H10 MORE INFO REQ’D TBC 2Standard G4 panels30/30 panelsYES252,217137£16,39410,936 3Pad filters 30/30 pleated panel filters YES126,10869£8,1975, mm Bags600 mm Hi Flo BagsTRIAL REQ’D464,447247£ ,691 7 S Flo (WU) & Opakfil (rigid) Bags Hi Flo Bags (no panels) YES87,93848£5,7161,443 8Change panel filters at lower pressure dropYES252, ,39410,936 9Change bag filters at lower pressure dropYES162, ,5856, Improved filters &changing regime for AHUs < 15 kW YES672, ,37324, (SAF) HEPAs H13HEPAs H10YES50,43027£3, (SAF) Standard G4 panels30/30 panelsYES64,34735£4,183£2, (SAF) Opakfil BagsHi Flo bags (no Panels)TRIAL REQ’D138,3255£9,129£8,037 2,271,7651,156£146,710£87,008

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

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

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.

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

Continuous Optimisation – Carbon Desktop Carbon Desktop

Continuous Optimisation – Carbon Desktop

Pre Set-BackPost Set-Back

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

Continuous Optimisation – Carbon Desktop Post Set-Back Weekly Range = 0.8 tCO 2

Continuous Optimisation – Real Time Logging Real Time Logging

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.

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

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