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