Transcript Document

Optimizing the Assets You Already Have:
Your Best Energy Return on Investment
Session: FAC 5.6
Presented by:
Calvin Wohlert, P.E.
Principal, Solution Dynamics, LLC
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Optimizing the Assets You Already Have:
Your Best Energy Return on Investment
When it comes to obtaining PUE goals, it’s often more about how the
equipment is operated than original system design and equipment
selection. This concept presents a great opportunity to achieve
significant savings with little or no capital investment using what you
already have. By setting up the “right” Key Performance Indicators,
opportunities can be uncovered to implement simple operational
changes or retrofits. This session will present a case study
highlighting actual results obtainable from this approach.
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Agenda
• Selected Case Study
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- Brief Facility Description
- PUE & Findings
- Background on KPIs, & Targets
- Data Point Availability
- Sample Recommend KPIs
- Sample Cost Savings Opportunities
Takeaways and Lessons Learned
Continuous Energy Optimization
Other Examples
Question & Answers
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Case Study Facility Description
Very large data center
~ 25 MW load
Reported PUE between 1.3 and 1.4
Custom and very aggressive electric
utility rate $/kWh
• Third party managed
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Contains both containerized and traditional raised floor server areas
Hot aisle / Cold aisle design
> 200 A/C Units
2 chilled water systems (> 4,000 tons of load ea.) w/ full water side
economizers
• Commissioned < 5 years ago at time of survey
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Scope of Work
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Evaluate available data points, what is being trended and
what isn't, recommend what should be.
What additional high priority data points should be added?
Develop Key Performance Indicator (KPI) recommendations:
I.e. “How to use data points to set up useful KPIs for
managing the facility for increased efficiency and reliability.”
Analyze historical PUE data, and if possible, regress to
weather & data center traffic variables.
And if you see any energy efficiency opportunities while
you’re there, let us know.
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Findings:
center energy consumption or power
PUE = Total data
IT energy consumption or power
• PUE
- Being reported (but not measured)
- Different explanations of how PUE is calculated depending on
when question was asked.
- Because PUE not measured or tracked, no way to develop
multi-variant regression model.
• Available Data Points
- Wealth of data points available
- Few trended beyond 2 weeks
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Findings:
• KPIs
- Because of wealth of data points available many powerful
management KPIs could be easily established
• Energy Cost Savings Opportunities Abounded
- Both energy and water consumption savings.
- Most very low cost / operational because built with the latest
and greatest equipment & systems.
- Significant utility cost savings potential to leverage existing
assets to negotiate even better average utility pricing.
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Background on KPIs, Alerts, and Targets
• KPIs are “virtual” efficiency meters.
• Often ratios, but not always, can be multivariable regressions, or simple curve fits.
• Can alarm some KPIs but exercise caution
• Set KPIs targets
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“You Can’t Manage
What You Don’t
Measure!”
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Benchmark, Measuring & Verifying - an Ongoing
Process
Tracking total facility utility bills is not an
easy or effective method of verifying
savings.
Monthly Bill Data:
Not real time
Very low resolution
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Benchmark, Measuring & Verifying - an Ongoing
Process
15 min data = 35,040 points/yr
Can see hour to hour variations
Spot deviations and correct them quickly.
Ideally you want to be able to:
Monitor conversion efficiencies for secondary utilities
(kWh/Ton, etc.)
Track KPIs with regard to both secondary and primary
utilities.
Benchmark against goals, industry standards, & best
in class.
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Targeting, Tracking, and Goal Setting

Slope / Gradient
(111.9)
Base Load = 58,483 kWh
(Data Traffic)
Target Equation: (kWh) = (111.9 x (Data Traffic) + 58,483 (kWh)
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Key KPI
System
Sub-System
Component
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Selected Data Point Availability
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Selected Data Point Availability
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Recommend
KPIs
Level
KPI
Description and Uses
Available from Existing Data Points?
Key KPI
PUE
Overall Metric rolling up all
efficiencies. Identify performance
against targets
No – Need to interface with separate electrical metering system
and install additional metering points
Key KPI
PUE regression with Outside Air
Temp & Humidity
Same as PUE but normalized for
weather
No – Need to interface with separate electrical metering system
and install additional metering points. Regression analysis also
needed.
System
Total Chilled Water kW/ton
Sum of all kW for both systems as a
function of tonnage
System
Total Chilled Water kW/ton
normalized for weather
Allows more sophisticated alarm setpoints as well as better long term
trending
Yes – provided previous KPI is established. Regression analysis
needed
System
Total chiller kW/ton
Sum of all chiller kW for both systems
as a function of tonnage
Yes – needs to be set up and trended
System
Total chiller kW/ton normalized
for condensing & chilled water
temp.
Allows more sophisticated alarm setpoints
Yes – provided previous KPI is established.
Regression analysis needed
Yes – needs to be set up and trended
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Recommend
KPIs
Level
KPI
Description and Uses
Available from Existing Data Points?
Sub-System
Total Chilled Water kW/ton per
loop
Sum of all kW for each system as a
function of tonnage
Sub-System
Total chiller kW/ton per loop
normalized for condensing &
chilled water temp
Allows more sophisticated alarm setpoints
Yes – provided previous KPI is established.
Regression analysis needed
Sub-System
Storage availability on each loop
Monitor capacity for absorbing load
Yes – needs to be set up, calculated and trended
Mode Status
Compare Chiller, Economizer and preeconomizer modes to wet bulb and
alarm if free cooling isn't being utilized
Sub-System
Yes – needs to be set up and trended, non-metered pumps may
need to be spot measured and applied a value
Yes – needs to be setup and trended
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Level
KPI
Recommend
KPIs
Description and Uses
Available from Existing Data Points?
Component
Chiller kW/ton normalized for
condensing & chilled water temp
Too high indicates inefficiency. Set
target/alarm range based on manufacturer
specs
Yes – needs to be setup and trended. Regression analysis needed to generate
target values
Component
Cooling tower kW/MMBtuh
Too high indicates inefficiency. Set
target/alarm range based on manufacturer
specs
Yes – needs to be setup and trended. Will need to calculate MMBtuh based
on chiller load and kW
Component
Evaporator approach F (based on % full
load)
Too high could indicate fouling or flow
problems.
Set target/alarm range based on manufacturer
specs
Yes – needs to be setup and trended. Can further refine based on UA*dT HX
Calculation vs. predicted Btuh heat XFR from chiller load
Component
Cooling tower approach to wet bulb
(based on % full load)
Too high could indicate fouling or flow
problems.
Set target/alarm range based on manufacturer
specs
Yes – needs reliable archiving & will need to calculate MMBtuh to condenser
based on chiller load and kW
Component
Trend and Alarm Surge Count on Chillers
Identification of problems to avoid reliability
impacts
Yes – need archived and trended
Component
Makeup meters to towers vs. calculated
tonnage to towers
Detect wasted water
No – meters not fully operational
Component
Non-condensables in chiller (drop leg
temp vs. SCT)
Helps to determine if chiller has loss of
efficiency due to non-condensibales in
refrigerant loop.
No – data is available at chiller panel but presently not picked up by system.
Requires refrigerant property calculation
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Sample Data - Identified Chiller Savings
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Sample Data Identified Chiller Savings
• ~ $100,000 Annual Electric Savings
• Cost = $13,300, Rebate = $13,300 => Net Cost $0
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Sample Data Identified Chiller Savings
• ~ $142,000 Annual Electric Savings
• Cost = $25,000, Rebate = $25,000 => Net Cost $0
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Sample Data Identified Chiller Savings
Very Good Approach!
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Sample Data Identified Chiller Savings
• ~ $125,000 - $150,000 Annual
Electric Savings
• Cost = $0 to $10,000, Rebate = $0 to
$10,000 => Net Cost $0
• Options are basic lowering of set
point or programming a more
aggressive dynamic reset based on
chiller surge line curve.
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Summary of Recommended Utility Cost Savings
Chilled Water System:
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9 opportunities, $425,000/yr. savings, all low cost/no cost.
Air Handling Systems:
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7 opportunities, $285,000/yr. savings, $325,000/yr. imp costs (after $281,000 in rebates)
Lighting Controls:
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$32,000/yr savings, low cost/no cost (after rebates)
Thermal Storage:
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$250,000/yr savings, $500,000 implementation cost, + added reliability, using existing system, re-piping and
revising controls.
Demand Response:
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$150,000/yr. savings, low cost/no cost using existing assets w/out negative impact on reliability or service.
Water savings = 6,000,000 gal./yr.
PUE moves from 1.5 to 1.35
Total: Annual Energy Savings = $960,000, Total Installed Cost = $825,000
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Takeaways and Lessons
Learned
1.
How energy is purchased can have a large impact on how energy use can be
managed to save money & vice versa.
2.
Understand exactly how your top KPI (PUE) is calculated or measured.
3.
Leverage the tools and resources you already have available to create
continuous commissioning / ongoing diagnostics via KPI’s, alerts and targets
to keep your systems operating at peak efficiency and to avoid potential
reliability impacting situations.
4.
Just because a facility is built with the latest and greatest equipment does not
mean there is little opportunity for improvement. In fact, there can be great
opportunity to leverage the assets (and data) you already have to achieve
significant savings at minimal investment.
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Continuous Energy Optimization
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Generic Example
Example: 600 Ton Chiller
Average annual electric cost to run chiller = $145,656
(Assuming: 0.68kw/ton ave., $0.075/kwh, 70% ave. LF, 6,800 hrs/yr)
© 2011 Solution Dynamics, LLC
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600 Ton Chiller
Chiller Life Cycle Owning & Operating Costs
Initial Equip. Cost,
$270,000 , 14%
Maintenance Cost,
$74,189 , 4%
Energy Cost,
$1,637,278 , 82%
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Example Chiller:
A centrifugal water chiller can easily lose as much as 30% efficiency
and still appear to be operating normal.
If our 600 ton chiller was operating with a 15% efficiency loss the
actual operating cost would go up to $167,500 / yr.
$21,845 / year ENERGY WASTE!!!
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Example: Chiller Plant - Further
Maintenance tasks based on need not an arbitrary or OEM schedule
for activities such as:
Tube brushing
Leak testing
Oil changes
Paradigm shift from a scheduled to a predictive maintenance program
results in additional cost savings
Do you brush condenser tubes every year?
By analyzing tube fouling using CEO, tube cleaning is done only when it is
needed.
Typical tube brushing for a chiller costs $1,500 per year.
Cost of unscheduled downtime – HUGE!
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6:
30
7: AM
55
9: AM
2
10 0 A
:4 M
5
12 AM
:1
0
1: PM
35
3: P M
00
4: P M
25
5: P M
50
7: P M
15
8: P M
4
10 0 P M
:0
11 5 PM
:3
12 0 P
:5 M
5
2: AM
20
3: AM
45
5: AM
10
6: AM
35
8: AM
00
9: AM
2
10 5 A
:5 M
0
12 AM
:1
5
1: PM
40
3: P M
05
4: P M
30
5: P M
55
7: P M
20
8: P M
4
10 5 P M
:1
11 0 PM
:3
5
PM
Temp (F) / Amps
60
50
40
60%
30
50%
40%
20
10
0
MA Temp
Weather Stat OAT
Heating delta T
% Outside Air
Example - Air Handling Unit
Air Handling Unit Monitoring Results - Partial Data
100%
90%
80%
70%
30%
20%
10%
0%
Fraction OA
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Example - Air Handling Unit
Air Handling Unit Monitoring Results - Partial Data
60
100%
Economizer not
functioning properly
90%
70%
MA temp floating around and not
being controlled properly
60%
30
50%
40%
OA minimum = approx. 50%
Space is being over ventilated
20
% Outside Air
40
80%
30%
20%
10
10%
Unit running at night
0
0%
6:
30
7: AM
55
9: AM
2
10 0 A
:4 M
5
12 AM
:1
0
1: PM
35
3: P M
00
4: P M
25
5: P M
50
7: P M
15
8: P M
4
10 0 P M
:0
11 5 PM
:3
12 0 P
:5 M
5
2: AM
20
3: AM
45
5: AM
10
6: AM
35
8: AM
00
9: AM
2
10 5 A
:5 M
0
12 AM
:1
5
1: PM
40
3: P M
05
4: P M
30
5: P M
55
7: P M
20
8: P M
4
10 5 P M
:1
11 0 PM
:3
5
PM
Temp (F) / Amps
50
Heating valve stuck on
or leaking
MA Temp
Weather Stat OAT
Heating delta T
Fraction OA
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Other Example:
Data & Telecom Company:
• 12 facilities in eight states in 90
days.
(over 2,500,000 SF of office and data center space)
• Included many low
cost/operational opportunities
(About $600,000 of savings in low cost projects with
under a year payback just in the first 6 sites visited)
• Followed by 38 facilities: over $3,600,000 in annual
energy savings at an average internal rate of return of
over 38.5%
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Thank You
Questions?
Presented by:
Calvin Wohlert, P.E.
Principal, Solution Dynamics, LLC
Phone: 815-436-5560
Email: [email protected]
Web Site: www.sol-dyn.com
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