Regional Technical Forum

Recommissioning commercial retail facilities:A whole building approach to energy savings

April 7th, 2009Presented by:Jeremy Litow

Jamie AnthonyMark Effinger

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Recommissioning commercial retail facilities:A whole building approach to quantifying energy

savings• Overview

– Goal today: RTF provisional approval of approach for pilot projects

– In brief:• Project approach and value• Market potential and benefits

– In detail• Origins• Energy savings methodology

– Next steps

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Project approach and value• What is whole building

recommissioning?– Optimize all building

systems, 80%+ of usage• Why is it a useful approach?

– Missed opportunities• Why now? Evolution

• Market– Energy cost– Technology

• Program– Technical approach– Persistence

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Overview - project approach

• Interval metering at the building level, pre and post

• Pre inspection and documentation, sensors and logs

• Recommissioning process• Post inspection and

documentation• Energy savings quantified (more

later)• Persistence monitoring (three

year)

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Market potential

• Building types – refrigeration is important– Convenience stores– Grocery stores and standard supermarkets– Large stores

• Savings range– Average of 7-10% annual savings– Typical range 5-15%– 1 in 10, 20% or more possible

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Benefits of taking a whole building approach

• Big picture– Leveraging AMI investments– Leadership

• Capacity building• Drive market to systems

approach– Measurement to determine savings

more powerful than estimation

• Local picture - Optimized buildings– Systems approach

• No missed opportunities– Persistence monitoring (3 years)

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Origins of the whole building approachand basis of the methodology

• Long history, 1980s PRISM • IPMVP, 1997• ASHRAE Guideline (GL) 14-2002• ASHRAE Research project 1050, 2002• California Commissioning Collaborative – Guideline for

Verifying Existing Building Project Savings Using Interval Data Energy Models: IPMVP Options B and C, 2008

• “Verification of Savings” methodology– Whole building energy use– Many, interactive ECMs

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Verification of whole building approach:normalized savings

1. Acquire baseline data, utility or logged2. Model energy use as function of variable(s) (e.g. DB) for pre ReCx3. Estimate savings and savings uncertainty and required post period4. Acquire post-ReCx data, utility or logged5. Model energy use as function of variable(s) for post6. Drive each model with “normal” conditions (TMY or influential

variables) to determine annualized pre and post energy use7. Savings = modeled annualized baseline - modeled, annualized post-

ReCx8. Evaluate overall uncertainty using ASHRAE GL 14

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Verification of Savings (VoS) methodology: discussion of the method, 1

VoS is a proven method• Change point model, all hourly power data points with

corresponding DB temperature– We also looked at other methodologies

4 Parameter model

Ambient Temp

B3

C

Ene

rgy

use B2

B1

B1

C

Ambient Temp

Ene

rgy

use

2 Parameter model

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Verification of savings methodology: discussion of the method, 2

Example follows a proven method among several options

• Method uses statistics to determine accuracy– R2: proportion of variability in a data set that is accounted for by the

statistical model• 0 to 1 range, >.7 considered “good”

– CV (RMSE): differences between values predicted by a model and the values actually observed from the thing being modeled

• %, <7% “good”– R2: provides a measure of how well future outcomes are likely to be

predicted by the model. – CV (RMSE): evaluates the relative closeness of the predictions to

the actual values

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Verification of savings methodology: discussion of the method, 3

Example follows a proven method among several options

• Range of post data to see temp variation, typically over swing season

• Latent loads (case infiltration/defrost) accounted for?– DB is proven for other building types– DB is provides best correlation to power vs. WB, RH, DP, W– Will look at other variables, evaluate if DB is best for PNW CZ

and refrigeration– Need to field test

• Estimated savings uncertainty–CCC meets approach, ASHRAE GL 14 requirements– 68% confidence with < or = to 50% uncertainty ok

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Example: Verification of savings methodology

• Sample site– Grocery 100,000 ft2

– ReCx and retrofits– 591 days of interval data

• 411 pre• 180 post

– OAT DB 1F to 110F• Average 56F

– RH 4.5-100%• Average 53%

– Observed OAT 73% of TMY range

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Energy savings calculation methodology• Change point on all data, DB

R squared: .74 and .64CV (RMSE): 5.5% and 5.2%Annual savings: 541,520 kwh

Post change point

Pre change point

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Energy savings calculation methodology

• Method comparisons

1. Change point on all data, DB2. Change point on all data, WB3. Linear on all data, DB4. Linear on all data, WB5. 2nd degree polynomial, averaged power vs. weather bin, DB6. 2nd degree polynomial on all data, DB7. 2nd degree polynomial on all data, WB

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Energy savings calculation methodology

• Other areas of interest– Post period perspectives

• Post ReCx duration– Season very important, range of temperatures needed– Period can be shorter if timed right

• Estimated savings uncertainty

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Post period duration and timing1+ year pre project: R2 .72 and CV RMSE 5.7%

Change point for this building, this CZ

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Post period duration and timing2 months post project Dec 07-Jan 08: R2 .27 and CV RMSE 6.7%

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Post period duration and timing2 months post project Mar-Apr 08: R2 .69 and CV RMSE 4.2%

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Post period duration and timing3 months post project Dec 07-Feb 08: R2 .36 and CV RMSE 6.2%

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Post period duration and timing3 months post project Feb-Apr 08: R2 .67 and CV RMSE 4.8%

Nearly as good as 5th mos post!

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Post period duration and timing4 months post project Dec 07- Mar 08: R2 .49 and CV RMSE 5.8%

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Post period duration and timing5 months post project Dec 07- April 08: R2 .60 and CV RMSE 5.6%

Appropriate change point visible

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ProjDate 9/24/07 23:15 Last DateTime in BaselineConfLvl 68% Required Confidence Level

p 4 Number of Parameters in Modelm 3588 Anticipated Number of Post PointsF 12.3% Anticipated Savings Percentage

Regression DataBaseline Post

Intercept 340.4608 272.8681 Intercept at T= 0 ºFSlope 2.5932 2.6280 SlopeAvgY 503.00 406.94 Average YAvgX 62.68 51.02 Average XRSQ 0.6556 0.6568 R-squared

SteyX 31.8008 20.6926 Standard ErrorStdErrorPct 6.3% 5.1% Standard Error, % of Average

CVRMSE 5.4% 5.1% CVRMSErho 0.817 rho=autocorrelation coefficient

n 8438 Number of Baseline Pointsnprime 849 No. Base Pts. Adjusted for Autocorrelation

tStat 0.99 t-statisticDevSqX 2,415,298 SumOfSquaresX

2.9% Fractional Savings Uncertainty12.3% ± 0.2% Savings Range

-0.247% Net Determination BiasStdev Resids 27 21 Standard Deviation of the Residuals

Energy savings calculation methodology• Uncertainty – using CCC Verification of Savings method

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Conclusions on methodology

• Use change point models with driving variable(s)• Look for importance of latent loads in pilots• Post required will vary with season

– Shorter in the spring than in the winter• Uncertainty – follows VoS guidance, meets ASHRAE GL 14

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Next steps – pilots

• Provisional approval to claim savings using this approach

• Pilots on several facilities• Refine approach• Present findings to RTF

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Recommissioning commercial retail facilities:A whole building approach to energy savings

Discussion