DEER and Measure Cost Presentation
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Transcript DEER and Measure Cost Presentation
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
1
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
2
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
3
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
4
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
5
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
6
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
7
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
8
Measure Savings Project
Consultant Team Roles
Synergy
Christine Chin-Ryan
Develop web interface
Populate web interface with data
Debug web interface
9
Measure Savings Project
Consultant Team Roles
Measure costs developed under separate
contract by Summit Blue
Measure cost team and roles will be
discussed later
10
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)
11
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
12
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
13
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
14
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
15
DEER Update
Final Report Milestones
Draft Final Report - Sept 30th for PAC
Final Report - October 31st
16
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
17
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.
18
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
19
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
20
Questions/Comments?
21
Development of DEER
Products
Non-Weather Sensitive Energy
Savings
Presenter:
Gary Cullen – Itron
22
Non-Weather Sensitive Measures
Residential Measures
CFL Lighting
Refrigerators
Clothes Washers & Dryers
Dishwashers
Water Heating
Swimming Pool Pumps
23
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
24
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 * 0.081
= 3.35 W
25
Non-Weather Sensitive Measures
Residential Measures
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)
26
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:
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
27
Non-Weather Sensitive Measures
Residential 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
28
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 0.371. This is carryover
from previous 2001 DEER
29
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 * 0.371
= 17.8 W
30
Non-Weather Sensitive Measures
Residential Measures
Dishwasher
Used the Energy Star calculator available on-line at:
http://www.energystar.gov
Key Input values for the calculator:
Base Energy Factor (EF) = 0.46
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
31
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 0.22. This is carryover
from previous 2001 DEER
32
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%
33
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
34
Non-Weather Sensitive Measures
Non-Residential Measures
Interior Lighting
Exterior Lighting
Cooking
Copy Machine
Water Heating
Vending Machine Controls
High Efficiency Motors
Agriculture
35
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
36
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
37
Non-Weather Sensitive Measures
Non-Residential Measures
Exterior Lighting & Exit Signs
High intensity discharge (HID) lamps
Exit Signs
Timeclocks
Photocells
38
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
39
Non-Weather Sensitive Measures
Non-Residential Measures
Cooking
High efficiency fryers (gas & electric)
High efficiency griddle (gas)
Hot food holding cabinet
Connectionless steamer
40
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
41
Non-Weather Sensitive Measures
Non-Residential Measures
Copy Machines – three sizes
0-20 copies/minute
21-44 copies/minute
over 45 copies/minute
Methodology assumptions from Energy Star
calculator
42
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, therefore no demand savings
43
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)
44
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
45
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)
46
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
47
Non-Weather Sensitive Measures
Non-Residential Measures
Agricultural Measures
Methodology taken from Express Agricultural
Working Papers
Irrigation savings varied by crop type
48
Questions/Comments?
49
Development of DEER
Products
Weather Sensitive Energy
Savings
Presenter:
Jeff Hirsch – JJ Hirsch &
Associates
50
Weather Sensitive Measures
Overview
I.
Methods Used
II.
Sources of Information
III. Calibration
IV. Simulation Cases
V.
Results Available
51
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
52
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
53
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
54
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, …
55
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
56
Weather Sensitive Measures
Methods Used
Complete analysis tool published
•
Allows examination of assumptions
(prototypes/measures)
•
Eases updating (EM&V, research, new
codes/standards)
57
Weather Sensitive Measures
Sources of Information
Previous DEER studies
Potential Studies
RASS/CUES surveys
EM&V studies
Published research
Laboratory and field test work
58
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
59
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
60
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
61
Questions/Comments?
62
DEER Update
Measure Cost Study
Presenter:
Floyd Keneipp – Summit Blue
Consulting
63
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
64
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
65
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
66
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
67
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).
68
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
69
Data Collection and Analysis Process
Analytic Methods
1.
2.
3.
4.
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
70
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
City
Residential
Non-residential
San Francisco
1.21
1.22
Los Angeles
1.06
1.07
San Diego
1.04
1.04
Sacramento
1.11
1.08
Fresno
1.10
1.10
Statewide average
1.10
1.10
71
Data Collection and Analysis Process
Cost Data Sources
1.
2.
3.
4.
5.
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
72
Data Collection and Analysis Process
Cost Analysis Workbooks
Excel based cost analysis workbook developed for each
measure.
Each workbook has 5 sections:
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.
73
Data Collection and Analysis Process
Cost Analysis Workbooks – Raw Data
Example of the ‘Raw Data’ section of the High Efficiency Electric
Clothes Dryer workbook
Tech Specs
Size
Size
Units
Eff
Eff Units
Volts
Base or
Measure
Cost Basis
(Eq., Incr.
Equipment
Eq., Inst. or Cost (per
Cost Type Incr. Inst.) unit)
High Efficiency Electric Clothes Dryer with
Maytag
Moisture MDE6400A
Sensor.
6.0
Cu Ft
924
kWh/year
240
Base
MSRP
equipment
$565.00
High Efficiency Electric Clothes Dryer with
Maytag
Moisture MDE2400A
Sensor.
6.0
Cu Ft
924
kWh/year
240
Base
MSRP
equipment
$565.00
D03-941
High Efficiency Electric Clothes Dryer with
Maytag
Moisture SDE3606A
Sensor.
7.1
Cu Ft
924
kWh/year
240
Base
MSRP
equipment
$442.00
RF_29
D03-941
High Efficiency Electric Clothes Dryer with
Whirlpool
Moisture GEW9868K
Sensor.
7.4
Cu Ft
950
kWh/year
120
Measure
MSRP
equipment
$699.00
RF_29
D03-941
High Efficiency Electric Clothes Dryer with
Whirlpool
Moisture GEW9868P
Sensor.
7.4
Cu Ft
950
kWh/year
240
Measure
MSRP
equipment
$649.00
RF_29
D03-941
High Efficiency Electric Clothes Dryer with
Whirlpool
Moisture GEQ9800P
Sensor.
7.4
Cu Ft
950
kWh/year
240
Measure
MSRP
equipment
$499.00
Measure
Log ID ID
Measure Description
RF_34
D03-941
RF_34
D03-941
RF_34
Mfr
Model No.
74
Data Collection and Analysis Process
Cost Analysis Workbooks – Cost Results
Example of the ‘Results’ section of the High Efficiency Electric
Clothes Dryer workbook
Measure
Measure ID Name
D03-941
Efficient
Clothes
Dryer
Measure
Description
Base
Description
Delivery
Channel Application
Energy
Star?
Purchase
Volume
Base
Equipment
Cost Basis Cost
High Efficiency
Electric Clothes
Dryer with
Moisture
Sensor.
Electric Clothes
Dryer EF=3.01.
Single Family,
416 dry cycles
Retail
No
low
INCR/INCR
ROB/NEW
$319
Measure
Equipment
Cost
$557
Incremental
Equipment
Cost
Cost
Unit
$238 Dryer
75
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
Analysis
Measure ID Method
D03-941
Average
# Obs
40
Mean
$557
Median
$525
Base
Min
$261
Max
$869
# Obs
38
Mean
$319
Median
$296
Min
$224
Max
$509
76
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
77
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
78
Overview of Cost Data
Changes from 2001 to 2005
2005 Cost Spec
High-Efficiency Refrigerators Example
2001 Cost Spec
Energy Analysis Spec
Capacity
(cubic
feet)
Type
15.5
Top
Side
Botto
m
23
Top
Side
Botto
m
Capacity
(cubic
feet)
Type
Capacity
(cubic
feet)
Type
15.5
15
Top
Side
Top
Side
Bottom
20
Top
Side
Bottom
23
Top
Side
Bottom
25
Top
Side
Bottom
30
Top
Side
Bottom
20
Top
Side
25
Top
Side
30
Top
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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
80
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-$10 in
2002
• Compared to 2001 DEER, average CFL prices for low volume
purchases down by 29%; high volume down by 48%
81
Changes in Cost Data
Some Examples: CFL
Retail price spread for integral CFL lamps
Retail Price Spread of Integral CFL Lamps
Observed Retail Cost ($)
$25.00
$20.00
$15.00
Average
$10.00
$5.00
$0.00
7
9
11
13
14
15
16
18
19
20
23
25
26
28
32
36
50
Lamp Wattage
82
Cost Data
Collection 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
1.
2.
•
•
3.
4.
Organized by measure category
More details and measure variations
Cost Analysis Workbooks – most detailed
In hard copy in the final project report
83
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
84
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
85
Questions/Comments?
86
Guide to DEER and
Some Results
Website and Test Drive
Presenters:
Gary Cullen – Itron
Jeff Hirsch – JJ Hirsch & Associates
Floyd Keneipp – Summit Blue
87
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
88
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)
89
Website Navigation – Opening
Screen
90
Website Navigation – Browse
Measures
91
Website Navigation – Select
Subcategory
92
Website Navigation – Review
Summary Page - Top
93
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
94
Website Navigation – Review
Summary Page - Bottom
95
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
96
Website Navigation – Detailed
Measure Information
97
Website Navigation – Detailed
Measure information - Top
98
Website Navigation – Detailed
Measure information - Bottom
99
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
100
Supporting Documents Section –
Consolidated Measure Data
101
Questions/Comments?
102
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
103
Planning for DEER Updates
and Linkages to EM&V
Objectives
Approach
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
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
104
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
105
DEER Update Process
Most suggest DEER be preferred (default) source of
program planning data, some JS prefer mandatory
Comprehensively updated at least every three years
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
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
106
Savings Methods and
Calibration
Three primary methods:
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
Engineering calcs, building simulations, eval/field/lab data
RASS, CEUS, tracking and billing data, eval/field/lab data
Tradeoffs among accuracy, simplicity, transparency
107
Segmentation and Averaging
General/default approach - reflect market average
Extensive segmentation for weather sensitive
Program managers desire data for sub-segments
Less efficient portion of pop
Groups with specific characteristics
Inclusion of sub-segment data should be considered
Btype, vintage, CZ – 1,680 combos
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
108
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
109
Types of Data to Include
Interviewees asked which of following to include:
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 savings, peak savings, load shape, cost, effective
useful life (EUL), net to gross ratio (NTGR), penetration
and saturation information, potential study results
Energy & peak savings, load shapes (could be reduced
form), costs, EULs, market weights tied to segments
NTGR incorporation needs more consideration
110
Measure Coverage and
Allocation of Resources
DEER has never included all measures
Limited criteria-based allocation of resources
Small impact measures sometimes absorb
disproportionate resources
Future efforts should prioritize based on
Focus on prescriptive-type measures
Focus on prototypical measures
Scope/resource tradeoffs
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)
111
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
Importance of pre-measurement
(Pre-98 impact evals focused on program realization rates)
Some issues beg for controlled experiments
Integration between DEER and Protocols teams
DEER team need for direct access to eval data
112
Measure-Level Issues
Primary Sector
All
All
All
All
All
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Non-Residential
Non-Residential
Non-Residential
Non-Residential
Category
HVAC
Lighting
Lighting
Issue
Better Alignment Between EM&V Results and DEER Inputs
Better Characterization of Uncertainty Around DEER Estimates
Further Effort to Calibrate and Segment Base Consumption
Inclusion of Load Shape Data
Inclusion of Measure Packages/Interactions
High Efficiency Equipment - Energy and Peak Savings (EER/SEER issue)
Room A/C - Hours of Operation and Savings
Duct Sealing - Parameters and Savings
HVAC Practices - Parameters and Savings (e.g., refrigerant charging)
Programmable Thermostats - Behavior and Savings
Evaporative Coolers Impacts (including comfort)
CFL Average Hours of Operation
CFL Other Issues (e.g., in-service rates, base wattages, replacement, etc.)
Clothes Washers - Savings
Pool Pumps - Operation Hours, Wattages, and Savings
Documentation and Calibration of Equivalent Full Load Hours of Operation
Definitions and Baselines for AC and Chillers
CFL Average Hours of Operation (e.g., larger samples, more segments)
CFL Other Issues (e.g., screw-in vs. hard wired, re-install behavior/re-rebates)
Non-Residential
Non-Residential
Non-Residential
Lighting
Refrigeration
Motors
Other Non-residential Lighting Issues (e.g., EFLH by tech and segment)
Refrigeration - Savings & Costs (integration, expanded analysis)
Motors - Parameters and Base Case Assumptions (e.g., rewind vs. new motors)
Non-Residential
Non-Residential
All
Lighting
Custom Measure Savings and Costs (e.g., calculators, prototypical cases, eval)
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)
General
General
General
General
General
HVAC
HVAC
HVAC
HVAC
HVAC
HVAC
Lighting
Lighting
Appliances
Pool Pump
HVAC
113
Documentation
Strong desire for highly detailed documentation
Electronically-linked documentation also desired
Parameters, assumptions, and sources
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
114
Questions/Comments?
115