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SEEM 94 Calibration to Single Family RBSA Data. Regional Technical Forum January 23, 2013. Introduction. SEEM is used to estimate energy savings for most space-heating-effected residential UES measures Goal Ensure SEEM’s results are grounded in measured space heating energy use. Method - PowerPoint PPT Presentation
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SEEM 94 Calibration to Single Family RBSA Data
Regional Technical ForumJanuary 23, 2013
Analysis Performed By Adam Hadley
Cursory Reviews By Tom Eckman, Ben Larson, David Baylon, Nick O’Neil, Josh Rushton
Presentation By Adam Hadley
Introduction• SEEM is used to estimate energy savings for most space-heating-
effected residential UES measures• Goal
– Ensure SEEM’s results are grounded in measured space heating energy use.
• Method1. Run SEEM using characteristics data from billing analyses and/or
metering reports to define inputs.2. Compare SEEM’s heating energy use outputs to the reports’ findings.3. Modify unknown characteristics data (usually T-stat setting) until a
reasonable match is found.4. Standardize the “calibration inputs” (from step 3) for use in RTF
measure analyses.
Introduction - 2
RTF Guidelines3.3.3.2 Model CalibrationIn most cases, calibrated engineering procedures will involve at least one stage of modeling in which baseline and efficient case energy consumption are estimated for the measure-affected end use. For example, the heating load for single-family homes is estimated as part of the derivation of UES for ductless heat pump conversion. A simulation model is used to derive the heating end use for typical homes in different climate zones. Ideally, the model would be calibrated to measured heating end use for a sample of homes. If end use data are not available, the model should at least be calibrated to metered total use for the sample. Calibration should also be performed for samples that have adopted the measure, i.e., the efficient case. For measures that affect new buildings the calibration may be limited to the efficient case or to comparable buildings of recent vintage.
Introduction - 3
History• 11/9/2009
– SEEM92 Single Family Calibration Approved• 70°F/64°F for Gas FAF and HP’s• 66°F for Electric FAF and Zonal
• 12/13/2011– RTF adopted SEEM 94
• Infiltration Calculation now physics-based (previously assumed at a steady rate)– SEEM94 Manufactured Home Calibration Approved
• 69.4°F/61.9°F for all heating system types
• 9/18/2012– SEEM94 Multi-Family Calibration Approved
• 68°F for walk-up and corridor buildings• 66°F for townhouses
Introduction - 4
Data Sources• SF Data Sources used in previous calibration:
• Data Source used in this calibration:– Underlying database** for the Single Family Residential Building
Stock Assessment (2012)• RBSA study’s database offers recent billing analyses results and detailed
house characteristics on 1404 houses in the Region.• This allows well-defined SEEM runs for each individual house.
Report Date Type n*
Single-Family Residential New Construction Characteristics and Practices Study (RLW for NEEA)
2007 Billing Analysis 114
Analysis of Heat Pump Installation Practices and Performance (Ecotope for NEEA)
2005 Billing Analysis 381
Super Good Cents Metered Data ~1994 Billing Analysis 740
Method - 5
*Sample size used in the calibration exercise (study sample size may have been larger).** Using a pre-release version of the database for this analysis .
Key Model Input Parameters
RBSA Data Availability
UA Available for each house.
Weather Zip code (available for each house) linked to nearest TMY3 weather station.
Gas Heating Efficiency Available for some houses; used average for remaining houses.
HP Operation & Efficiency Not readily available. Used ARI control & 7.9 HSPF.
Duct System Leakage and Surface Area
Available for some houses; used average for remaining houses with ducts.
Duct System Insulation and Location
Available for each house.
Infiltration Available for some houses; used a floor area-scaled average (by foundation type) for remaining houses
Mechanical Ventilation Not available. Assumed 2 hours /day at 50 cfm.
Non-Lighting Internal Gains Not available. See next slide for details.
Lighting Internal Gains LPD available for each house; assumed 1.5 hours/day.
T-stat Setting Available based on interviews, but used this as the “calibration knob”.
Method - 6
Non-Lighting Internal Gains• Equation:
• Based loosely on Building America Benchmark*– Used the original equation and values (averaged) to determine average internal
gains for RBSA homes.• Original equation also includes Number of Bedroom and Finished Floor Area terms
– Set Number of Bedrooms and Finished Floor Area terms to zero and adjusted Number of People term to achieve same average internal gains for RBSA homes.
• Building America Benchmark based on– “The appliance loads were derived by NREL from EnergyGuide labels, a Navigant
analysis of typical models available on the market that meet current NAECA appliance standards, and several other studies. ”
– “The general relationship between appliance loads, number of bedrooms, and house size, was derived empirically from the 2001 RECS. ”
Method - 7
*Hendron, Robert. "Building America Research Benchmark Definition, Updated December 20, 2007." NREL/USDOE EERE. January 2008. NREL/TP-550-42662
Some Houses Unable (or unwilling) to Run with SEEMIssue Count
More than one foundation type 331
25% > Ceiling Area to Floor Area > 200%, or Missing Ceiling U-value 36
Footprint Area to Floor Area < 20% 36
30% > Wall Area to Floor Area > 200%, or Missing Wall U-value 24
Missing Floor U-value for Crawlspace Foundation 5
Window Area = 0 3
Window u-value = 0 3
• Resulting House Count: 1011– These issues overlap on some houses, so the sum of
the counts cannot be subtracted from 1404 to get 1011.
Method - 8
Data FiltersVariable Filter
Value(s)Notes Count
(filtered out)SEEM Run Valid SEEM run must be valid (> 0 kWh/yr). 4
Billing Energy Use > 1,500 kWh/yr
Intends to screen out partially used or unused houses
38
eRsq and gRsq = 0 or ≥0.45
Screens out houses with poor billing analysis results (0.45 per David Baylon)
398
Non-natural-gas & non-electric Fuel Use
0 Screens out houses with wood, oil, propane, etc. consumption because billing analysis not performed.
352
Primary Heating System
eZonal, eFAF, gFAF, HP
Removes gas boilers, wood stoves, etc. 216
Secondary Heating System Fuel
Electric or Gas
Removes wood stoves, propane heaters, etc. 274
• Gas Billing converted to kWh/year using reported AFUE• Resulting House Count: 289• (The counts for each item overlap here, too)
Method - 9
Results
Results - 10
T-Stat Setting “Calibrated” to:Heating System Type
Heating High °F(day)
Heating Low °F(night)
Electric Zonal64 64
Electric FAF
Gas FAF 68.6 63.9
Heat Pump 69.6 65.4
Results - 11
• Electric Zonal and FAF based on results• Gas FAF and Heat Pump based on average
from RBSA (n=1011 subset).
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000
Nor
mal
ized
Billi
ng H
eatin
g U
se (k
Wh/
hr)
SEEM Heating Use (kWh/yr)
80,000 40,000 30,000
Avg. 12,332 11,560 10,868
St. Dev.
9,060 7,205 6,189
Avg. 11,348 11,054 10,819
St. Dev.
7,086 6,783 6,600
kWh 984 506 49
% 9% 5% 0%
289 283 274
P-Value
1.6% 16.0% 87.9%
>.05 ? No Yes Yes
SEEM Heating Use less than
SEEM kWh/yr
Billing kWh/yr
Difference of
Averages
Count
Student's T-test
eZonal, eFAF, gFAF, Heat Pump
Results - 12
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000
Nor
mal
ized
Billi
ng H
eatin
g U
se (k
Wh/
hr)
SEEM Heating Use (kWh/yr)
80,000 40,000 30,000
Avg. 8,876 8,876 8,399
St. Dev.
5,757 5,757 4,838
Avg. 7,922 7,922 7,881
St. Dev.
4,638 4,638 4,681
kWh 954 954 518
% 12% 12% 7%
91 91 89
P-Value
9.7% 9.7% 29.4%
>.05 ? Yes Yes Yes
SEEM Heating Use less than
SEEM kWh/yr
Billing kWh/yr
Difference of
Averages
Count
Student's T-test
eZonal
Results - 13
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000
Nor
mal
ized
Billi
ng H
eatin
g U
se (k
Wh/
hr)
SEEM Heating Use (kWh/yr)
80,000 40,000 30,000
Avg. 14,071 12,471 12,471
St. Dev.
9,558 6,292 6,292
Avg. 12,103 11,963 11,963
St. Dev.
4,872 4,955 4,955
kWh 1968 508 508
% 16% 4% 4%
21 20 20
P-Value
31.2% 69.5% 69.5%
>.05 ? Yes Yes Yes
SEEM Heating Use less than
SEEM kWh/yr
Billing kWh/yr
Difference of
Averages
Count
Student's T-test
eFAF
Results - 14
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000
Nor
mal
ized
Billi
ng H
eatin
g U
se (k
Wh/
hr)
SEEM Heating Use (kWh/yr)
80,000 40,000 30,000
Avg. 17,244 15,909 14,829
St. Dev.
9,863 7,010 5,627
Avg. 15,841 15,365 15,039
St. Dev.
7,098 6,728 6,516
kWh 1402 544 -210
% 9% 4% -1%
125 120 113
P-Value
6.4% 41.2% 72.5%
>.05 ? Yes Yes Yes
SEEM Heating Use less than
SEEM kWh/yr
Billing kWh/yr
Difference of
Averages
Count
Student's T-test
gFAF
Results - 15
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000
Nor
mal
ized
Billi
ng H
eatin
g U
se (k
Wh/
hr)
SEEM Heating Use (kWh/yr)
80,000 40,000 30,000
Avg. 5,873 5,873 5,873
St. Dev.
2,913 2,913 2,913
Avg. 6,239 6,239 6,239
St. Dev.
4,062 4,062 4,062
kWh -366 -366 -366
% -6% -6% -6%
52 52 52
P-Value
48.9% 48.9% 48.9%
>.05 ? Yes Yes Yes
SEEM Heating Use less than
SEEM kWh/yr
Billing kWh/yr
Difference of
Averages
Count
Student's T-test
Heat Pump
Results - 16
Alternative Method• This is how the RTF has performed SEEM calibrations in the past
– Results shown here for comparison; not intended to be used as part of calibration
– Modeling each house is considered a better approach• Compare Averages: RBSA average billing data vs. SEEM runs with
Average RBSA characteristics– Using only RBSA data from the report to define SEEM run characteristics
for the 3 prototypes• Exception: Used database to determine how many R0 duct insulation cases had
ducts inside– Note: Used T-stat setting per RBSA report
• 68.7°F with 65% of homes using a setback to 62.2°F
• Results…
Alternative Method - 17
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
20,000
OR(PDX/SPK)
WA(SEA/SPK)
ID(BOS)
MT(KAL)
Region
Annu
al H
eatin
g U
se (k
Wh/
yr)
City for SEEM TMY3 weather file shown in parenthesis
Electric Space Heating
RBSA Billing90% CI
SEEM
Alternative Method - 18
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
OR(PDX/SPK)
WA(SEA/SPK)
ID(BOS)
MT(KAL)
Region
Annu
al H
eatin
g U
se (k
Wh/
yr)
City for SEEM TMY3 weather file shown in parenthesis
Gas Space Heating
RBSA Billing90% CI
SEEM
Alternative Method - 19
What are the Takeaways?• Key SEEM inputs RTF carries forward
for future Single Family space heating modeling:– Tstat settings (see table)– Internal Gains Method
• Non-lighting: Use modified equation with RBSA average # of people/house for each prototype
• Lighting: Use RBSA average LPD & 1.5 hours/day
– Baseline Ventilation• 2 hours/day at 50 cfm
– Baseline InfiltrationConclusion - 20
Heating System Type
Heating High °F(day)
Heating Low °F(night)
Electric Zonal 64 64Electric FAFGas FAF 68.6 63.9Heat Pump 69.6 65.4
Remaining Issues• Wood/Other Heat– By ignoring the significant fraction of wood/other heated
homes in this analysis, future RTF analyses will likely overstate the electric space heat savings.• From a cost-effectiveness perspective, this may be ok if we consider
the value of wood/other fuels similar to the value of electricity.• From an electric savings perspective, it’s important to remember
some fraction of the stated electric savings will actually be wood/other savings, not actual electric savings.
• Unused Homes– By ignoring unused homes in this analysis, we have a similar
issue as with wood/other heat (except there won't be wood/other savings in these cases).
Discussion - 21
Some Options
1. Leave as is; note caveats regarding stated savings2. Determine a “grid savings” and a “TRC savings” for each
measure– Grid Savings
• Savings would account for wood/other and unused houses. – This will take more work & discussion.
• Used to report electric savings.– “TRC Savings”
• Savings don’t include the effects of wood/other heat. – Savings would be based on the calibration presented today.
• Used to report TRC – Value of electricity used as a proxy for value of wood/other heat
Discussion - 22
Decision
• Approve SEEM94 calibration for use in estimating space heating energy savings in single family homes.
Decision - 23