Energy Savings Through Metering
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Andy Watson Director – Sim Energy Ltd In partnership with BMSi Ltd Energy Savings Through Energy Savings Through Metering Metering
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This presentation provides details about how exactly to get the most from the data available from energy meters.It is acknowledged by those working in the energy industry that it is rare for more than 50% of the savings potential available from metered data is used. This presentation points to where to find those "hidden" savings. Pleace contact me for more information.
Transcript of Energy Savings Through Metering
Andy WatsonDirector – Sim Energy Ltd
In partnership with BMSi Ltd
Energy Savings Through Energy Savings Through MeteringMetering
Why meter?Why meter?
• “You cannot manage what you cannot measure”
• But you can reduce energy consumption without metering….!
• You cannot know how efficient plant:• Should be• Could be• Is
What benefit
M&TDevelopment &
Interaction
Returns
Devolvement
Install
Raw data & quick wins
Benchmarking & exception reports
Driving factor and CUSUM analysis
Model study…
• A most unusual building…
Phase 1 - What would you normally get…
Quarterly useage Quarterly cost
Summary Electricity Gas Electricity Gas
Spring 96,041 37,230 £ 9,604 £ 1,117
Summer 166,431 14,673 £ 16,643 £ 440
Autumn 104,636 26,864 £ 10,464 £ 806
Winter 103,888 96,360 £ 10,389 £ 2,891
Total 470,996 175,127 £ 47,099.60 £5,253.81
Phase 2 – AMR and 24hr profiles
Electricity - Spring
0
20
40
60
80
100
120
00:0
001
:00
02:0
003
:00
04:0
005
:00
06:0
007
:00
08:0
009
:00
10:0
011
:00
12:0
013
:00
14:0
015
:00
16:0
017
:00
18:0
019
:00
20:0
021
:00
22:0
023
:00
Electricity - Summer
0
20
40
60
80
100
120
00:0
001
:00
02:0
003
:00
04:0
005
:00
06:0
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08:0
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10:0
011
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12:0
013
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14:0
015
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017
:00
18:0
019
:00
20:0
021
:00
22:0
023
:00
kW
Electricity - Autumn
0
20
40
60
80
100
120
00:0
001
:00
02:0
003
:00
04:0
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10:0
011
:00
12:0
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:00
14:0
015
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16:0
017
:00
18:0
019
:00
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021
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22:0
023
:00
kW
Electricity - Winter
0
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40
60
80
100
120
00:0
001
:00
02:0
003
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kW
Gas - Spring
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50
00:00
02:00
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06:00
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kW
Gas - Summer
05
101520253035404550
00:00
02:00
04:00
06:00
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10:00
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14:00
16:00
18:00
20:00
22:00
kW
Gas - Autumn
05
101520253035404550
00:0
0
01:0
0
02:0
0
03:0
0
04:0
0
05:0
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10:0
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11:0
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12:0
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16:0
0
17:0
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18:0
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19:0
0
20:0
0
21:0
0
22:0
0
23:0
0
kW
Gas - Winter
05
101520253035404550
00:0
0
01:0
0
02:0
0
03:0
0
04:0
0
05:0
0
06:0
0
07:0
0
08:0
0
09:0
0
10:0
0
11:0
0
12:0
0
13:0
0
14:0
0
15:0
0
16:0
0
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0
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19:0
0
20:0
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kW
Phase 3 – Energy Management Strategy
• Improve granularity of data – install more meters
• Group into asset types:– HVAC– Lighting– Small power etc
• Analyse asset loads• Identify quick wins
Electricity - Spring
0
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100
120
00:00
02:00
04:00
06:00
08:00
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12:00
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22:00
kW
Lifts
Small power
Lighting
AHU
Chiller
Electricity - Summer
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20
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120
00:00
02:00
04:00
06:00
08:00
10:00
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22:00
kW
Lifts
Small power
Lighting
AHU
Chiller
Electricity - Autumn
0
20
40
60
80
100
120
00:00
02:00
04:00
06:00
08:00
10:00
12:00
14:00
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kW
Lifts
Small power
Lighting
AHU
Chiller
Electricity - Winter
0
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kW
Lifts
Small power
Lighting
AHU
Chiller
Quick wins…
• Chilling fighting the heating• Lighting and small power left on at
night• Building being conditioned at
night/weekends
10 – 20% improvement possible
Benchmarking and exceptions
• Feature of most energy databases• Requires historical or industry data to make
benchmarks• Dynamic benchmarking• DRIVING FACTORS:
– By nature of business• Property – energy/m2
• Manufacturing – energy/item made• Commercial – energy/turnover
– By nature of equipment• Air conditioning – energy/Degree day• Escalators – energy/m ascent
• leading to…
Cumulative Sum Analysis (CUSUM)
1. Establish a record 1. Establish a record of driving factor of driving factor against energy useagainst energy use
y = 22.568x + 61.55R2 = 0.96
0
100
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0 5 10 15 20 25
Temp
En
erg
y
2. Plot a scatter graph 2. Plot a scatter graph and establish a trendand establish a trend
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Day
En
erg
y
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Tem
p Prediction
Actual
Temp
3. Make predictions and record actual consumption
(60)
(40)
(20)
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
4. Calculate the variation between predicted and actual consumption
(200)
(100)
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Day
CU
SU
M e
ner
gy
5. Cumulatively sum the variations
Identify:• Stable performance• Optimum performance• Problems stabilising• Effects of energy efficiency on stable operation
Example – 3 storey common user office building – chiller energy
Stable operation Fault Fault stabilises Repair Energy efficiencyinstalled
Electricity - Spring
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20
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80
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120
00:00
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04:00
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22:00
kW
Lifts
Small power
Lighting
AHU
Chiller
Electricity - Spring
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kW
Lifts
Small power
Lighting
AHU
Chiller
Electricity - Summer
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120
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02:00
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06:00
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kW
Lifts
Small power
Lighting
AHU
Chiller
Electricity - Summer
0
20
40
60
80
100
120
00:00
02:00
04:00
06:00
08:00
10:00
12:00
14:00
16:00
18:00
20:00
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kW
Lifts
Small power
Lighting
AHU
Chiller
Electricity - Autumn
0
20
40
60
80
100
120
00:00
02:00
04:00
06:00
08:00
10:00
12:00
14:00
16:00
18:00
20:00
22:00
kW
Lifts
Small power
Lighting
AHU
Chiller
Electricity - Autumn
0
20
40
60
80
100
120
00:00
02:00
04:00
06:00
08:00
10:00
12:00
14:00
16:00
18:00
20:00
22:00
kW
Lifts
Small power
Lighting
AHU
Chiller
Electricity - Winter
0
20
40
60
80
100
120
00:00
02:00
04:00
06:00
08:00
10:00
12:00
14:00
16:00
18:00
20:00
22:00
kW
Lifts
Small power
Lighting
AHU
Chiller
Electricity - Winter
0
20
40
60
80
100
120
00:00
02:00
04:00
06:00
08:00
10:00
12:00
14:00
16:00
18:00
20:00
22:00
kW
Lifts
Small power
Lighting
AHU
Chiller
Gas - Spring
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10
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40
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kW
Gas - Summer
05
101520253035404550
kW
Gas - Autumn
05
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00:0
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01:0
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02:0
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12:0
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13:0
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15:0
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16:0
0
17:0
0
18:0
0
19:0
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20:0
0
21:0
0
22:0
0
23:0
0
kW
Gas - Winter
05
101520253035404550
00:0
0
01:0
0
02:0
0
03:0
0
04:0
0
05:0
0
06:0
0
07:0
0
08:0
0
09:0
0
10:0
0
11:0
0
12:0
0
13:0
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kW
Typical savings
30 – 60% by implementation of a full PI strategy including:
• metering• improved controls• behavioural change• devolved responsibility
40% saving in consumption through better control only!
£47,100
£5,254
£52,353
£28,982
£2,310
£31,292
£-
£10,000
£20,000
£30,000
£40,000
£50,000
£60,000
Electricity Gas Total
Typical
Improved
Further references
• Vilnis Vesma - http://vesma.com/
Good Practise examples
0
500000
1000000
1500000
2000000
2500000
3000000
3500000
4000000
4500000
0
50
100
150
200
250
300
350
400
450
CONSUMPTION
Av Degree days
Terminal 4, Heathrow Airport
The benefits
Measured savings after programme (extrapolated to one year):– £136k per annum– 2.7 GWh– 108 CO2 tonnes
– 13% saving on T4 total power
Latest detailed HV reading:• March 2005
– 27% below average monthly consumption– 37% below March 2004 consumption– 17% below March 2003 consumption– Lowest monthly consumption in five years
Good Practise Examples
Heathrow Point Complex – 3 multi-use office buildings
HPW Annual kWh
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0:00
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Average WD
Average WE
HPN Annual kWH
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35
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1:00
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Average WD
Average WE
HPTC Annual kWh
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1:00
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3:00
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5:00
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7:00
8:00
9:00
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12:00
13:00
14:00
15:00
16:00
17:00
18:00
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23:00
Average WD
Average WE
Building HPW HPN HPTC TotalAnnual cost 121,710£ 16,946£ 34,816£ 173,472£ Baseload % 40% 40% 38%
Eliminate:Weekend load 32,612£ 4,270£ 8,125£ 45,006£ Night load 29,920£ 4,073£ 4,073£ 38,065£
Total saving 83,071£ 48%
Improved annual cost 90,401£
Summary
• Smart metering solution SPB = 1-3 years
• Up to 60% improvement possible• Other requirements:
– Behaviours– Processes/Operations
• Work to get more out of the investment
Thank you for listening
