1 Database for Energy Efficiency Resource Update Project Information and Final Results A DEER Presentation at CALMAC Meeting Pacific Energy Center, San Francisco September 21, 2005

2 DEER Update  Introduction and History  DEER  Measure Cost Study  Objectives and EE Regulatory/Policy Context  Project Management Structure  Program Advisory Committee  Technical Committee  Decision-making Processes and Orientation  Challenges and Accomplishments

3 DEER Update Project Implementation Structure and Consultant Team Roles Presenters: Gary Cullen – Itron Floyd Keneipp – Summit Blue Measure Savings Team Itron, J. J. Hirsch Associates, Quantum Inc, Synergy Measure Cost Team Summit Blue Consulting, Heschong-Mahone Group

4 Project Advisory Team  Shahana Samiullah, SCE (Project Manager)  Ingrid Bran, PG&E (MCS Project Manager)  Tim Drew, Energy Division, CPUC  Adriana Merlino, Energy Division, CPUC  Christine Tam, ORA, CPUC  Sylvia Bender, CEC  Mike Messenger, CEC  Andrew Sickels, SDG&E (Project Manager phase)  Jennifer Barnes, PG&E  Leonel Campoy, SCE  Craig Tyler, Tyler Associates (PG&E representative phase)  Jay Luboff (former ED representative phase)  Eli Kollman (former ED representative phase)  Others

5 Role of Project Advisory Team  Provide feedback and direction to the initial work plan  Provide unified and consistent advice and direction as issues appeared  Review methodological methods and assumptions  Review and provide comments on study results

6 Measure Savings Project Consultant Team Roles ITRON Gary Cullen (Project Manager), Bob Ramirez, Ulrike Mengelberg  Coordinate the activities of the consultant and advisory teams  Coordinate with the measure cost team  Develop the non-weather sensitive residential and commercial sector measure savings  Develop the agricultural sector measure savings  Coordinate, consolidate, and format the measure savings, cost, and EUL data for uploading  In consultation with Synergy, help design the web interface

7 Measure Savings Project Consultant Team Roles JJ Hirsch & Assoc. Jeff Hirsch, Scott Criswell, Paul Reeves, Kevin Madison  Develop the analysis software based on the DOE-2 model for weather sensitive measures  Suggest methodological directions and solutions  Develop the building prototype and conservation measure characteristics  Develop the weather sensitive residential and commercial sector measure savings  Coordinate data transfer format with Itron and deliver data to Itron for uploading

8 Measure Savings Project Consultant Team Roles Quantum Consulting Mike Rufo  Interview potential DEER users  Create DEER Periodic Update Plan  Identify linkages to EM&V studies  Identify new measures to potentially include in future DEER updates

9 Measure Savings Project Consultant Team Roles Synergy Christine Chin-Ryan  Develop web interface  Populate web interface with data  Debug web interface

10 Measure Savings Project Consultant Team Roles  Measure costs developed under separate contract by Summit Blue  Measure cost team and roles will be discussed later

11 What is DEER?  A collection of data for Residential and Non-Residential energy efficiency measures.  It provides a common set of: Ex ante Savings values: kW, kWh, kBtu; Measure Costs; and Effective Measure Life (a.k.a EUL)

12 Previous DEER Database  Savings estimates and cost estimates were never integrated  Database on hard copy and soft copy  Commercial measures savings had not been updated since 1994  Residential measures savings more recently in 2001  No information on EULs

13 DEER Update  First Phase of DEER Update began in 2003 and included: Updating savings for non-weather sensitive measures Updating weather-sensitive models and the software –Measure Analysis Software Creating a searchable, on-line database

14 DEER Update  Second Phase of DEER began in 2004 and included: Revised non weather sensitive lighting measures savings estimates Completed the Measure Analysis Software for weather sensitive analysis Developed a limited number of “High Priority” weather sensitive measure savings estimates Integrated measure cost into the database  Partial release Milestone completed on March 2005 Frozen to support June 1st EE filing

15 DEER Update  Final DEER milestone Completed on-line DEER version 2.0 on August 31, 2005 Supercedes March 2005 DEER version 1.0 Revised non-weather sensitive data Added new and updated weather sensitive measures Added Agricultural measures Integrated new effective useful life estimates Completed integration of cost data Updated the website with the new information

16 DEER Update Final Report Milestones  Draft Final Report - Sept 30 th for PAC  Final Report - October 31st

17 DEER Update  TOU Profiler– Currently TBD Too many other issues; other items with higher priority Definition of kW Calibration Unification of kW definition across all measures and end uses Agreed initially: Create a Time of use Profiler Will utilize the DEER eQuest model The model will be available for download Preliminary estimate of amount of data More discussions needed

18 Measure Cost Study (MCS) Project Team  Marshall Keneipp, Summit Blue Consulting (Project Manager)  Floyd Keneipp, Summit Blue Consulting  Joshua Radoff, Summit Blue Consulting  Cathy Chappell, Heschong Mahone Group, Inc.  Cynthia Austin, Heschong Mahone Group, Inc.

19 MCS Project Overview  Undertaken to update measure cost estimates within DEER  Previous update conducted in 2001  Parallel completion schedule to DEER Update High priority measures complete in March 2005 Full update completed in August 2005

20  814 separate costs were collected on 287 measure IDs Many measure IDs have one cost Some measure IDs have costs for multiple bins (i.e. capacities, purchase volumes, etc.). For example measure D03-410, residential condensing 90 AFUE furnace, has 10 costs - one cost for each of 10 Btu capacities  625 separate base costs were collected Some measures were full cost only and did not require base cost estimates  574 measure labor cost were collected Some measures were incremental equipment costs only and did not require a labor cost estimate  A total of over 12,100 individual cost observations were collected Measure Cost Study (MCS) Project Scope of effort

21 Questions/Comments?

22 Development of DEER Products Non-Weather Sensitive Energy Savings Presenter: Gary Cullen – Itron

23 Non-Weather Sensitive Measures Residential Measures  CFL Lighting  Refrigerators  Clothes Washers & Dryers  Dishwashers  Water Heating  Swimming Pool Pumps

24 Non-Weather Sensitive Measures Residential Measures  CFL Lighting Measure Impact = (delta watts/unit * hours/day * days/year * In Service Rate) / 1000 watts/kWh Demand Impact = delta watts/unit * In Service Rate * Peak Hour Load Share The “In Service Factor” is an estimate of the percentage of lamps that are actually used. It is a rough estimate based on utility experience. “Hours of Operation/Day” and “Peak Hour Load Share” from KEMA CFL Metering Study

25 Non-Weather Sensitive Measures Residential Measures  CFL Lighting – Example (14W CFL replace 60W Inc) Measure Impact = (46W * 2.34 hours/day * 365 days/year * 0.9) / 1000 watts/kWh = 35.4 kWh Demand Impact = 46W * 0.9 * = 3.35 W

26 Non-Weather Sensitive Measures Residential Measures  Refrigerators Used the Energy Star calculator available on-line at: Key Input values for the calculator: Refrigerator Type (top, side, or bottom mount freezer) Ice through the door (yes or no) Refrigerator fresh volume (cubic feet) Refrigerator freezer volume (cubic feet)

27 Non-Weather Sensitive Measures Residential Measures  Clothes Washers Utilized the three recommended Consortium for Energy Efficiency (CEE) Tiers for Modified Energy Factor: Used the Energy Star calculator (that utilizes an EF rather than MEF) on-line at: Estimated the equivalent EF value for CEE MEF values from Energy Star list of approved washers Other key Energy Star variables include: Number of wash cycles/year (E Star value is 392 cycles) Washer capacity (three sizes – 1.5, 2.65, and 3.5 cubic feet) Further disaggregated impacts by water heat and clothes dryer fuel types Fuel impact disagreegations based on ‘Efficiency Vermont” estimates Demand impact based on a energy/peak factor of This is carryover from previous 2001 DEER

28 Non-Weather Sensitive Measures Residential Measures  Clothes Washer – Example (Tier cu.ft) Measure Impact = (cycles/year * capacity / base EF) – (cycles/year * capacity / measure EF) = (392 * 2.65 / 1.58) – (392 * 2.65 / 4.94) = 447 kWh Demand Impact = Measure Impact * energy/peak factor = 447 kWh * = W

29 Non-Weather Sensitive Measures Residential Measures  Clothes Dryer 1993 National Appliance Energy Conservation Act (NAECA) minimum efficiency used for base technology: EF = 3.01 for electric dryers EF = 2.67 for gas dryers Used DOE test procedure guidelines for: Drying cycles per year = 416 UEC of 2.33 kWh/cycle for electric (969 kWh/year) UEC of 8.95 kBtu/cycle for gas (37.2 therms/year) Assumed 416 cycles represented Single Family Assumed 250 cycles for Multi-Family (CEC estimate of 60% less use by MF) Energy savings 5% of energy use. This is a carryover from previous 2001 DEER Demand impact based on a energy/peak factor of This is carryover from previous 2001 DEER

30 Non-Weather Sensitive Measures Residential Measures  Clothes Dryer – Example (SF electric) Measure Impact = Electric base use * Savings Percentage = 969 kWh * 0.05 = 48 kWh Demand Impact = Measure Impact * energy/peak factor = 48 kWh * = 17.8 W

31 Non-Weather Sensitive Measures Residential Measures  Dishwasher Used the Energy Star calculator available on-line at: Key Input values for the calculator: Base Energy Factor (EF) = 0.46 Measure Energy Factor = 0.58 Annual wash cycle (DOE test procedure) = 215 (assume SF) MF wash cycles (assumed to be ~75% of SF) = 160 Demand impact based on a energy/peak factor of This is carryover from previous 2001 DEER

32 Non-Weather Sensitive Measures Residential Measures  Water Heating Measures: High efficiency water heater (electric EF=0.93, gas EF=0.63) Heat pump water heater (EF=2.9) Point of use water heater low flow showerhead (from 2.5 to 2.0 gallons per minute) Pipe wrap Faucet aerators Savings expressed as % of base use Base use varied by utility service area (same method as 2001) Demand impact based on a energy/peak factor of This is carryover from previous 2001 DEER

33 Non-Weather Sensitive Measures Residential Measures  Water Heating Measure Saving %: High efficiency water heater – electric - 5.4% High efficiency water heater – gas - 5.0% Heat pump water heater – 69.7% Point of use water heater – 15.0% low flow showerhead – 4.0% Pipe wrap – 4.0% Faucet aerators – 3.0%

34 Non-Weather Sensitive Measures Residential Measures  Pool Pumps Single speed and two speed included Relied on PG&E and SCE engineers for calculating impacts: General assumptions: Average pool size of 25,000 gallons Average water turnover rate of 6-8 hours Average pump motor demand of 1.75 kVA Typical filtration time of 4 to 6 hours For single speed motors, motor downsizing and runtime reductions assumed

35 Non-Weather Sensitive Measures Non-Residential Measures  Interior Lighting  Exterior Lighting  Cooking  Copy Machine  Water Heating  Vending Machine Controls  High Efficiency Motors  Agriculture

36 Non-Weather Sensitive Measures Non-Residential Measures  Interior Lighting Measures: CFL screw-in lamps CFL hardwire fixtures High intensity discharge (HID) lamps Premium T8 lamps Dimming Ballasts De-lamping fluorescent 4 ft and 8 ft fixtures

37 Non-Weather Sensitive Measures Non-Residential Measures  Interior Lighting – Basic Methodology Measure Impact = (delta watts/unit * hours/day * days/year * In Service Rate) / 1000 watts/kWh Demand Impact = delta watts/unit * In Service Rate * Peak Hour Load Share

38 Non-Weather Sensitive Measures Non-Residential Measures  Exterior Lighting & Exit Signs High intensity discharge (HID) lamps Exit Signs Timeclocks Photocells

39 Non-Weather Sensitive Measures Non-Residential Measures  Exterior Lighting & Exit Signs Methodology HID lamps : delta watts saved * hours of use (4,100 hours) no peak impacts Exit Signs : delta watts saved * 8760 hours * Interactive Effects peak = delta watts * Interactive effects * 1.0 (coincidence factor) Timeclocks & Photocells : watts controlled * hours of control no peak impacts

40 Non-Weather Sensitive Measures Non-Residential Measures  Cooking High efficiency fryers (gas & electric) High efficiency griddle (gas) Hot food holding cabinet Connectionless steamer

41 Non-Weather Sensitive Measures Non-Residential Measures Cooking - Methodology Relied primarily on the PG&E technology briefs For each of these measures, the energy savings calculation methodology is of the form: Savings = (APECRBase – APECREfficient) * Daily Hours * Days Where : APECR = The Average Production Energy Consumption Rate/hour Daily Hours = 12 Days = 365

42 Non-Weather Sensitive Measures Non-Residential Measures  Copy Machines – three sizes 0-20 copies/minute copies/minute over 45 copies/minute Methodology assumptions from Energy Star calculator

43 Non-Weather Sensitive Measures Non-Residential Measures  Vending Machine Controls Characterized in two measures by being installed in: Cold drink vending machines Uncooled snack vending machines Measure savings and characterization from the Pacific Northwest Regional Technical Forum database Methodology assumes operated during off-peak hours, thereforeno demand savings

44 Non-Weather Sensitive Measures Non-Residential Measures  Water Heating Savings expressed as % of base use Base use varies by building type. Come from the 1994 DEER study Measures: High efficiency gas water heater (7.1% savings) Point of use water heater (10% savings) Water circulation pump time clock (6% savings)

45 Non-Weather Sensitive Measures Non-Residential Measures  High Efficiency Motors Meet premium efficiency standards established by the Consortium for Energy Efficiency (CEE) Base efficiency meets Energy Policy Act (EPACT) minimum Motor sizes range from 1 HP to 200 HP Motor hours of operation vary by industry sector Motor loading from US DOE Motor Master software Peak demand based on a coincidence factor of 0.75

46 Non-Weather Sensitive Measures Non-Residential Measures  High Efficiency Motors - Calculation Energy savings (kWh) = (Motor HP / EPACT motor efficiency) * kW/HP * hours of operation * motor loading – (motor HP / premium motor efficiency) * kW/HP * hours of operation * motor loading Peak (kW) = (motor HP * kW/HP * coincidence factor / EPACT motor efficiency) - (motor HP * kW/HP * coincidence factor / premium motor efficiency)

47 Non-Weather Sensitive Measures Non-Residential Measures  Agricultural Measures Low pressure irrigation sprinkler nozzle Sprinkler irrigation to micro irrigation conversion Infrared film for greenhouses Greenhouse heat curtain Variable frequency drive for dairy pumps Ventilation fans or box fans High volume, low speed fans

48 Non-Weather Sensitive Measures Non-Residential Measures  Agricultural Measures Methodology taken from Express Agricultural Working Papers Irrigation savings varied by crop type

49 Questions/Comments?

50 Development of DEER Products Weather Sensitive Energy Savings Presenter: Jeff Hirsch – JJ Hirsch & Associates

51 Weather Sensitive Measures Overview I.Methods Used II.Sources of Information III.Calibration IV.Simulation Cases V.Results Available

52 Weather Sensitive Measures Methods Used  Using up-to-date DOE-2/eQUEST for simulation  Improving engineering accuracy of prototypes  Explicit simulations replace previous simplifications  16 Title 24 climate zones not CEC planning zones  Complete analysis tool published

53 Weather Sensitive Measures Methods Used  Using up-to-date DOE-2/eQUEST for simulation Hourly simulation of all elements Includes details of configurations Allows easy review and update Well understood and open tool

54 Weather Sensitive Measures Methods Used  Improving engineering accuracy of prototypes More complete “activity area” definitions More complete HVAC definitions Coordination with IOU program methods eQUEST “wizard” definitions for flexibility

55 Weather Sensitive Measures Methods Used  Explicit simulations replace previous simplifications Residential: evap cooler, whole house fan, SEER perf., PStat, … Non- Residential: refrigeration systems, HVAC loops/ducts w/losses, …

56 Weather Sensitive Measures Methods Used  16 Title 24 climate zones not CEC planning zones Sizing: Peak load based on design day for each zone Peak demand: Super critical peak days chosen for each zone

57 Weather Sensitive Measures Methods Used  Complete analysis tool published Allows examination of assumptions (prototypes/measures) Eases updating (EM&V, research, new codes/standards)

58 Weather Sensitive Measures Sources of Information  Previous DEER studies  Potential Studies  RASS/CUES surveys  EM&V studies  Published research  Laboratory and field test work

59 Weather Sensitive Measures Calibration  Residential RASS used to update previous studies  Non-residential Adjustments both at “activity area” and whole building level CEUS and EM&V

60 Weather Sensitive Measures Simulation cases  Base case Vintage typical base on survey data  Code base Case Minimally compliant or standard practice  Measure Case Most common program tier's

61 Weather Sensitive Measures Results Available  Customer Savings energy and demand  Above Code Savings Energy and demand  Baselines and Normalizations Baseline and enduse Common units allow scaling

62 Questions/Comments?

63 DEER Update Measure Cost Study Presenter: Floyd Keneipp – Summit Blue Consulting

64 Defining Cost Parameters Measure Cost Specifications  Measure lists provided by Itron  Developed cost specifications for each measure Includes more delineation in terms of sizes, efficiencies and features Measure cost specifications reflect product availability and common installation practices Measure cost team included best judgment regarding size and efficiency breakdowns and “bracketing” of energy analysis specs

65 Defining Cost Parameters Measure Cost Specifications (Cont.)  Measure costs specifications encompass the sizes and technical specs of measures used in the energy analysis, but reflect availability of products on the market Consistent with and indexed to Itron measure specs, but some specifications require a range of values to allow for adequate sample Cost team discerned between a wide range of product options and narrowing pricing to “representative” products options Example – A 90% AFUE single stage furnace was priced but a 90% AFUE furnace with a variable speed fan was not because the costs are very different

66 Defining Cost Parameters Measure Cost Specifications (Cont.)  Cost data is first cost only -- life cycle or O&M costs/cost savings not included  Pricing reflects commonly available “standard” products and excludes specialty, high-end items  Some price observations (outliers) were excluded to assume a rational purchasing policy would be used (“who would pay THAT?”)  Equipment and labor prices are specific to California to extent possible but average across state

67 Defining Cost Parameters Key Cost Definitions  Cost Observation – a single price point for an individual measure or measure configuration Cost values are what a program participant would pay to implement the measure consistent with definitions in the CA Standard Practice Manual (initial capital cost)  Cost units ($ / ton, $ / HP, $ / square foot, etc.) Mostly the same although different for some measures Distinct field in detailed cost data; appended to Cost Basis designator in measure detail

68 Defining Cost Parameters Key Cost Definitions (cont.) Application – indicates if the cost is for: Retrofit (RET) - replacing a working system with a new technology or installing a technology that was not there before. Replace-on-burnout (ROB) - replacing a technology at the end of its useful life. New construction or major renovation (NEW) - installing a technology in a new construction or major renovation project. Cost Basis – indicates if the cost is: Incremental (INCR) - the differential cost between a base technology and an energy efficient technology. Installed (FULL) - the full or installed cost of the measure including equipment, labor, overhead & profit (OH&P).

69 Data Collection and Analysis Process Overview  Created and implemented systematic data collection processes and instruments  Clarified measure lists and specifications through series of communications with Itron and members of Advisory Group  Used 4 analytic methods in determining costs  Labor cost estimates generally base on the following equation; Manhours x Appropriate wage rate  Used multiple data sources to collect cost data  Organized data in Cost Analysis Workbooks

70 Data Collection and Analysis Process Analytic Methods 1.Simple average – Average of all cost observations discarding outliers in some cases where a particular observation appeared out of line 2.Weighted average – Uses one or more observed market variables to weight raw cost data 3.Regression cost model – Regression models using relevant performance factors as independent variables 4.Custom cost estimates – Typical of “engineered” and/or technically complex types of measure where a unique equipment or system configuration needed to be defined and a cost estimate “built up” for the specific technical details of the measure

71 Data Collection and Analysis Process Labor Cost Estimates  Labor cost estimates generally base on manhours required to complete task times appropriate wage rate  Wage rate based on trade (electrician, plumber, etc.) and geographic location of activity  RS Means used to provide wage rate and location adjustment multipliers

72 1. Website and on-site cost surveys of retailers 2. Cost quotes from manufacturers, manufacturers sales representatives, and distributors 3. Cost surveys of contractors and design professionals. 4. Cost data from in California DSM program files, particularly local programs 5. Secondary sources and reports Data Collection and Analysis Process Cost Data Sources

73 Data Collection and Analysis Process Cost Analysis Workbooks  Excel based cost analysis workbook developed for each measure.  Each workbook has 5 sections:

74 Data Collection and Analysis Process Cost Analysis Workbooks – Raw Data  Example of the ‘Raw Data’ section of the High Efficiency Electric Clothes Dryer workbook

75 Data Collection and Analysis Process Cost Analysis Workbooks – Cost Results  Example of the ‘Results’ section of the High Efficiency Electric Clothes Dryer workbook

76 Data Collection and Analysis Process Cost Analysis Workbooks – Statistical Summary  Example of the ‘Statistical Summary’ section of the High Efficiency Electric Clothes Dryer workbook

77 Overview of Cost Data Changes from 2001 to 2005  The scope of some measures has been expanded CFL size categories expanded More evaporative cooler options Windows expanded to include non-res. high performance glazing  Several measures eliminated or reduced in scope Most T8 systems eliminated with the exception of premium efficiency and dimming T8 ballasts Eliminated coin-operated high efficiency clothes washers and hot water heater tank wrap

78 Overview of Cost Data Changes from 2001 to 2005  New measures and measure categories have been added Vending machine occupancy sensor controls High-efficiency office copiers High-efficiency commercial cooking equipment Premium-efficiency motors Heat pump water heaters, point-of-use water heaters, water circulation pump timeclocks Swimming pool pumps Room AC and PTAC broken out as distinct measures  Types and sizes of some applications has been expanded

79 High-Efficiency Refrigerators Example Overview of Cost Data Changes from 2001 to 2005 Capacity (cubic feet) Type 15.5Top Side Botto m 23Top Side Botto m Energy Analysis Spec Capacity (cubic feet) Type 15Top Side 20Top Side 25Top Side 30Top Side 2001 Cost Spec 2005 Cost Spec Capacity (cubic feet) Type 15.5Top Side Bottom 20Top Side Bottom 23Top Side Bottom 25Top Side Bottom 30Top Side Bottom

80 Overview of Cost Data Changes from 2001 to 2005  Examples of cost adjustments Average CFL prices decreasing Installed (full) cost of furnaces up by factor of 2; equipment up about 30%; installation cost estimate up by factor of 4 Energy Star refrigerator prices down over 30% on average

81 Changes in Cost Data Some Examples: CFLs  Market trends changes: CFLs Changes in the manufacturing base -- increase in scale of imports resulting in lower cost products Increasing product availability -- only 10% of CFLs purchased in 2002 were from big 3 mfrs (Philips, Osram, GE) with smaller mfrs getting shelf placement with lower prices Changes in distribution -- web sales increasing, B2C sales increased from $59B in 2000 to $428B in 2004 Prices trending down: NWEEA estimates avg. price down from $14-$28 in 1997 to $5-$10 in 2002 Compared to 2001 DEER, average CFL prices for low volume purchases down by 29%; high volume down by 48%

82 Changes in Cost Data Some Examples: CFL  Retail price spread for integral CFL lamps

83 Cost Data Collection and Analysis Process  Cost data available in four formats 1. Cost data included in measure details from website for each run ID 2. More detailed ‘Cost Data’ file available under Supporting Documents as a downloadable file Organized by measure category More details and measure variations 3. Cost Analysis Workbooks – most detailed 4. In hard copy in the final project report

84  How to find the most applicable cost information? Measure detail pages for each run ID - the per unit equipment measure cost of $13.65 for all 90% residential furnaces This provides an average cost based on a 100,000 Btu furnace The ‘Cost Data’ file under ‘Supporting Documents’ provides prices on a range of furnace sizes This provides a range of costs for 90% AFUE furnaces from 60,000 Btu to 140,000 Btu. Per unit costs ($/KBtu) ranges from $21.53 to $12.13, respectively The cost workbook section – Can use either statistical summary or individual price observations For example, the per unit equipment measure cost for 90% AFUE 100,000 furnaces ranges from to $12.31 to $16.52 based on 9 observations Cost Data Defining Cost Parameters

85 Itron developed a consolidated list of all measures Common units were identified and where possible, made consistent between energy impacts and cost Summit Blue developed point estimates for each measure in the consolidated list and populated the “Consolidated Measure” spreadsheet Itron utilized this “Consolidated Measure” spreadsheet as a series of look-up tables for populating DEER Integration of Costs and Savings Data

86 Questions/Comments?

87 Guide to DEER and Some Results Website and Test Drive Presenters: Gary Cullen – Itron Jeff Hirsch – JJ Hirsch & Associates Floyd Keneipp – Summit Blue

88 Website Considerations  Two Levels of Savings Customer savings - for system savings and early replacement savings. “Above Code” Savings - for all measures affected by an energy code or standard (reportable savings for replace on burnout.)  Common Units The energy and cost common units are distinct Over 90% of cases, they are the same When different, distinctly identified

89 Website Considerations  Application – indicates if the cost is for: Retrofit (RET) - replacing a working system with a new technology or adding a technology. Replace-on-burnout (ROB) - replacing a technology at the end of its useful life New construction or major renovation (NEW) - installing a technology in a new construction or major renovation  Cost Basis – indicates if the cost is: Incremental (INCR) - the differential cost between a base technology and an energy efficient technology Installed (FULL) - the full or installed cost of the measure including equipment, labor, overhead & profit (OH&P)

90 Website Navigation – Opening Screen

91 Website Navigation – Browse Measures

92 Website Navigation – Select Subcategory

93 Website Navigation – Review Summary Page - Top

94 Website Navigation –Summary Page Information  Area #1 - Summary Identification of 13 variables  Area #2 – Further Filtering Options Climate Zone, Building Type, Vintage, Savings Unit  Area #3 – Sorting Order  Area #4 – Download Measure Detain in Excel There are Excel spreadsheet limitations

95 Website Navigation – Review Summary Page - Bottom

96 Website Navigation –Summary Page Information  At bottom is listing of how many measures are included in this summary A large number would indicate a need for further filtering in order to do the download

97 Website Navigation – Detailed Measure Information

98 Website Navigation – Detailed Measure information - Top

99 Website Navigation – Detailed Measure information - Bottom

100 Supporting Documents Section  Website Users Guide  Net-to-Gross Ratios Table  Access Tables  Glossary  Cost Data  Cost Data User’s Guide  New EUL Estimates (SERA Report)  Consolidated Measure Data

101 Supporting Documents Section – Consolidated Measure Data

102 Questions/Comments?

103 DEER UPDATE PLAN Presenter: Mike Rufo, Quantum Inc. Measure Savings Team Itron, J. J. Hirsch Associates, Quantum Inc, Synergy Measure Cost Team Summit Blue Consulting, Heschong-Mahone Group

104 Planning for DEER Updates and Linkages to EM&V Objectives ID and discuss DEER-related Issues ID and discuss DEER-related EM&V needs Recommendations for future DEER updates Recommendations for improved EM&V-DEER linkages Approach Interviews with Joint Staff, IOUs, others Review of EM&V studies and plans Lessons learned from current and past studies Deliverables Report/chapter on issues and recommendations Prioritized list of detailed measurement needs

105 Key Update Issues Guidelines/Requirements for DEER Use DEER Update Process Energy Savings Methods and Sources Baseline Calibration and Load Shapes Segmentation and Averaging Costing Issues Types of Data to Include Measure Coverage and Allocation of Resources Measure-specific and EM&V Linkage Issues Documentation

106 DEER Update Process Most suggest DEER be preferred (default) source of program planning data, some JS prefer mandatory Deviations permitted if data not available in DEER If data in DEER, demonstrate why alternate data superior If not in DEER, increased regulatory review, higher likelihood of ex post measurement of savings Comprehensively updated at least every three years Process put in place to allow updates to specific values to occur more often (every year or half year) – Start Jan. ‘06 Next comprehensive update should be completed by end of ‘07 Update based on availability of superior information Strive for expected value orientation Neither conservative nor optimistic… But lean conservative in face of great uncertainty and risk Involve diverse group of experts

107 Savings Methods and Calibration Three primary methods: Engineering calcs, building simulations, eval/field/lab data All methods should be calibrated Calibration has several elements General baseline (e.g., EUIs/UECs, EFLH) Specific baseline (e.g., duct leakage, thermostat behavior) Savings (e.g., evaluation results) Load shapes (not a primary focus of current DEER) Key sources RASS, CEUS, tracking and billing data, eval/field/lab data Tradeoffs among accuracy, simplicity, transparency

108 Segmentation and Averaging General/default approach - reflect market average Extensive segmentation for weather sensitive Btype, vintage, CZ – 1,680 combos Program managers desire data for sub-segments Less efficient portion of pop Groups with specific characteristics Inclusion of sub-segment data should be considered But with caution, can backfire (e.g., t-stats in ’01 DEER) PMs must have plausible approach to targeting For both segments and sub-segments Need to include market weights Default average results across segments

109 Costing Issues Clearer measure specs and better/earlier integration w. savings task Systematize the pricing process to extent possible Index certain costing elements to industry recognized pricing methods and resources Conduct more frequent, targeted and less expansive updates Integrate cost data collection and reporting into program delivery (and evaluation) if possible Increase importance and resources for cost analysis Historically, costs are step-child to savings As important to TRC B-C ratio as savings

110 Types of Data to Include Interviewees asked which of following to include: energy savings, peak savings, load shape, cost, effective useful life (EUL), net to gross ratio (NTGR), penetration and saturation information, potential study results Most responded that all of above should be included, several said with exception of NTGRs Additional elements suggested included carbon, total source BTU, and water impacts We recommend including, at a minimum: Energy & peak savings, load shapes (could be reduced form), costs, EULs, market weights tied to segments NTGR incorporation needs more consideration

111 Measure Coverage and Allocation of Resources DEER has never included all measures Focus on prescriptive-type measures Focus on prototypical measures Scope/resource tradeoffs Limited criteria-based allocation of resources Small impact measures sometimes absorb disproportionate resources Future efforts should prioritize based on Contribution to program areas and portfolio, potential Cost-effectiveness and associated uncertainty List of measures to add compiled More effort needed on custom (EM&V and DEER)

112 Measure-specific and EM&V Linkage Issues Many difficult measure issues Lack of appropriate and reliable evaluation data List developed of measure-specific evaluation needs Need evaluations to produce measure-, segment-, and parameter-level results (Pre-98 impact evals focused on program realization rates) Importance of pre-measurement Some issues beg for controlled experiments Integration between DEER and Protocols teams DEER team need for direct access to eval data

113 Measure-Level Issues

114 Documentation Strong desire for highly detailed documentation Parameters, assumptions, and sources Electronically-linked documentation also desired Explanations of database fields Appropriate warnings or caveats Quality of documentation tied to decision to use Given DEER’s importance, level of documentation needed greater than for many other projects Adequate resources must be allocated Documentation must be timely Database preferred to website views due to volume of data and need for analysis

115 Questions/Comments?