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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. DEER Update. Introduction and History DEER Measure Cost Study

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database for energy efficiency resource update project information and final results

Database for Energy Efficiency Resource Update ProjectInformation and Final Results

A DEER Presentation

at CALMAC Meeting

Pacific Energy Center, San Francisco

September 21, 2005

deer update
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
deer update project implementation structure and consultant team roles

DEER UpdateProject 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

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

Project Advisory Team
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

Role of Project Advisory Team
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

Measure Savings ProjectConsultant Team Roles
measure savings project consultant team roles7
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

Measure Savings ProjectConsultant Team Roles
measure savings project consultant team roles8
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

Measure Savings ProjectConsultant Team Roles
measure savings project consultant team roles9
Synergy

Christine Chin-Ryan

Develop web interface

Populate web interface with data

Debug web interface

Measure Savings ProjectConsultant Team Roles
what is deer
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)
previous deer database
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
deer update13
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
deer update14
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
deer update15
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
deer update16
DEER Update

Final Report Milestones

  • Draft Final Report - Sept 30th for PAC
  • Final Report - October 31st
deer update17
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
measure cost study mcs project team
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.
mcs project overview
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
measure cost study mcs project scope of effort
Measure Cost Study (MCS) Project Scope of effort
  • 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
development of deer products non weather sensitive energy savings

Development of DEER ProductsNon-Weather Sensitive Energy Savings

Presenter:

Gary Cullen – Itron

non weather sensitive measures residential measures
Non-Weather Sensitive MeasuresResidential Measures
  • CFL Lighting
  • Refrigerators
  • Clothes Washers & Dryers
  • Dishwashers
  • Water Heating
  • Swimming Pool Pumps
non weather sensitive measures residential measures24
Non-Weather Sensitive MeasuresResidential Measures
  • CFL LightingMeasure 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

non weather sensitive measures residential measures25
Non-Weather Sensitive MeasuresResidential 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 * 0.081 = 3.35 W

non weather sensitive measures residential measures26
Non-Weather Sensitive MeasuresResidential Measures
  • RefrigeratorsUsed 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)

non weather sensitive measures residential measures27
Non-Weather Sensitive MeasuresResidential 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:http://www.energystar.gov 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 0.417. This is carryover from previous 2001 DEER
non weather sensitive measures residential measures28
Non-Weather Sensitive MeasuresResidential Measures
  • 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

non weather sensitive measures residential measures29
Non-Weather Sensitive MeasuresResidential Measures
  • Clothes Dryer1993 National Appliance Energy Conservation Act (NAECA) minimum efficiency used for base technology: EF = 3.01 for electric dryers EF = 2.67 for gas dryersUsed 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 0.371. This is carryover from previous 2001 DEER
non weather sensitive measures residential measures30
Non-Weather Sensitive MeasuresResidential 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 * 0.371 = 17.8 W

non weather sensitive measures residential measures31
Non-Weather Sensitive MeasuresResidential Measures
  • DishwasherUsed the Energy Star calculator available on-line at: http://www.energystar.gov

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 0.371. This is carryover from previous 2001 DEER
non weather sensitive measures residential measures32
Non-Weather Sensitive MeasuresResidential Measures
  • Water HeatingMeasures: 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 0.22. This is carryover from previous 2001 DEER
non weather sensitive measures residential measures33
Non-Weather Sensitive MeasuresResidential Measures
  • Water HeatingMeasure 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%
non weather sensitive measures residential measures34
Non-Weather Sensitive MeasuresResidential Measures
  • Pool PumpsSingle 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
non weather sensitive measures non residential measures
Non-Weather Sensitive MeasuresNon-Residential Measures
  • Interior Lighting
  • Exterior Lighting
  • Cooking
  • Copy Machine
  • Water Heating
  • Vending Machine Controls
  • High Efficiency Motors
  • Agriculture
non weather sensitive measures non residential measures36
Non-Weather Sensitive MeasuresNon-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
non weather sensitive measures non residential measures37
Non-Weather Sensitive MeasuresNon-Residential Measures
  • Interior Lighting – Basic MethodologyMeasure 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

non weather sensitive measures non residential measures38
Non-Weather Sensitive MeasuresNon-Residential Measures
  • Exterior Lighting & Exit Signs High intensity discharge (HID) lamps Exit Signs Timeclocks Photocells
non weather sensitive measures non residential measures39
Non-Weather Sensitive MeasuresNon-Residential Measures
  • Exterior Lighting & Exit Signs MethodologyHID lamps: delta watts saved * hours of use (4,100 hours) no peak impactsExit 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
non weather sensitive measures non residential measures40
Non-Weather Sensitive MeasuresNon-Residential Measures
  • Cooking High efficiency fryers (gas & electric) High efficiency griddle (gas) Hot food holding cabinet Connectionless steamer
non weather sensitive measures non residential measures41
Non-Weather Sensitive MeasuresNon-Residential Measures

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

non weather sensitive measures non residential measures42
Non-Weather Sensitive MeasuresNon-Residential Measures
  • Copy Machines – three sizes 0-20 copies/minute 21-44 copies/minute over 45 copies/minute Methodology assumptions from Energy Star calculator
non weather sensitive measures non residential measures43
Non-Weather Sensitive MeasuresNon-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, therefore no demand savings
non weather sensitive measures non residential measures44
Non-Weather Sensitive MeasuresNon-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)
non weather sensitive measures non residential measures45
Non-Weather Sensitive MeasuresNon-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
non weather sensitive measures non residential measures46
Non-Weather Sensitive MeasuresNon-Residential Measures
  • High Efficiency Motors - CalculationEnergy 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)

non weather sensitive measures non residential measures47
Non-Weather Sensitive MeasuresNon-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
non weather sensitive measures non residential measures48
Non-Weather Sensitive MeasuresNon-Residential Measures
  • Agricultural Measures Methodology taken from Express Agricultural Working Papers Irrigation savings varied by crop type
development of deer products weather sensitive energy savings

Development of DEER Products Weather Sensitive Energy Savings

Presenter:

Jeff Hirsch – JJ Hirsch & Associates

weather sensitive measures overview
Weather Sensitive MeasuresOverview
  • Methods Used
  • Sources of Information
  • Calibration
  • Simulation Cases
  • Results Available
weather sensitive measures methods used
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
weather sensitive measures methods used53
Weather Sensitive MeasuresMethods 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
weather sensitive measures methods used54
Weather Sensitive MeasuresMethods 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
weather sensitive measures methods used55
Weather Sensitive MeasuresMethods Used
  • Explicit simulations replace previous simplifications
    • Residential:

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

    • Non- Residential:

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

weather sensitive measures methods used56
Weather Sensitive MeasuresMethods 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

weather sensitive measures methods used57
Weather Sensitive MeasuresMethods Used
  • Complete analysis tool published
    • Allows examination of assumptions (prototypes/measures)
    • Eases updating (EM&V, research, new codes/standards)
weather sensitive measures sources of information
Weather Sensitive MeasuresSources of Information
  • Previous DEER studies
  • Potential Studies
  • RASS/CUES surveys
  • EM&V studies
  • Published research
  • Laboratory and field test work
weather sensitive measures calibration
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
weather sensitive measures simulation cases
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
weather sensitive measures results available
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
deer update measure cost study

DEER UpdateMeasure Cost Study

Presenter:

Floyd Keneipp – Summit Blue Consulting

defining cost parameters measure cost specifications
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
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

Defining Cost ParametersMeasure Cost Specifications (Cont.)
defining cost parameters measure cost specifications cont66
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
defining cost parameters key cost definitions
Defining Cost ParametersKey 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
defining cost parameters key cost definitions cont
Defining Cost ParametersKey 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).
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

Data Collection and Analysis ProcessOverview
data collection and analysis process analytic methods
Data Collection and Analysis ProcessAnalytic Methods
  • Simple average – Average of all cost observations discarding outliers in some cases where a particular observation appeared out of line
  • Weighted average – Uses one or more observed market variables to weight raw cost data
  • Regression cost model – Regression models using relevant performance factors as independent variables
  • 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
data collection and analysis process labor cost estimates
Data Collection and Analysis ProcessLabor 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
data collection and analysis process cost data sources
Website and on-site cost surveys of retailers

Cost quotes from manufacturers, manufacturers sales representatives, and distributors

Cost surveys of contractors and design professionals.

Cost data from in California DSM program files, particularly local programs

Secondary sources and reports

Data Collection and Analysis Process Cost Data Sources
data collection and analysis process cost analysis workbooks raw data
Data Collection and Analysis Process Cost Analysis Workbooks – Raw Data
  • Example of the ‘Raw Data’ section of the High Efficiency Electric Clothes Dryer workbook
data collection and analysis process cost analysis workbooks cost results
Data Collection and Analysis Process Cost Analysis Workbooks – Cost Results
  • Example of the ‘Results’ section of the High Efficiency Electric Clothes Dryer workbook
data collection and analysis process cost analysis workbooks statistical summary
Data Collection and Analysis Process Cost Analysis Workbooks – Statistical Summary
  • Example of the ‘Statistical Summary’ section of the High Efficiency Electric Clothes Dryer workbook
overview of cost data changes from 2001 to 2005
Overview of Cost Data Changes from2001 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
overview of cost data changes from 2001 to 200578
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
overview of cost data changes from 2001 to 200580
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
changes in cost data some examples cfls
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%
changes in cost data some examples cfl
Changes in Cost Data Some Examples: CFL
  • Retail price spread for integral CFL lamps
cost data collection and analysis process
Cost DataCollection and Analysis Process
  • Cost data available in four formats
    • Cost data included in measure details from website for each run ID
    • More detailed ‘Cost Data’ file available under Supporting Documents as a downloadable file
      • Organized by measure category
      • More details and measure variations
    • Cost Analysis Workbooks – most detailed
    • In hard copy in the final project report
cost data defining cost parameters
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
integration of costs and savings data
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
guide to deer and some results website and test drive

Guide to DEER and Some ResultsWebsite and Test Drive

Presenters:

Gary Cullen – Itron

Jeff Hirsch – JJ Hirsch & Associates

Floyd Keneipp – Summit Blue

website considerations
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
website considerations89
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)
website navigation summary page information
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
website navigation summary page information96
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
supporting documents section
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
deer update plan

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

slide104
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
slide105
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
slide106
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
slide107
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
slide108
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
costing issues
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
slide110
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
slide111
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)
slide112
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
slide114
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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