1 NORTHWEST ENERGY EFFICIENCY ALLIANCE
Creating a DHP UES Measure
Ecotope, Inc.July 16, 2013
2
Agenda
Introduction Overview
Study populationsSimulation Calibration SEEM thermostat settings
Savings Analysis Input Assumptions Savings Estimates
Discussion
3
Introduction
4
Overview / Review
Key findings presented to RTF at 21 May 2013 meeting
Technical Potential: Measure targets ER zonal houses only RBSA reports 388,847 ER zonal houses across
PNW Estimate 3,000 kWh/yr Technical Potential ≈ 133 MWa
5
Data Sources & Study Populations
6
Data Sources & Study Populations
3 Main Populations and Data Sources:RBSA Single Family Houses (n ≈ 1,400)
Only 170 houses with zonal electric resistance heat as primary heating source
DHP Pilot Study Billing Analysis (n ≈ 4,000)DHP Metered Group Houses (n = 95)
A subset of the full pilot billing analysis
7
Populations Compared
Compare Populations All populations screened to exclude supplemental fuels 90% confidence interval
RBSA regionally representative DHP Pilot skewed to Zone 1 DHP Metered skewed to Zones 2 and 3
Study Population
ER Heating Energy Use
kWh/yrEB
kWh/yr
Floor Area
ft²UA
Btu/hr-F
Area Normalized Heating
EnergykWh/ft² n
RBSA 8977 783 1568 583 5.7 170
DHP Pilot Study 7907 134 1533 ??? 5.2 2294
DHP Metered Group 9422 669 1610 514 5.9 93
8
Populations Compared
Heating energy use divided by conditioned floor area (heating EUI) across zones and populations
Conclusion: Use RBSA characteristics Statistically relevant across entire region Baseline energy use in line with DHP studies More detailed characteristics
Study Population
Heating Zone 1Energy Use
kWh/ft²
Heating Zone 2Energy Use
kWh/ft²
Heating Zone 3Energy Use
kWh/ft²
RBSA 5.3 (n=136) 7.1 (n=25) 6.3 (n=9)
DHP Pilot Study 5.2 (n=2096) 7.3 (n=122) 6.4 (n=76)
DHP Metered Group 5.9 (n=51) 6.7 (n=32) 6.0 (n=10)
9
Calibrating Thermostat Settings in SEEM
10
Thermostat Settings
Two Options(1) Use calibrated (from RBSA dataset) ER settings for both baseline and
DHP simulations:(Note: these are for houses with good insulation levels)
(2) Use calibrated (from RBSA dataset) ER settings for baseline and different DHP settings:
Calculate thermostat adjustment (“takeback”) from metering data
Heating Zone
ER Daytime Set Point
DHP Daytime Set Point
1 66.9F 66.9F2 64.8F 64.8F3 61.5F 61.5F
9hr night time setback: 4.8F
Heating Zone
ER Daytime Set Point
DHP Daytime Set Point
1 66.9F ???2 64.8F ???3 61.5F ???9hr night time setback: 4.8F ER, ??? DHP
11
Thermostat Calibration
Targets: Energy use calibration targets from the metered group
Billing analysis provides heating energy estimate for pre-DHP installation period
Meters record direct heating energy use for post-DHP installation periodSimulation Results:
SEEM matches the targets if certain thermostat settings used
Time Period Source
Heating Energy Use (kWh/yr)
Mean and SD NPre-DHP Installation
Target Billing Data 9347 3892 91
SEEM Output 9357 4111 91
Post-DHP Installation
Target Metered Data 6484 3894 91
SEEM Output 6468 3234 91
12
Calibration Method
Approach Create individual simulations for each house Set points vary by heating zone, HVAC type, and house insulation levels
In a similar way to RBSA calibration at 21 May 2013 meeting. Calibrate settings to metered data by varying the thermostat
95 SEEM Simulations – one for each
house
T-stat settings
Iterate until simulation output matches targets
13
Calibration Outcomes & Observations
Outcome The metered 95 dataset suggest using the following T-stat settings:
Observations ER-only houses needed higher set points than those from RBSA
calibrated dataset to match targets DHP houses needed a different (higher) set point than the ER
baseline houses to match the metered energy use target
Heating System Electric Resistance Zonal Only DHPCeiling / Wall Insulation Good Ceiling or Wall Poor Ceiling or Wall Good Ceiling or Wall Poor Ceiling or WallFloor Insulation Good Floor Poor Floor Good Floor Poor Floor Good Floor Poor Floor Good Floor Poor FloorHZ 1 69.1 67.0 65.3 62.9 69.9 67.8 66.1 64.1HZ 2 67.0 64.6 61.8 58.5 69.2 66.4 64.3 61.7HZ 3 63.7 60.9 59.5 55.5 66.6 63.3 60.8 58.8
14
Translation to General Housing Population
Simulate ER zonal baseline with set points from RBSA calibration These are not the set points that came out of the calibration of the DHP95
metered houses. That population and the RBSA “general” population differ enough to suggest different Tstat calibrations. We opt to use the RBSA source because it better represents the broader population.
RBSA SEEM calibration for ER zonal heat with good wall/ceiling/floor insulation:
Simulate DHP houses using a changed (increased) set point equal to the delta found from the DHP95 dataset What is the set point delta? How much is the takeback?
Heating Zone
ER Daytime Set Point
1 66.9F2 64.8F3 61.5F
9hr night time setback: 4.8F
15
Calculating Takeback
Takeback for Good Ceiling/Wall/Floor Case Subtract Electric Resistance Zonal set point from DHP set point
Heating Zone TakebackHZ 1 0.8F 0.8F 0.8F 1.2FHZ 2 2.2F 1.8F 2.5F 3.2FHZ 3 2.9F 2.4F 1.3F 3.3F
Heating System Electric Resistance Zonal OnlyCeiling / Wall Insulation Good Ceiling or Wall Poor Ceiling or WallFloor Insulation Good Floor Poor Floor Good Floor Poor FloorHZ 1 69.1 67.0 65.3 62.9HZ 2 67.0 64.6 61.8 58.5HZ 3 63.7 60.9 59.5 55.5
Heating System DHPCeiling / Wall Insulation Good Ceiling or Wall Poor Ceiling or WallFloor Insulation Good Floor Poor Floor Good Floor Poor FloorHZ 1 69.9 67.8 66.1 64.1HZ 2 69.2 66.4 64.3 61.7HZ 3 66.6 63.3 60.8 58.8
16
Thermostat Settings with Takeback
Start with RBSA-derived ER zonal set points for baseline. Then add takeback to produce DHP set points.
9hr night time setback: ER 4.8F, DHP 4.3F
ER Daytime Set Point
66.9F64.8F61.5F
DHP Daytime Set Point
67.7F67.0F64.4F
Takeback
0.8F
2.2F
2.9F
Heating Zone
123
17
Thermostat Settings: Conclusion
Two Options(1) Settings for both baseline and DHP
(2) Settings for baseline and takeback for DHP
Heating Zone
ER Daytime Set Point
DHP Daytime Set Point
1 66.9F 66.9F2 64.8F 64.8F3 61.5F 61.5F
9hr night time setback: 4.8F
Heating Zone
ER Daytime Set Point
DHP Daytime Set Point
1 66.9F 67.7F2 64.8F 67.0F3 61.5F 64.4F
9hr night time setback: ER 4.8F, DHP 4.3F
18
Simulation Inputs: Prototype Sizes & Insulation Levels
19
Prototypical House Matched to RBSA
RBSA House Prototype Summary Process Use RTF prototypes to make RBSA bins
Subset RBSA Database• Single-family
homes with electric primary heat only
Categorize• Categorize
floor area: large/small
• Merge in foundation types
• Merge in climates
Summary by Sample• Use survey
weights to calculate proportions of each foundation/size combo by climate
20
Prototypical House – Distribution
RBSA Prototype Summary
Floor area - different study groups: RBSA Zonal Electric Resistance: 1568 ft2 DHP Pilot Study: 1533 ft2
DHP Metered Group: 1610 ft2
Prototype HZ1CZ- HZ2CZ- HZ3CZ- ALL Occupants1344c 77.2% 52.5% 6.1% 68.4% 2.451344s 7.7% 21.6% 0.0% 9.6% 2.712200c 6.2% 2.2% 19.3% 6.4% 2.942200s 0.5% 2.3% 19.3% 2.0% 2.632688b 8.4% 21.5% 55.4% 13.6% 2.91
Overall ft2: 1514 1671 2419 1598 2.67
(categorical data)
(continuous data)
21
Prototypical House – Insulation Levels
RBSA U-Value Summary Process Subset for single-family homes with electric
zonal primary heat
RBSA gives current conditions
RBSA Database• R-value and
characteristics from surveyor
• Database has assigned U-value
Summary by Site• Find area-
weighted average U-value by site for each component of interest
Summary by Sample• Use survey
weights to find average component U-value for region
22
What the book says
Guidelines for the Estimation of RTF Savings, 16 April 2013
2.3.3.4. Interactions between Measures
In many cases, the savings of one measure depends on whether another measure is present…. The UES for each measure should be computed under the assumption that all other measures it significantly interacts with are already implemented. Interaction is significant if the RTF determines that it is likely to account for more than 10% of the measure savings.
The other measures assumed to be present should be consistent with expected typical conditions at the end of the measure’s effective useful life. This “last-in” requirement may create a downward bias in the short-term savings estimate for a measure. An alternative estimate of UES may be prepared using different assumptions about what other measures have already been implemented. If an alternative is developed, both UES estimates must be presented to the RTF along with the justification for which should be used. The measure’s sunset date may be based on the rate of implementation for the other interactive measures.
23
Prototypical House – Insulation Levels
Insulation Levels Now vs Later Current conditions found from RBSA Cost Effective Limit (CEL) for “last-in”
Assume all homes fully weatherized by end of measure (85% achievable)
From RBSA, some homes already at or above goal Homes near goal not cost effective
Forecast is somewhere between? 25% in 15 years?
24
Prototypical House – Insulation Levels
Calculate new CEL from RBSA Database Each component assigned insulation levels Apply the following logic to data
Incorporate 85% achievable rate Re-summarize
Component If ≤ UpgradeAttic R-19 R-38
Floor R-16 R-30
Wall Uninsulated R-11
Infiltration 9 ACH50 7 ACH50
25
Prototypical House – Insulation Levels
R0-R5 R6-R10 R11-R15 R16-R20 R21-R25 R26-R30 R31-R35 R36-R40 >R400
50,000
100,000
150,000
200,000
Attic Insulation Distribution: RBSAPo
pula
tion
R0-R5 R6-R10 R11-R15 R16-R20 R21-R25 R26-R30 R31-R35 R36-R40 >R400
50,000
100,000
150,000
200,000
Attic Insulation Distribution: Forecast (25% <R20 Get Insulated)
Popu
latio
n
R0-R5 R6-R10 R11-R15 R16-R20 R21-R25 R26-R30 R31-R35 R36-R40 >R400
50,000
100,000
150,000
200,000
Attic Insulation Distribution: RBSA CEL (85% <R20 get insulated)
Popu
latio
n
26
Prototypical House Insulation Summary
Insulation Summary
Component RBSA Forecast RBSA CEL RTF CELFloor R-Value 9.6 15.3 24.6 26.8
Wall R-Value 7.0 8.9 11.3 11.4
Ceiling R-Value 12.4 19.2 28.8 35.0
Door R-Value 3.0 3.0 3.0 5.3
Window U-Value 0.631 0.564 0.490 0.293
LPD W/sqft 1.30 1.00 0.71 0.60
Current 15 Years From Now Reference
27
Prototypical House – Forecast
Forecast Case – Why 25% Assume pre-1980 house has little or no
insulation In 30 years, 65% of these homes still have
little or no insulation (from RBSA attic data) Projecting forward 15 years, 25% additional
weatherization could be reasonable
28
Prototypical House – UA
1 2 3 ALL0
100
200
300
400
500
600
700
800
Average UA by Climate
RBSA CELForecastRBSA
Climate Zone
UA
For reference, the DHP Metered Group UA is 514 Btu/hr-°F
29
Energy Savings
30
Energy Savings – No Supplement Fuels
1 2 3 ALL0
1000
2000
3000
4000
5000
6000
Energy Savings for Houses with no Supplemental Fuels and with Takeback
RBSA CELForecastRBSA
Climate Zone
Savi
ngs
(kW
h/yr
)
31
Energy Savings – No Screen
1 2 3 ALL
-1000
0
1000
2000
3000
4000
5000
Energy Savings for mix of Houses with and without Supplemental Fuels and with Takeback
RBSA CELForecastRBSA
Climate Zone
Savi
ngs
(kW
h/yr
)
32
Energy Savings – With Supplemental Fuels
1 2 3 ALL
-2000
-1000
0
1000
2000
3000
4000
Energy Savings for Houses with Supplemental Fuels and with Takeback
RBSA CELForecastRBSA
Climate Zone
Savi
ngs
(kW
h/yr
)
33
Savings Check: No Supp. Fuel CaseDifferences between modeled savings and metered savings
Metered Group Savings: Source: Ductless Heat Pump Impact & Process Evaluation: Field Metering Report, May 1, 2012, NEEA Report #E12-237
Current modeling shows regional ave ~4000 kWh/yr for cases w/o supp. fuelsReconciling Differences (adjustments to current modeling output):
Geographic Cluster Mean Savings kWh/yr NWillamette 3316 26
Puget Sound 3043 25Inland Empire 1882 16
Boise/Twin 3628 16Eastern Idaho 3307 10Average/Total 3049 93
Rationale Adjustment (kWh/yr)Geographic distribution 50
LPD from 1.75 W/ft2 in metered group to 1.0 W/ft2 in modeled population. (changes overall heating load) > 300
Proposed measure spec will have higher HSPF requirement than those observed in metered group ~ 200
Inland Empire metered sites had even further under-performing DHPs ~ 250
Total Adjustments 800
34
Discussion
35
Discussion Questions
Is the SEEM DHP calibration appropriate? Should we use the electric resistance settings
from the RBSA/SEEM calibration for the baseline?
Is the method to determine the calibrated setting for the efficient-case appropriate?
What is an appropriate insulation level to expect over the 15 year lifetime of the DHP measure? First year savings are the “RBSA” case but what
are the 5, 10, and 15 year savings?
36
Extras
37
Thermostats: Final Note
With the simulation, it is possible to run the pre-DHP baseline with the post-DHP thermostat settings and vice versa. Such an approach allows us to compare the energy use without takeback and match the energy savings observed in the field by directly measuring heat output of the DHP.
Time Period SourceHeating Energy
Use (kWh/yr) NMean SD
Pre-DHP Installation
Target Billing Data 9347 3892 91SEEM ER Set points 9357 4111 91SEEM DHP Set points 10476 4409 91
Post-DHP Installation
Target Metered Data 6484 3894 91SEEM ER Set points 5788 3018 91SEEM DHP Set points 6468 3234 91
38
-2000
-1000
0
1000
2000
3000
4000
5000
6000
7000
1 2 3 ALL
Sav
ings
(kW
h/yr
)
Climate Zone
Screen, No Wood
RBSA CEL + Takeback
RBSA CEL No Takeback
Forecast + Takeback
Forecast No Takeback
RBSA + Takeback
RBSA No Takeback
-2000
-1000
0
1000
2000
3000
4000
5000
6000
7000
1 2 3 ALL
Sav
ings
(kW
h/yr
)
Climate Zone
No Screen
RBSA CEL + Takeback
RBSA CEL No Takeback
Forecast + Takeback
Forecast No Takeback
RBSA + Takeback
RBSA No Takeback
-2000
-1000
0
1000
2000
3000
4000
5000
6000
7000
1 2 3 ALL
Sav
ings
(kW
h/yr
)
Climate Zone
Screen, Yes Wood
RBSA CEL + Takeback
RBSA CEL No Takeback
Forecast + Takeback
Forecast No Takeback
RBSA + Takeback
RBSA No Takeback
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