measures that save the most energy
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Measures that Save The Most Energy. Jackie Berger David Carroll ACI New Jersey Home Performance Conference March 5, 2010. Session Outline. Introduction Measuring Energy Savings – Projections Measuring Energy Savings – Billing Data Average Savings by Type of Measure - PowerPoint PPT PresentationTRANSCRIPT
Measures that Save The Most Energy
Jackie BergerDavid Carroll
ACI New Jersey Home Performance ConferenceMarch 5, 2010
Session Outline
1. Introduction
2. Measuring Energy Savings – Projections
3. Measuring Energy Savings – Billing Data
4. Average Savings by Type of Measure
5. Energy Education Savings Potential
6. Maximizing Measure Savings
7. Conclusions2
Introduction - Perspective
• Evaluator’s Perspective• Based on findings from:
– Program design research– Survey research– In-field research– Energy impacts
3
Introduction - Scope
• Sources– APPRISE evaluation studies– Blasnik and Associates evaluation studies– Dalhoff and Associates evaluation studies– ECW plug load study
• Geographic scope– Northeast– Midwest– Mountain
4
MEASURING ENERGY SAVINGSProjections
5
Projected Savings vs. Measured Savings
• Value of projections
• Projection methodology
• Issues with projections
• Comparison of projected savings to measured savings
6
Projections vs. ImpactsData Needs
ProjectionsData
Driven Projections
Impacts
Installed measures No Yes Yes
Pre treatment usage No Yes Yes
Post treatment usage No No Yes
Degree days No No Yes
Comparison group No No Yes7
Projections vs. Impacts
• Basic Projection Methodology– Assumptions
• Measure installation rates
• Measure retention rates
• Pre installation usage
• Measure effectiveness
8
Projections vs. Impacts
• Basic Projection Methodology– Calculation
• Average household saving= Measure Installation Rate *
Measure Retention Rate *
(Pre Installation Usage – Post Installation Usage)
9
Projections vs. Impacts
• Basic Projection Methodology– Calculation
• Pre Installation Usage per bulb per hour= 60 watts * .001 = .06 kWh
• Post Installation Usage per bulb per hour= 13 watts * .001 = .013 kWh
• Change per Bulb per hour=.06 - .013 = .047 kWh
10
Projections vs. Impacts
• Basic Projection Methodology– Calculation
• Change per bulb per day= .047 kWh * 2.5 hours/day
= .1175 kWh/day
• Change per bulb per year= . 1175 kWh/day * 365 days
= 43 kWh/year
11
Projections vs. Impacts
• Basic Projection Methodology– Calculation
• Number installed per home= 43 kWh * 8 bulbs
= 344 kWh
• Retention rate= 344 kWh *.8
= 275 kWh saved per home per year
12
Projections vs. Impacts
So simple, what could go wrong…• Incorrect assumptions
– Measure installation rate
– Measure retention rate • Bulbs left for occupants to install
• Bulbs removed
• Bulbs broken
– Existing bulb kWh
– Hours of use
13
Projections vs. Impacts
So simple, what could go wrong…• Interactions
– Adding up individual measure savings can overstate results
– Need to account for reduced heat gain from CFLs• Increase heating usage
• Reduce cooling usage
14
Projections vs. Impacts
Survey Results
Annual kWh Savings by Hours Used
2.5 hr/day 1.5 hr/day
Bulbs provided (database) 15.4 660 396
Bulbs provided (client reported) 12.0 515 309
Number installed by auditor or client 11.6 497 298
Number not burned out or removed 10.6 455 273
(clients reported that 46% are used at least 1 hour per day)
15
Projections vs. Impacts
Impact Analysis Results
High Use Moderate Use
Projected Actual Projected Actual
kWh Savings per Bulb 76 41 72 26
kWh Savings per Home 1,231 677 878 316
Survey Results – High and Moderate UseMonths After Service Delivery
4-6 7-9 10-12 13-15 16-19
% Burned Out 6% 8% 9% 13% 17%
Source: M. Blasnik and Associates.
16
Projections vs. Impacts
How far are we off with the projections?• Evaluations that measure actual usage impacts
usually find 50% to 70% of projected savings– NEAT Audit – measured savings were 57% and 54% of
projected savings (Sharp, 1994 and Dalhoff, 1997)– Ohio electric baseload savings were 58% to 68% of
projected– NJ electric baseload savings were 60% - 69% of
projected
Source: M. Blasnik and Associates.
17
MEASURING ENERGY SAVINGSBilling Data
18
Average Savings by Measure Type• Methodology for developing measured savings• Methodology for attribution of savings to measures• Evaluation findings – electric baseload• Evaluation findings – space heating measures
19
Usage Impact Analysis
• Usage Impact Methodology– Obtain pre and post energy usage data for
program participants– Use regression model to adjust usage for
changes in weather from “normal weather year”– Construct weather normalized change in usage
for treated households– Construct weather normalized change in usage
for comparison households
20
Usage Impact Analysis
• Usage Impact Methodology– Run regression to determine measure specific
impacts
Usage change = α + β * household characteristics + γ1* measure1 + γ2* measure2 + γ3* measure3 + μ
21
Measure Savings – Evaluation Findings
kWh Savings Per MeasureOhio EPP1 PPL WRAP1
NJ CP1 CO E$P1
PECO LIURP2High
UseMod Use
BaseloadFull Cost
CFL 41 26 40 47
Refrigerator 926 544 777 532 912 692 949
Freezer 760
Air conditioner 172
1M. Blasnik and Associates.2APPRISE. 22
Measure Savings – Evaluation Findings
$ Cost per kWh Savings By Measure
NJ CP
CFL $0.061
Refrigerator $0.069
Source: M. Blasnik and Associates.23
Measure Savings – Evaluation Findings
CCF Savings Per MeasureNJ CP CO E$P IL WAP OH WAP IA WAP
Heater Replacement
85 114 146 117
Attic insulation
85 110 92 148 65
Air sealing 24 70-108 53
Thermostat 41
Source: M. Blasnik and Associates.24
Measure Savings – Evaluation Findings
$ Cost Per CCF Saved By Measure
NJ CP1 CO E$P1 PECO2
Heater Replacement $1.30 $1.90
Attic insulation $0.60 $0.20 $1.28
Air sealing $1.23
Thermostat $0.19
1M. Blasnik and Associates2APPRISE 25
ENERGY EDUCATIONPotential Savings
26
Potential for Education
• Major opportunities
• Potential vs. realization
• Successful models
27
Potential Education Savings
Wattage Reduction Number Savings
Electric Measures kWh
Turn off lights 60 4 hrs/day 4 350
Turn off lights at night 60 8 hrs/day 2 350
Reduce central AC 3º All times 250
Reduce TV usage 100 4 hrs/day 2 292
Turn off computer 250 8 hrs/day 1 730
Gas Measures Therms
Turn down water temperature 10° All times 25
Turn down thermostat 2° All times 84
Use cold water for clothes washing Cold wash 4/week 52
Set back temperature at night 4º Night 58AC – 72 to 75 degrees, heating 72 to 70 degrees
28
ECW Plug Load Study
• Telephone survey and mailed appliance survey• 50 site visits
– Household survey– Electronics inventory– Metering (5-30 appliances per home)
• Metered for one month
• 6-minute intervals
• Computers, televisions, audio, telephone, • HVAC – space heaters, dehumidifiers, room AC, fans,
humidifiers• Kitchen appliances
29
ECW Plug Load StudyPotential Education Savings
Computers
Potential Savings from Full Power Management
% of homesEstimated
Annual Savings
Always on 20% 400
Long idle periods 40% 190
Off when not in use 25% 15
Not used much 15% 2
Average savings 160
30
ECW Plug Load Study Potential Education Savings
Wattage When
Not in UseAnnual kWh Savings if
Unplugged When Not in Use
Mini Stereos 23 200
Older TVs 7 58
Printers 6 43
DVD/VCR Player 7 59
31
ECW Plug Load StudyPotential Education Savings
• Saving Strategies– Power management
– Unplug
– Turn off
– Use timer
– Use power strip
• Assessment– Potential savings
– Motivation
32
Education Impacts
Ohio EPP Unprompted
Agreed to Taken
Turn off lights 54% 16%
Turn off appliances 14% 3%
Use CFLs 10% 5%
Conserve energy 10% 2%
Use double spin on clothes washer 9% 2%
Reduce heating temperature 5% 1%
Line dry clothes 4% 0%
Reduce water heater temperature 3% 1%
Wash clothes in cold water 1% 1%
None 19% 19% 33
Education Impacts
Niagara Mohawk Unprompted
Actions Taken As a Result of:
Workshop VideoIn-Home Education
Turn off lights 43% 40% 33%
Install CFLs 27% 20% 24%
Turn down thermostat 14% 15% 10%
Reduce TV usage 11% 3% 6%
Turn off appliances 11% 9% 9%
Turn down water temperature 10% 12% 10%
Reduce use of AC 9% 3% 6%
Use cold water for clothes washing 9% 5% 6%
Set back temperature at night/when out 5% 4% 2% 34
Behavioral Impacts
35
Reduced use of _____ as a result of participating in the program?
Obs.Mean Electric Savings (kWh)
All Customers 233 854
Electric space heater**yes 105 1150no 128 611
Air conditioneryes 136 947no 97 723
Electric dryeryes 71 995no 162 792
Dehumidifieryes 18 1058no 215 837
Number of lights left on all night*yes 43 1174
no 190 781
Recap
• Projected savings tend to overestimate
• Billing data are critical
• Potential for savings from education
36
Maximizing Savings
• Programs that save the most:
– Target measures to the highest use households
– Install measures in a way that maximizes effectiveness
– With an understanding of what is going on in this house
37
Targeting
Usage (ccf) Spending Savings $ per ccf saved
<1,000 $653 26 ccf $25
1,000-1,400 $836 80 ccf $10
1,400+ $1,043 171 ccf $6
38
Targeting
kWh Savings Per MeasureOhio EPP1 PPL WRAP1
NJ CP1 CO E$P1
PECO LIURP2High
UseMod Use
BaseloadFull Cost
CFL 41 26 40 47
Refrigerator 926 544 777 532 912 692 949
Freezer 760
Air conditioner 172
1M. Blasnik and Associates.2APPRISE. 39
Measure Effectiveness
• Duct Sealing– Ducts outside envelope = High Savings– Ducts inside envelope = Low/No Savings– Ducts in basement or crawl space = It Depends
• Insulation– With properly sealed envelope = High Savings– Without air sealing = Low Savings
40
Focus on This House
• Example – Baseload Job in Massachusetts House– Pre-visit Information: Annual electric usage of 10,000
kWh
– On-Site Measurement: 6,000 kWh for appliances / 4,000 kWh for space heater
– Problem: Program only pays for baseload measures
– Solution: Install cfls, encourage behavioral changes, and refer to electric heat program
41
Maximizing Savings
• Programs that save the most per dollar spent:
– Spend lots more when there are more opportunities
– Spend substantially less when there are fewer opportunities
42
Targeting
Usage (ccf) Spending Savings $ per ccf saved
<1,000 $653 26 ccf $25
1,000-1,400 $836 80 ccf $10
1,400+ $1,043 171 ccf $6
43
Maximizing Savings
• Programs that save the most per dollar spent:
– Conduct tests to focus resources and time
– Use models as a guide for action
44
Testing
• Field inspections of New Jersey programs found that better testing was needed to …
– Find and isolate sources of infiltration in complex structures (enclosed porch, addition, sun room)
– Identify unobservable leaks in ductwork outside the thermal envelope
45
Testing
• Blasnik refrigerator study found that testing is needed, but more is not necessarily better …– Low Savings / Net Benefits
• Rating Protocol = $101
• 1 Hour Metering = $111
• 2 Week Metering = $135
– High Savings / Net Benefits• Rating Protocol = $419
• 1 Hour Metering = $414
• 2 Week Metering = $445
46
Audit Tools / Modeling
• Benefits– Clarify decision rules on measure installation– Improve consistency across program
• Barriers– Data entry can be a communications barrier– Reconciliation is poorly understood
47
Financial Decision Rules
• Spending Limits– Do they focus delivery on highest saving measures or
restrict delivery of cost-effective measures?
• Spending Goals– Do they ensure comprehensiveness or encourage a
program to over-invest?
• Spending Targets– Do they furnish flexibility or result in over-investment
in some homes and under-investment in others?
48
Recommendations
• Usage Data – Essential for good decision-making
• Decision Criteria - Field staff need a good tool for determining which measures to install
• Financial Guidelines – Should vary with energy savings potential and should be expressed as a range
49
Contact Information
• Jackie Berger, 609-252-8009, [email protected]
• David Carroll, 609-252-8010, [email protected]
50