Upload
devlin
View
47
Download
0
Tags:
Embed Size (px)
DESCRIPTION
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. - PowerPoint PPT Presentation
Citation preview
Continuous Optimisation
JISC Improved Sustainability Across Estates
Through The Use of ICT
Continuous Optimisation – an Imperial College estatesinitiative 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 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.
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’
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
Savings kWh £ CO2 TonnesNight Set Back 273,000 23,342 145.8
Reduce daytime pressure 218,400 18,673 116.6
Heating & Cooling 70,175 6,000 37.5
Add weekends 28,080 2,401 15.0
Total 589,655 44,416 315
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
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, £31,450 275 tonnesCO2
Continuous Optimisation – Air change rationalisation
14
Floor area served m2 Volume served m3/sFloor AHU 1 AHU 2 AHU 3 AHU 1 AHU 2 AHU 3
2 196.35 196.35 392.7 540.0 540.0 1079.93 196.35 196.35 392.7 540.0 540.0 1079.94 196.35 196.35 151.8 540.0 540.0 417.55 196.35 196.35 540.0 540.0 6 196.35 196.35 540.0 540.0
981.75 981.75 937.2 2,700 2,700 2,577
Air delivered (design) m3/s 7.96 8.34 9.89Air delivered (measured 2010) m3/s 8.16 8.77 10.37Air Delivered (setback) m3/s 5.97 8.09 7.56
ACH (design) 10.6 11.1 13.2ACH (measured 2010) 10.9 11.7 13.8ACH (setback) 8.0 10.8 10.1
Continuous Optimisation – Air change rationalisation
15
AHU 1 AHU 2 AHU 3 TOTAL20 20.5 30
73% 92% 73%10 3 1587,600 26,937 131,400 245,937£5,694 £1,751 £8,541 £15,986
47.65 14.65 71.48 133.79tonnes CO2 saved
Approx kW reduction based on Trilon email 15/9/10
kW of fan as foundReduction in volume
kWh reduction over year
Fan power savings
Electricity cost saving @ 6.5p/kWh
AHU 1 AHU 2 AHU 3 Total284,896 84,294 348,333 717,523
£5,698 £1,686 £6,967 £14,35052.42 15.51 64.09 132.02
AHU 1 AHU 2 AHU 3 Total7,625 1,852 7,652 17,128£496 £120 £497 £1,1134.15 1.01 4.16 9.32
AHU 1 AHU 2 AHU 3 Total292,520 86,146 355,985 734,651
£6,194 £1,806 £7,464 £15,46456.57 16.52 68.26 141.34
tonnes CO2
tonnes CO2
kWh£
kWh£
Boiler saving
Chiller saving
Total Heating & Cooling SavingkWh£tonnes CO2
AHU 1 AHU 2 AHU 3 TOTAL380,120 113,083 487,385 980,588£11,888 £3,557 £16,005 £31,450
104.22 31.17 139.74 275.13
Total energy savingkWh reduction over yearCost savingtonnes CO2 saved
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 series 30% E £19.73Basic economic bag ~ 300mm deep
S Flo – WP series 50% E £18.23Basic economic bag ~ 500+mm deep
Opakfil Green 20% A £60.68Energy efficient “rigid” bagUsed at SAF
Hi Flo – M series 0% A £48.05
Energy efficient – high surface area bagNot used anywhere at IC yet.
Continuous Optimisation – Filter Optimisation
20
No Measure Implement Immediately?
Energy Savings (kWh/yr)
CO2 Savings
(tonnes/yr)
Energy Cost
Savings (£/yr)
Total Life
Cycle Cost
Savings - LCC (£/yr)
SAF 1 Replace HEPAs (H13 to H10) YES 50,430 27 £3,278 £3,278
SAF 2 Replace standard G4 panels with 30/30 panels (implemented) YES 64,347 35 £4,183 £2,574
SAF 3 Replace Opakfil Bags with Hi Flo and remove Panels NO - TRIAL REQ’D 138,325 5 £9,129 £8,037
253,102 67 £16,590 £13,889
No Measure Energy Savings (kWh/yr)
CO2 Savings
(tonnes/yr)
Energy Savings
(£/yr)
Total Cost
Savings LCC (£/yr)
1-10 All filters measures above 2,271,765 1,156 £146,710 £87,008
Continuous Optimisation – Filter Optimisation
21
NoMeasure
Implement Immediately?
Savings
Current Proposed Energy (kWh/yr)
CO2 (tonnes/yr)
Cost(£/yr)
Total Life Cycle Cost - LCC (£/yr)
1 HEPAs H13 HEPAs H10 MORE INFO REQ’D TBC TBC TBC TBC
2 Standard G4 panels 30/30 panels YES 252,217 137 £16,394 10,936
3 Pad filters 30/30 pleated panel filters YES 126,108 69 £8,197 5,468
4-6 300 mm Bags 600 mm Hi Flo Bags TRIAL REQ’D 464,447 247 £29460 13,691
7 S Flo (WU) & Opakfil (rigid) Bags
Hi Flo Bags (no panels) YES 87,938 48 £5,716 1,443
8 Change panel filters at lower pressure drop YES 252,217 137 16,394 10,936
9 Change bag filters at lower pressure drop YES 162,848 89 10,585 6,273
10 Improved filters &changing regime for AHUs < 15 kW YES 672,888 363 43,373 24,373
11 (SAF) HEPAs H13 HEPAs H10 YES 50,430 27 £3,278 £3,278
12 (SAF) Standard G4 panels 30/30 panels YES 64,347 35 £4,183 £2,574
13 (SAF) Opakfil Bags Hi Flo bags (no Panels) TRIAL REQ’D 138,325 5 £9,129 £8,037
2,271,765 1,156 £146,710 £87,008
Continuous Optimisation – Filter Optimisation
22
Hi flow bagS 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 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
Continuous Optimisation – Carbon Desktop
Carbon Desktop
Continuous Optimisation – Carbon Desktop
Continuous Optimisation – Carbon Desktop
Pre Set-Back Post 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 tCO2
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