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Energy Use Analysis:Value, Pitfalls, Mistakes and
Best Practice
By Anatoli Naoumov, GreenQ Partners
Objective
Demonstrate how energy use analysis helps engineers
buy, sell and implement more and better energy projects
Take away message
Proper analysis of energy use will help me Buy/sell energy projects faster and Gain praise, professional satisfaction and good night sleep
Plan
What is the right tool and why?
What’s in it for me?
How to calculate savings by IPMVP?
How to find new projects?
How not to do analysis?
When looking at projects, CFO …
Core business
Energy projects
Knows how it works? Yes Nope
Has done it before? Yes You wishHas reliable numbers to prove results? Yes ?Acceptable return 10% 50%
When looking at projects, CFO …
Core business
Energy projects
Knows how it works? Yes Nope
Has done it before? Yes You wishHas reliable numbers to prove results? Yes ?Acceptable return 10% 50%
Proper tool …
1. Is as simple as possible, but not simpler2. Links results to business3. Delivers much more value than it costs
Goal-oriented Energy Analysis and Reporting -
GEAR
EMs: GEAR assures good night sleep
Common approaches to measuring results: “It’s obvious, just look at the Amps” “Accountants will calculate” “Vendor will calculate”
Proper GEAR:
Pre-agreed result assessment procedure
based on data and linked to key business indicators
Vendors: GEAR helps build business
Win projects on value
Make results count in the Boardroom
Make client happy
Satisfied clients send chequesHappy clients also send referrals
EMs and Vendors:risks and pains with no right GEAR
Frustratingly long sales cycle
Unconvincing Boardroom presentations
At risk: Satisfaction, recognition, career, job
Determine reduction by IPMVP
Before implementation: Identify and measure key consumption drivers and consumption
through the same period Build a statistically valid baseline Record all non-measured factors that affect consumption
After: Measure drivers and calculate Expected consumption Measure Actual consumption Check if factors are still the same, else adjust baseline
Reduction = Expected – Actual ±adjustments
Watch for pitfalls
• Understand accuracy and certainty of statistics-based baseline; agree on them with decision-maker
• Monitor data for human error
• Check dates: production is often recorded later
• Use engineering common sense to validate model
Demand profile shows possible waste
<1% of time demand
exceeded 450kW
25% of the time demand was under 50kW
40% of the time demand was over
almost 300kW
Is there a problem?
1-Jan
-10
1-Mar-
10
1-May
-10
1-Jul-
10
1-Sep
-10
1-Nov
-10
1-Jan
-11
1-Mar-
11
1-May
-11
1-Jul-
11
1-Sep
-11
1-Nov
-11
1-Jan
-12
1-Mar-
12
1-May
-12
1-Jul-
12
1-Sep
-12
1-Nov
-12
1-Jan
-13
1-Mar-
13
1-May
-13
1-Jul-
13
1-Sep
-13
1-Nov
-13
1-Jan
-14
1-Mar-
14
1-May
-14
1-Jul-
14
1-Sep
-14 20,000
25,000
30,000
35,000
15.0
20.0
25.0
30.0
35.0
Nat. gas, m3
Ove
n co
nsum
ptio
n, m
3
Con
sum
ptio
n ra
te, m
3 /ton
CUSUM analysis
April
Baseline
CUSUM analysis and result
April
Baseline
Oven recalibration
Result of calibration
1-Jan
-10
1-Mar-
10
1-May
-10
1-Jul-
10
1-Sep
-10
1-Nov
-10
1-Jan
-11
1-Mar-
11
1-May
-11
1-Jul-
11
1-Sep
-11
1-Nov
-11
1-Jan
-12
1-Mar-
12
1-May
-12
1-Jul-
12
1-Sep
-12
1-Nov
-12
1-Jan
-13
1-Mar-
13
1-May
-13
1-Jul-
13
1-Sep
-13
1-Nov
-13
1-Jan
-14
1-Mar-
14
1-May
-14
1-Jul-
14
1-Sep
-14 20,000
25,000
30,000
35,000
15.0
20.0
25.0
30.0
35.0
Nat. gas, m3
After recalibration in Jan 2014 consumption rate dropped below 2010 level
Value of Energy ManagerNew Plant Manager
$115K per year
CUSU
M, k
Wh
Major retrofit
$240K per year
How useful is this dashboard?
Saved a lot of natural gas in 2016?
m3 per unit
2014 1.39
2015 1.54
2016 1.26
… or not?
2014 (part) 2015 2015 (part)
Take away message
For a copy of this presentation with notes and hidden slides
please contact Anatoli Naoumov [email protected]
Visit us at www.greenq.ca or call 416-728-7239Subscribe to our blog at www.greenq.ca/blog
Proper GEAR => more business and less hassle
Thank you
