RTF Presentation Mohit Singh-Chhabra, Ben Larson March 15, 2016 Multifamily Weatherization Measures

Presentation Objectives and Outline Update the RTF on the status of multifamily (MF) SEEM calibration Present Research Strategy for calibrating SEEM and develop Proven MF weatherization measures Approve proposed MF Weatherization measure analysis – Heat Pump and DHP home measures as Small Saver – Electric Resistance heated homes as Planning Sunset Date extension for Multifamily New Construction 2

MF Calibration 3

Existing Calibration Background Constrained to MF buildings three stories or less Building types and prototypes: – Townhouse Exterior access; shared walls – Woody walk-up Exterior access; stacked flats; shared walls, floors, & ceilings – Double loaded corridor Interior access; stacked flats; shared walls, floors, & ceilings 4

MF Calibration – Current Status An existing MF calibration was approved in 2012 – Based on five small MF billing studies from 1994 to 2010 (pre-dates RBSA) – SEEM heating energy calibrated to billing energy using thermostat adjustment August, 2015: RTF directed CAT to test the existing thermostat based calibration with pre-/post- data to determine if the calibration is good enough December 2015: Pre-/Post- data to test the calibration not available; CAT presented an alternate plan to test existing calibration on all feasible (22) RBSA buildings study results and then recommend next steps 5

Existing Calibration Definition Thermostat set-point of 68 degrees, no setback. Internal gains calculated with the SEEM MF Calibration Internal Gains Calculator Infiltration assumed at 0.35 ACH natural unless otherwise known – rare to know for MF building stock 6

Existing Calibration (continued) 7 ReferencePrototypeLocation Heating System Sample Size (n units) Temp setpoints Actual Heat EUI (kWh/yr- ft 2 ) SEEM Heat EUI (kWh/yr- ft 2 ) % Diff # units # bldgs Heat Low (F) Heat High (F) MF MCS Multifamily Metering Study - AAHX Woody Walk- Up Seattle Electric Zonal % MF MCS Multifamily Metering Study Woody Walk- Up Seattle Electric Zonal % ARRA-FG. ARRA Verification - Forest Glen (Ecotope) Woody Walk- Up Redmond Electric Zonal % New MF-2009 Study (Ecotope) Double Loaded Corridor Seattle Electric Zonal % ARRA-AV. ARRA Verification (Ecotope) TownhomesSeattle Electric Zonal % Total Units & Buildings: Avg % Existing calibration summary:

Research needs: Knowledge gap Need data that provides direct insight into change in energy consumption, pre- and post-weatherization, in multifamily buildings – Need to know the realization rate, ∆VBDD/∆SEEM Existing calibration sought to get overall SEEM heating kWh (averaged across multiple buildings) to equal overall VBDD heating kWh – No pre/post data, no insight into ∆VBDD/∆SEEM Existing calibration tested against 22 relevant RBSA buildings – Results somewhat encouraging (next two slides) – Confidence intervals are wide and test sample isn’t pre/post 8 – Multifamily Weatherization

Calibration Test Results (kWh/sq.ft.) 9 – Multifamily Weatherization Slope ≈ 0.5 Not clear how this “across- buildings” slope should relate to within-building (pre/post) ∆V/∆S

Calibration Test Results (kWh) 10 – Multifamily Weatherization Not clear how this “across- buildings” slope should relate to within-building (pre/post) ∆V/∆S

Research Strategy 11

Research needs: Savings Potential Electric Resistance-Heated MF Buildings – Regional Wx savings potential ~ 250 aMW* – CAT proposal: Identify research needed to prove out Wx for MF buildings with ER heat; develop Planning estimates using existing calibration DHP-heated MF buildings – RBSA found ~ 1% of MF units had DHPs – Little immediate potential, but electric-resistance buildings could convert to DHPs – CAT proposal: Develop Wx for MF buildings with DHP as Small Saver for now using existing calibration Reassess DHP penetration at sunset; Move to planning, provisional, or proven as warranted Heat Pump-Heated MF Buildings – Regional Wx savings potential ~ 3 aMW* – CAT proposal: Develop Wx for MF buildings with HP-heated spaces as Small Saver using existing calibration Research Strategy focuses on existing buildings with electric resistance heat. No research required for Small Saver measures * Source: 7 th Plan and RBSA 12

Research Strategy Subcommittee Meeting: March 4 th Paul Sklar, ETO Kate Scott, ETO Scott Leonard, ETO Ben Mabee, BPA Erin Hope, BPA Jess Kincaid, BPA Phillip Kelsven, BPA Tom Eckhart, UCONS Jim Perich-Anderson, Puget Sound Energy Kiley Faherty, Snohomish PUD Mark Jerome, CLEAResult Garrett Herndon, RTF Staff Jennifer Light, RTF Manager 13 Michael Noreika, PSE Peggy Peterson, Seattle City Light Bob Davis, Ecotope Lauren Gage, BPA Gary Grayson, Idaho Power Greg Kelleher, EWEB Rachel Clark, Tacoma Richard Cole (?) Todd Blackman, Franklin PUD Josh Rushton, RTF CAT (Presenter) Mohit Singh-Chhabra, RTF CAT Adam Hadley, RTF CAT List of attendees:

Research Strategy: Objectives Savings estimates should be closely tied to observed changes in energy consumption, pre- and post-weatherization, in multifamily buildings – Estimation target is the pre/post ∆VBDD/∆SEEM – This parameter is a realization rate for SEEM savings For a sample of multifamily buildings, need to collect, pre- and post-weatherization: – Energy consumption data sufficient to fit VBDD models – Building/site characteristics sufficient to create SEEM models 14 – Multifamily Weatherization

Straw-man Approach: Sample Size To estimate typical ∆VBDD/∆SEEM with 10% precision (and 90% confidence), sample target is 33 pre/post buildings Estimate based on standard sample mean calculation assuming coefficient of variation (CV) equal to 0.35 Relatively low CV chosen for two reasons: – Measurement Error: Building-level VBDD estimates expected to be resistant to house-hold-specific noise – Expected Variability: Don’t expect ∆VBDD/∆SEEM values to deviate wildly about the mean (additional slide for details) CAT doesn’t see a more rigorous way to anticipate study precision 15 – Multifamily Weatherization

Straw-man Approach: Sample Details Sampled buildings should have significant pre/post changes in Uo Include wide range of pre-case shell efficiencies, and include buildings east and west of the Cascades – Not seeking separate calibration parameters that vary with Uo and/or geography 16 – Multifamily Weatherization

Straw-man Approach: Data Collection Billing data for whole building – At least 12 consecutive months, pre and post – Preferably 24 months pre Location (county or zip code) Building configuration and size Pre- and post-Wx building characteristics – Component U-factors and square footage (windows, walls, floors, attic) 17 – Multifamily Weatherization

Straw-man Approach: Analysis Billing analysis – Use billing analysis (VBDD) to estimate normalized annual heating energy for each building, pre and post – Pre/post change, each building: ∆VBDD = VBDD.pre – VBDD.post Engineering analysis – Run SEEM for each building using site-specific inputs for climate, component U-factors, and component square footage Do not anticipate site-specific data on internal gains or infiltration – Pre/post change, each building: ∆SEEM = SEEM.pre – SEEM.post Estimate average realization rate: – Ratio estimator is Sum(∆VBDD)/Sum(∆SEEM) – Result works as a realization rate for SEEM-based savings estimates for MF Wx measures 18 – Multifamily Weatherization

Residential Multifamily Weatherization Measure Development 19

MF Weatherization Current Measure Category: Proven Proposed Measure Category: Planning (ER) & Small Saver (HP) Current Measure Status: Under Review Proposed Measure Status: Active Measure Sector: Residential End Use: Whole Building Current Sunset Date: March,

Measure Overview Measure DevelopersEcotope, Mohit Singh-Chhabra CAT ReviewMohit Singh-Chhabra Tech Sub-Com ReviewNo R&E Sub-Com ReviewYes NotesThis is a planning measure for Electric Resistance heated buildings, Small Saver for HP and DHP heated. Measures were tested for interaction, it was determined that measure interaction is not significant (< 10%) 21

Multifamily Weatherization Measures 22 These measures have unique identifiers for: 3 Heating Zones 4 HVAC system types Electric Furnace Electric Zonal Heat Pump Ductless Heat Pump Ecotope confirmed measure list with BPA, BPA requested these measures be maintained and requested for Door Insulation measure

Measure Interactions Not Significant Calculated savings from a full measure package (FMP) with an uninsulated building as a starting point – Simulated all measures in the FMP as first-in and last-in – Compared the sum of all applicable first-in, last-in savings to the FMP – Sum of last-in and first-in savings within 10% of FMP savings; last-in savings closer to FMP savings – Guidelines, Roadmap Section 1.3.4: “A measure interaction is significant if the RTF determines that it could change a measure’s savings estimate by more than ± 10%” 23

Updated Analysis: Changes that have a Major Effect on Savings Update to SEEM infiltration module – Upgraded, (more) physically accurate infiltration model results in changes to heat transfer across the ceiling and across the floor Warmer air in the attic Crawl space closer to outside temperature – Results in (much) lower savings from attic insulation – Results in slightly higher savings from floor insulation measure in some cases 24

Updated Analysis: Changes that have a Minor Effect on Savings Update to Calibration: New Thermostat setpoint- 68 F; changed from: – Electric Resistance: 66 F – Heat Pump: 70 F (6 AM) 64 F (10 PM) Updated internal gains, slightly lower. 25

Electric Zonal Heating: Energy Savings (kWh/sf) 26 Updates coming – need to include infiltration effects

Electric Furn. Heating: Energy Savings (kWh/sf) 27

Heat Pump Heating: Energy Savings (kWh/sf) 28

DHP Heating: Energy Savings (kWh/sf) 29

Incremental Cost Calculation Methodology Standard Information Workbook is the primary source for all cost data Attic, floor, and wall insulation set to SIW values for MF buildings Low E Storm window cost same as that used in SF and MH Door insulation upgrade cost from SBW research conducted for BPA – Calculated using material and installation cost data from the National Repair and Remodeling Estimator

Incremental Cost Comparison (2012$) 31

Incremental Cost Comparison (2012$) 32

Regional Cost Benefit Analysis: Elec. Zonal 33

Regional Cost Benefit Analysis: Elec. Furn. 34

Regional Cost Benefit Analysis: Heat Pump 35

Regional Cost Benefit Analysis: DHP 36

Proposed Motion “I, _______, propose that the RTF update the Multifamily Weatherization measures as Active and: Adopt the measure analysis and Research Strategy for electric resistance heated homes as Planning with a Sunset Date of March, 2019 Adopt the measures for Heat Pump, and Ductless Heat Pump heated homes as Small Saver with a Sunset Date of March, 2019 Change in savings and cost effectiveness of low-e windows will be presented to the RTF” 37

MF New Construction ENERGY STAR Homes Measure savings estimate need to be updated as: State building codes have now been updated and to so have ENERGY STAR measure specifications – Idaho only state where state building codes remain unchanged SEEM has been significantly updated since this measure was last updated Measure sunsets at the end of this month; staff propose extending the sunset date to July 30 th,

Proposed Motion: MF New Construction ENERGY STAR Homes “I, ______, move that the RTF extend the Sunset Date for MF New Construction ENERGY STAR Homes to July, 2016” 39

Additional Slides 40

Door Replacement Measure Baseline is Current Practice – Average of all RBSA door (used as proxy for current practice) is R2.9 – Measure is an ENERGY STAR door, average R value is R-3.75 No infiltration reduction modeled; no data to determine how to model this effect – May not matter: tested this measure; nowhere near cost effective 41 ENERGY STAR LevelR Value Opaque>= 4.76 <= 1/2 – Lite>= 3.7 > 1/2 - Lite>=3.13

Sample size: A priori CV estimate Hypothetical example to think about what we should expect for CV of the parameter ∆VBDD/∆SEEM Example: Wx measure decreases SEEM-predicted heating energy by 10,000 kWh for buildings of a certain size and in a certain area. Measure is applied to several MF buildings (of similar sizes, in the same area) Question: In this example, how much variability should we expect to see in the different buildings’ ∆VBDD values? Subjective answer: Since ∆SEEM is the same for each building, we’d be surprised to see many buildings with ∆VBDD as much as 70% different from the mean Upshot: Interpreting “surprise” as reaction to events that should occur < 5% of the time, we take the 70% figure to represent two standard deviations (hence, CV = 0.35) 42 – Multifamily Weatherization

3a. Explain why infiltration savings went down Different Calculation Method in SEEM (see December 2011 Presentation for details) – Old Version of SEEM: Infiltration is an input Input = ACHn (CFM50 * 60 / 20 / House Volume) – New version of SEEM: Infiltration is modeled Input = CFM50 (blower door test result), Stack Height, Weather Comparison: – Modeled infiltration measure savings for each prototype in Portland 69/64, no adjustment). – Results, expressed as a ratio of SEEMnew Savings/SEEMold Savings: 1344 ft2: 43% 2200 ft2: 64% 2688 ft2: 49% Then, there are differences from SEEM Calibration and Measure Interaction adjustments… 43 Slide from August Meeting: 43