SEEM Calibration: RevisitedRevising the regression to use continuous heat

loss variable

Regional Technical ForumDecember 17, 2013

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Background

975

429

SEEM Calibration

SF RBSA Pie: 1404 Homes

• Adjustment factors converted to calibrated thermostat settings

Approved by the RTF on May 21, 2013.

SEEM Calibration “Phase I”• Compared SEEM (68°F, day and night) heating energy estimates to

billing data estimates. • Restricted to 429 RBSA homes with well-known characteristics, no

non-utility fuels, and clear heating signatures in billing data.• Regression used to determine adjustment factors that align SEEM

(68°F) with billing data estimates of total heating energy.

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BackgroundSEEM Calibration “Phase II”• Independent of Phase I; adjustments apply on top of Phase I

adjustments.• Based on billing (VBDD) heating kWh estimates--does not use SEEM

estimates. • Identifies variables that drive patterns in electric heating energy among

“program-like” RBSA homes. Variables related to: - Non-utility heat sources, - Gas heat sources, and - Phase I filters.

552

Gas Heated, 249

Electric Heated, 180

In Utility Programs, but not in SEEM

calibration, 423

SEEM Calibration

SF RBSA Pie: 1404 Homes

Approved by the RTF on September 17, 2013.

Today’s work applies only to Phase I. It does not affect Phase II.

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Phase I Review (1)• Intended to limit complication in future UES workbooks

by choosing variables that correspond with RTF measures.

• Wanted to limit to variables well-known through RBSA (e.g., no infiltration).

• Regression variables (and adjustment factors) coded as indicator functions. Adjustments for:– Heating equipment,– “Poor” insulation in walls or ceiling,– Uninsulated crawlspace,– Climate Zone.

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Phase I Review (2)• Regression yields adjustment factors, which are

converted to calibrated T-stat values.

• Factors converted to calibrated T-stat values using SEEM T-stat sensitivity curves…

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.68)

T-stat conversion

Calibrated T-stat values 64⁰ (Day)

Adjustment factors

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Why are we revisiting this?Applications more diverse than appreciated in May. Basic proposal is to trade in some simplicity for realism.

• Regression Variable (Main proposed change). Replace insulation step functions with continuous heat loss function. New function treats heat loss from different sources equally:– Magnitude of heat loss matters but path does not; – Includes loss via infiltration (imputed for homes w/o blower door test); – Small changes yield small calibration adjustments (no threshold effects).

• T-stat Role (Secondary proposal). Apply adjustment factors directly, rather than converting to thermostat adjustments. – Concern is that thermostat “calibration knob” might bias results;– Adjustment factors would be relative to SEEM (69°F day / 64°F night) rather

than SEEM (68°F day / 68°F night).

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Changing Role of T-Stat (1)• Current calibration begins with SEEM Input = 68°F day/night

– This arbitrary value didn’t affect the results much since adjustment factors were converted to t-stat settings.

• Proposal would begin with SEEM Input = 69°F day, 64°F night– Values based on survey results from

RBSA (not arbitrary).– Not much difference by heating

system type, so the same roundednumber used for all.

– Values would become standard SEEM input (adjustment factors would be applied to output).

T-stat Daytime T-stat Night setback

69 64 5

tStatHi tStatLow Avg SetbackElectric FAF 69 63 6Electric Zonal 68 63 5Heat Pump 69 65 4Gas FAF 68 64 5

Primary Heating System

RBSA Data (settings reported by homeowner)

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Changing Role of T-Stat (2)What if we calculate adjustments relative to SEEM (68/68) and SEEM (69/64) and then convert adjustments into t-stat values?

Little difference in the end results.

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Tstat based on 68/68 data

"y=x"

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Regression Revision (1)

Main work is in developing heat loss variable.

• Infiltration loss based on CFM-Natural;– CFM-Nat is a SEEM input, derived from blower-door test data; – Blower door tests for about 1/3 of RBSA houses; – Regression-based “averages” for homes w/o blower door tests;– Calculations and regression based on RTF guidance.

• Convert infiltration loss to same units as conductive heat loss; add heat loss rates together; normalize by surface area.

• Result is called “Uo-Both”.

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Regression Revision (2)Developing the heat loss variable...

Ran preliminary regressions to see if any additional transform is needed. • Effect very pronounced in the

low range of U-values, but going from fairly high heat loss to very high heat loss has little effect.

• Final proposed heat loss function equals Uo-Both up to a point, but stays constant beyond that point.

• Cut-off value is 0.20 in Z1, 0.175 in Z2, 0.15 in Z3.

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Regression Revision (3)

Proposed Regression

Variable Coefficient P-valueIntercept -0.623 0.000Climate Zone 2 0.149 0.008Climate Zone 3 0.306 0.000Electric Resistance 0.246 0.000Uo Both (cut) 4.448 0.000

Current Regression Variable Coefficient P-value

Intercept -0.055 0.047uninsulated crawl 0.163 0.001poor wall or ceiling insulation 0.291 0.000Climate Zone 2 0.065 0.245Climate Zone 3 0.184 0.019Electric Resistance 0.282 0.000

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Regression Revision (4)

Example: Home in Zone 1 with Electric-Resistance heat and moderately insulated walls and floors.

Ceiling Insulation

Uninsulated Wall/Ceiling

Current RegressionAdjustment

Uo - Both

Proposed Heat Loss Variable

Proposed RegressionAdjustment

R5 1 62% 0.156 0.156 73%

R30 0 84% 0.139 0.139 79%

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Comparing Regression Results Z1 Elec. ResistanceCurrent and Proposed Adjustments (Example)

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Uo Both: Infiltration + Conduction

R30 – Current

R5 - Current

R5 (Proposed)

R30 (Proposed)

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Comparing Regression Results Z1 Elec. Resistance Current (unins. wall-ceiling/ unins. crawl) and Proposed

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Uo Both: Infiltration + Conduction

Current 0/0

Current 0/1

Current 1/0

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Proposed

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Comparing Regression Results Elec. ResistanceCurrent (R0) and Proposed (R3) All Heating Zones

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Uo Both: Infiltration + Conduction

Z1 - Elec.Res. (R0) Z2 - Elec.Res. (R0) Z3 - Elec.Res. (R0)Z1 - Elec.Res. (R3) Z2 - Elec.Res. (R3) Z3 - Elec.Res. (R3)

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Regression Revision (5)Effect on UES Calculations• Insulation

– Current: Different pre/post adjustments for only the cases where Uninsulated Insulated– Proposed: Different pre/post adjustments for nearly all the cases, even new construction

• Windows, Air Sealing– Current: No change in pre/post adjustments.– Proposed: Different pre/post adjustments for nearly all the cases, even new construction

• Duct Sealing, Heat Pump Upgrades, and Heat Pump CC&S– Current: No change in pre/post adjustments.– Proposed: No change in pre/post adjustments.

• (Central) Heat Pump Conversions– Current: Different pre/post adjustments.– Proposed: Different pre/post adjustments.

• DHPs (not a part of this analysis)

• Measure Interactivity– Old Method: Adjustment factors vary only when components are uninsulated.– Proposed Method: Adjustment factors are different for each “characteristic scenario”.

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Bottom Line…• Regression / Heat Loss Variable Proposal. Staff sees benefits in the

new heat loss function:– Heat loss due to infiltration treated the same as conductive loss;– All forms of conductive loss treated the same; – Small changes yield small calibration adjustments (no threshold effects).Drawbacks are added complication and overhead related to making a change.

• T-stat Proposal. Staff is neutral on this one. What do you believe is really driving differences between SEEM and billing data? – If it’s really T-stat settings, then it’s best to implement adjustments via

thermostat calibration;– If it’s something else, then adjustment factors are probably better—

thermostat calibration could bias some results.

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Decisions• “I ______ move that the RTF, in its single family calibration

method: (choose one)a) Switch to using a function based on continuous Uo, as

presented. b) Continue using the existing step-functions.”

• “I ______ move that the RTF, in its single family calibration method: (choose one)a) Switch to using adjustment factors directly, along with pre-

assigned thermostat setting inputs of 69F day and 64F night.b) Continue using ‘calibrated’ thermostat settings.”

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Additional Slides…

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Comparing Regression Results Elec. ResistanceCurrent (R0) and Proposed (R3) All Heating Zones

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Uo Both: Infiltration and Conduction

Z1 - Elec.Res. (R0) Z2 - Elec.Res. (R0) Z3 - Elec.Res. (R0)Z1 - Elec.Res. (R3) Z2 - Elec.Res. (R3) Z3 - Elec.Res. (R3)

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Comparing Models in T-stat terms Elec. ResistanceCurrent (R0) and Proposed (R3) All Heating Zones

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Z1 - Elec.Res. (R0) Z2 - Elec.Res. (R0) Z3 - Elec.Res. (R0)Z1 - Elec.Res. (R3) Z2 - Elec.Res. (R3) Z3 - Elec.Res. (R3)

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Comparing Regression Results Gas/Heat PumpCurrent (R0) and Proposed (R3) All Heating Zones

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Uo Both: Infiltration and Conduction

Z1 - Gas/HP (R0) Z2 - Gas/HP (R0) Z3 - Gas/HP (R0)Z1 - Gas/HP (R3) Z2 - Gas/HP (R3) Z3 - Gas/HP (R3)

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Z1 - Gas/HP (R0) Z2 - Gas/HP (R0) Z3 - Gas/HP (R0)Z1 - Gas/HP (R3) Z2 - Gas/HP (R3) Z3 - Gas/HP (R3)

Comparing Models in T-stat terms Gas/Heat Pump Current (R0) and Proposed (R3) All Heating Zones