1 Database for Energy Efficiency Resource Update Project Information and Final Results A DEER...

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Database for Energy Efficiency Resource

Update ProjectInformation and Final Results

A DEER Presentation at CALMAC Meeting

Pacific Energy Center, San FranciscoSeptember 21, 2005

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DEER UpdateIntroduction and History

DEERMeasure Cost Study

Objectives and EE Regulatory/Policy Context

Project Management Structure Program Advisory Committee

Technical CommitteeDecision-making Processes and Orientation

Challenges and Accomplishments

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DEER UpdateProject Implementation Structure

and Consultant Team Roles

Presenters:Gary Cullen – Itron

Floyd Keneipp – Summit BlueMeasure Savings Team Itron, J. J. Hirsch Associates, Quantum Inc, SynergyMeasure Cost TeamSummit Blue Consulting, Heschong-Mahone Group

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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 2002-03 phase) Jennifer Barnes, PG&E Leonel Campoy, SCE Craig Tyler, Tyler Associates (PG&E representative 2002-03 phase) Jay Luboff (former ED representative 2002-03 phase) Eli Kollman (former ED representative 2002-03 phase) Others

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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

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Measure Savings ProjectConsultant 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

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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

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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

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Synergy

Christine Chin-Ryan

Develop web interface

Populate web interface with data

Debug web interface

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Measure costs developed under separate contract by Summit Blue

Measure cost team and roles will be discussed later

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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)

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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

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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

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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

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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

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DEER Update

Final Report Milestones Draft Final Report - Sept 30th for PAC

Final Report - October 31st

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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

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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.

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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

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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

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Questions/Comments?

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Development of DEER Products

Non-Weather Sensitive Energy Savings

Presenter:

Gary Cullen – Itron

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Non-Weather Sensitive Measures Residential Measures

CFL Lighting

Refrigerators

Clothes Washers & Dryers

Dishwashers

Water Heating

Swimming Pool Pumps

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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

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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 * 0.081 = 3.35 W

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Refrigerators

Used the Energy Star calculator available on-line at:http://www.energystar.gov

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)

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Clothes Washers

Utilized the three recommended Consortium for Energy Efficiency (CEE) Tiers forModified Energy Factor:

Used the Energy Star calculator (that utilizes an EF rather than MEF) on-line at:http://www.energystar.govEstimated 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 typesFuel impact disagreegations based on ‘Efficiency Vermont” estimates

Demand impact based on a energy/peak factor of 0.417. This is carryoverfrom previous 2001 DEER

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Clothes Washer – Example (Tier 3 2.65 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 * 0.417 = 186.4 W

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Clothes Dryer

1993 National Appliance Energy Conservation Act (NAECA) minimum efficiency used for base technology:

EF = 3.01 for electric dryersEF = 2.67 for gas dryers

Used DOE test procedure guidelines for:Drying cycles per year = 416UEC 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


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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 * 0.371 = 17.8 W

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Dishwasher

Used the Energy Star calculator available on-line at:http://www.energystar.gov

Key Input values for the calculator:Base Energy Factor (EF) = 0.46Measure Energy Factor = 0.58Annual 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 0.371. This is carryover from previous 2001 DEER

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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 heaterlow flow showerhead (from 2.5 to 2.0 gallons per minute)Pipe wrapFaucet aerators

Savings expressed as % of base use Base use varied by utility service area (same method as 2001)


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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%

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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 gallonsAverage water turnover rate of 6-8 hours Average pump motor demand of 1.75 kVATypical filtration time of 4 to 6 hours

For single speed motors, motor downsizing and runtime reductions assumed

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Non-Weather Sensitive Measures Non-Residential Measures

Interior Lighting

Exterior Lighting

Cooking

Copy Machine

Water Heating

Vending Machine Controls

High Efficiency Motors

Agriculture

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Interior Lighting Measures:CFL screw-in lampsCFL hardwire fixturesHigh intensity discharge (HID) lampsPremium T8 lampsDimming BallastsDe-lamping fluorescent 4 ft and 8 ft fixtures

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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

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Exterior Lighting & Exit Signs High intensity discharge (HID) lampsExit SignsTimeclocksPhotocells

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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

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Cooking High efficiency fryers (gas & electric)High efficiency griddle (gas)Hot food holding cabinetConnectionless steamer

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Cooking - Methodology Relied primarily on the PG&E technology briefs

For each of these measures, the energy savings calculationmethodology is of the form:

Savings = (APECRBase – APECREfficient) * Daily Hours * Days

Where:

APECR = The Average Production Energy Consumption Rate/hourDaily Hours = 12Days = 365

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Copy Machines – three sizes 0-20 copies/minute21-44 copies/minute over 45 copies/minute

Methodology assumptions from Energy Star calculator

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Vending Machine Controls Characterized in two measures by being installed in:

Cold drink vending machinesUncooled 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

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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)

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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

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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)

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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

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Agricultural Measures Methodology taken from Express Agricultural

Working Papers

Irrigation savings varied by crop type

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Questions/Comments?

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Development of DEER Products

Weather Sensitive Energy Savings

Presenter:

Jeff Hirsch – JJ Hirsch & Associates

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Weather Sensitive MeasuresOverview

I. Methods Used

II. Sources of Information

III. Calibration

IV. Simulation Cases

V. Results Available

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Weather Sensitive MeasuresMethods 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

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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

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Improving engineering accuracy of prototypes

• More complete “activity area” definitions

• More complete HVAC definitions

• Coordination with IOU program methods

• eQUEST “wizard” definitions for flexibility

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Explicit simulations replace previous simplifications

• Residential:

evap cooler, whole house fan, SEER perf., PStat, …

• Non- Residential:

refrigeration systems, HVAC loops/ducts w/losses, …

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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

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Complete analysis tool published

• Allows examination of assumptions (prototypes/measures)

• Eases updating (EM&V, research, new codes/standards)

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Weather Sensitive MeasuresSources of Information

Previous DEER studies

Potential Studies

RASS/CUES surveys

EM&V studies

Published research

Laboratory and field test work

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Weather Sensitive MeasuresCalibration

Residential

• RASS used to update previous studies

Non-residential

• Adjustments both at “activity area” and whole building level

• CEUS and EM&V

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Weather Sensitive MeasuresSimulation cases

Base case

• Vintage typical base on survey data

Code base Case

• Minimally compliant or standard practice

Measure Case

• Most common program tier's

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Weather Sensitive MeasuresResults Available

Customer Savings

• energy and demand

Above Code Savings

• Energy and demand

Baselines and Normalizations

• Baseline and enduse• Common units allow scaling

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Questions/Comments?

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DEER UpdateMeasure Cost Study

Presenter:

Floyd Keneipp – Summit Blue Consulting

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Defining Cost ParametersMeasure 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

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Defining Cost ParametersMeasure 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

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Defining Cost ParametersMeasure 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

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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

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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).

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Data Collection and Analysis ProcessOverview

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

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Data Collection and Analysis ProcessAnalytic 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

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Data Collection and Analysis ProcessLabor Cost Estimates

1.101.10Fresno

1.101.10Statewide average

1.081.11Sacramento

1.041.04San Diego

1.071.06Los Angeles

1.221.21San Francisco

Non-residentialResidentialCity

1.101.10Fresno

1.101.10Statewide average

1.081.11Sacramento

1.041.04San Diego

1.071.06Los Angeles

1.221.21San Francisco

Non-residentialResidentialCity

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

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1. Website and on-site cost surveys of retailers2. Cost quotes from manufacturers, manufacturers

sales representatives, and distributors3. Cost surveys of contractors and design

professionals.4. Cost data from in California DSM program files,

particularly local programs5. Secondary sources and reports

Data Collection and Analysis Process Cost Data Sources

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Data Collection and Analysis Process Cost Analysis Workbooks

Contact Log Data sources and contact information

Raw Data Raw cost data supplied by data sources

Data for Analysis Raw cost data organized for analysis purposes

Cost Analysis Measure cost analysis and modeling

Cost Results Final incremental and installed cost data for each measure and measure variation

Statistical Summary Summary of statistical variables for each measure including range, confidence and standard deviation.

Excel based cost analysis workbook developed for each measure.

Each workbook has 5 sections:

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Data Collection and Analysis Process Cost Analysis Workbooks – Raw Data

Example of the ‘Raw Data’ section of the High Efficiency Electric Clothes Dryer workbook

Log IDMeasure ID Measure Description Mfr Model No. Size

Size Units Eff Eff Units Volts

Base or Measure Cost Type

Cost Basis (Eq., Incr. Eq., Inst. or Incr. Inst.)

Equipment Cost (per unit)

RF_34 D03-941 High Efficiency Electric Clothes Dryer with Moisture Sensor. Maytag MDE6400A 6.0 Cu Ft 924 kWh/year 240 Base MSRP equipment $565.00

RF_34 D03-941 High Efficiency Electric Clothes Dryer with Moisture Sensor. Maytag MDE2400A 6.0 Cu Ft 924 kWh/year 240 Base MSRP equipment $565.00

RF_34 D03-941 High Efficiency Electric Clothes Dryer with Moisture Sensor. Maytag SDE3606A 7.1 Cu Ft 924 kWh/year 240 Base MSRP equipment $442.00

RF_29 D03-941 High Efficiency Electric Clothes Dryer with Moisture Sensor. Whirlpool GEW9868K 7.4 Cu Ft 950 kWh/year 120 Measure MSRP equipment $699.00

RF_29 D03-941 High Efficiency Electric Clothes Dryer with Moisture Sensor. Whirlpool GEW9868P 7.4 Cu Ft 950 kWh/year 240 Measure MSRP equipment $649.00

RF_29 D03-941 High Efficiency Electric Clothes Dryer with Moisture Sensor. Whirlpool GEQ9800P 7.4 Cu Ft 950 kWh/year 240 Measure MSRP equipment $499.00

Tech Specs

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Data Collection and Analysis Process Cost Analysis Workbooks – Cost Results

Example of the ‘Results’ section of the High Efficiency Electric Clothes Dryer workbook

Measure IDMeasure Name

Measure Description

Base Description

Delivery Channel Application

Energy Star?

Purchase Volume Cost Basis

Base Equipment Cost

Measure Equipment Cost

Incremental Equipment Cost

Cost Unit

D03-941

Efficient Clothes Dryer

High Efficiency Electric Clothes Dryer with Moisture Sensor.

Electric Clothes Dryer EF=3.01. Single Family, 416 dry cycles Retail ROB/NEW No low INCR/INCR $319 $557 $238 Dryer

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Data Collection and Analysis Process Cost Analysis Workbooks – Statistical Summary

Example of the ‘Statistical Summary’ section of the High Efficiency Electric Clothes Dryer workbook

Measure IDAnalysis Method # Obs Mean Median Min Max # Obs Mean Median Min Max

D03-941 Average 40 $557 $525 $261 $869 38 $319 $296 $224 $509

BaseMeasure

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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

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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

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High-Efficiency Refrigerators Example


Capacity (cubic feet)

Type

15.5 Top

Side

Bottom

23 Top

Side

Bottom

Energy Analysis Spec Capacity (cubic feet)

Type

15 Top

Side

20 Top

Side

25 Top

Side

30 Top

Side

2001 Cost Spec

2005 Cost Spec

Capacity (cubic feet)

Type

15.5 Top

Side

Bottom

20 Top

Side

Bottom

23 Top

Side

Bottom

25 Top

Side

Bottom

30 Top

Side

Bottom

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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

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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%

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Changes in Cost Data Some Examples: CFL

Retail Price Spread of Integral CFL Lamps

$0.00

$5.00

$10.00

$15.00

$20.00

$25.00

7 9 11 13 14 15 16 18 19 20 23 25 26 28 32 36 50

Lamp Wattage

Ob

serv

ed R

etai

l C

ost

($)

Average

Retail price spread for integral CFL lamps

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Cost Data Collection and Analysis Process

Cost data available in four formats1. Cost data included in measure details from website

for each run ID2. 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 detailed4. In hard copy in the final project report

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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

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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

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Questions/Comments?

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Guide to DEER and Some Results

Website and Test Drive

Presenters:

Gary Cullen – Itron

Jeff Hirsch – JJ Hirsch & Associates

Floyd Keneipp – Summit Blue

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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

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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)

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Website Navigation – Opening Screen

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Website Navigation – Browse Measures

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Website Navigation – Select Subcategory

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Website Navigation – Review Summary Page - Top

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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

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Website Navigation – Review Summary Page - Bottom

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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

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Website Navigation – Detailed Measure Information

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Website Navigation – Detailed Measure information - Top

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Website Navigation – Detailed Measure information - Bottom

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Supporting Documents Section

Website Users Guide Net-to-Gross Ratios Table Access Tables Glossary Cost Data Cost Data User’s Guide New EUL Estimates 7-14-05 (SERA Report) Consolidated Measure Data

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Supporting Documents Section – Consolidated Measure Data

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Questions/Comments?

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DEER UPDATE PLAN

Presenter:Mike Rufo, Quantum Inc.

Measure Savings Team Itron, J. J. Hirsch Associates, Quantum Inc, SynergyMeasure Cost TeamSummit Blue Consulting, Heschong-Mahone Group

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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

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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

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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

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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

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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

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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

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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

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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)

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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

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Measure-Level Issues

Primary Sector Category IssueAll General Better Alignment Between EM&V Results and DEER InputsAll General Better Characterization of Uncertainty Around DEER EstimatesAll General Further Effort to Calibrate and Segment Base ConsumptionAll General Inclusion of Load Shape DataAll General Inclusion of Measure Packages/InteractionsResidential HVAC High Efficiency Equipment - Energy and Peak Savings (EER/SEER issue)Residential HVAC Room A/C - Hours of Operation and SavingsResidential HVAC Duct Sealing - Parameters and SavingsResidential HVAC HVAC Practices - Parameters and Savings (e.g., refrigerant charging)Residential HVAC Programmable Thermostats - Behavior and SavingsResidential HVAC Evaporative Coolers Impacts (including comfort)Residential Lighting CFL Average Hours of OperationResidential Lighting CFL Other Issues (e.g., in-service rates, base wattages, replacement, etc.)Residential Appliances Clothes Washers - SavingsResidential Pool Pump Pool Pumps - Operation Hours, Wattages, and Savings Non-Residential HVAC Documentation and Calibration of Equivalent Full Load Hours of OperationNon-Residential HVAC Definitions and Baselines for AC and Chillers Non-Residential Lighting CFL Average Hours of Operation (e.g., larger samples, more segments)Non-Residential Lighting CFL Other Issues (e.g., screw-in vs. hard wired, re-install behavior/re-rebates)

Non-Residential Lighting Other Non-residential Lighting Issues (e.g., EFLH by tech and segment)Non-Residential Refrigeration Refrigeration - Savings & Costs (integration, expanded analysis)Non-Residential Motors Motors - Parameters and Base Case Assumptions (e.g., rewind vs. new motors)

Non-Residential All Custom Measure Savings and Costs (e.g., calculators, prototypical cases, eval)Non-Residential Lighting New Construction Savings and Costs Linkage (e.g., design features to beat 05 T24)

Non-Residential Windows New Construction Savings and Costs Linkage (e.g., daylight/HVAC)

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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

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Questions/Comments?

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