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Rain or shine: Behavioral Efficiency with a 100% chance of savings
Lauren MacMillan, OpowerKerry Kaseman, Otter Tail Power Company
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Agenda
1. Behavioral Science & Home Energy Reports2. Measuring & Forecasting Savings3. Otter Tail Case Study4. Other Cool Findings
1. Behavioral Science & Home Energy Reports
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Opower today
3
The Company• Software as a Service Customer
Engagement Platform
• Serving 90+ utilities in 8 countries• Over 4TWh saved to date
• 40% of US household data under management totaling 300 billion reads
• 500 people in Washington, San Francisco, London, Singapore, Tokyo
Our DNA• Behavioral Science
• Data Science
• Computer Science
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Conservation messages printed on door hangers and left on homes
Applied Behavioral Science
Schultz & Cialdini (OPOWER Scientists)Hewlett Foundation San Marcos Study
$$$
Turn off AC &Turn on Fan
Environment
Turn off AC &Turn on Fan
Citizenship
Turn off AC &Turn on Fan
Zero Impact on Consumption
Neighbors
Turn off AC &Turn on Fan
6% Drop inConsumption
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People care about what other people are doing
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6
Energy Efficiency TipsNormative Comparison
Home Energy ReportApplied behavioral science, delivered
Historical ComparisonNeighbor Rank
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1. Behavioral Science & Home Energy Reports2. Measuring & Forecasting Savings3. Otter Tail Case Study4. Other Cool Findings
Agenda
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Randomized Control Trials Allow Opower To Measure Savings
Random Allocation
Control Group
Test Group
Statistically equivalent
groups
+
ReceiveReports
No Reports+
Targeted households
in utility footprint
Outcome
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Opower Programs Ramp Over Time
Savings ramp over first 1-12 months
Typical Savings Curve Associated with Opower Program
Steady state savings after 12-18
months
Savings impacted by report delivery &
seasonality
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0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
4.0%
4.5%
5.0%
Savi
ngs
of th
e Te
st G
roup
Rel
ativ
e to
Con
trol
Gro
up
Average Steady State Savings = 1.5 – 2.5%
Months since program start
Results From Hundreds of Programs Have Been Measured & Verified
6 12 18 24 30 36 42
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-
1,000
2,000
3,000
4,000
5,000
6,000
7,000
Opower Has Complied A Large Dataset of Program ResultsCumulative ObservationsProgram Months
2008 2010 2012 2014
>500 program years of results
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Process For Predicting Future Savings
Measure results monthly to generate data set
Correlate savings to program characteristics
Fit program characteristics to forecast model
1
2
3
Semi-Annually
Monthly
Just completed our last model update in January
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What have we learned about the factors that best predict savings?
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There Are Several Factors That Help Us Predict Future Program Savings
• Number of reports• Report cadence
• State’s Regulatory Environment
• Utility type
• Energy Consumption
Customer Utility Program
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Predictability of Savings Is Important For Utilities
Installed Measure SavingsCustomers x Deemed Savings
Opower Program SavingsCustomers x Usage x Savings
Rate
Deemed Savings are reliable & predictable
Forecasting Reduces Uncertainty Around Savings Rates
Opt-Out nature means known, large number of customers
Opt-In nature means number of customers is unknown
Savings rates & usage are unknown
Pros:
Cons:
Pros:
Cons:
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Agenda
1. Behavioral Science & Home Energy Reports2. Measuring & Forecasting Savings3. Otter Tail Case Study4. Other Cool Findings
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Partial Solution: Research measurable energy savings from behavioral change programs.
Otter Tail Power Company & OpowerBackground: The Next Generation Energy Act (NGEA), passed in 2007, prioritized energy efficiency in Minnesota, even creating an incentive structure to encourage utilities to help their customers save energy.
Dilemma: Otter Tail was looking for a cost-effective EE program to add to their portfolio to increase savings and contribute to their 2011-2013 filed goal
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0.00%
0.50%
1.00%
1.50%
2.00%
2.50%
3.00%
Savi
ngs
of th
e Te
st G
roup
Rel
ativ
e to
C
ontr
ol G
roup
Opower Program Achieved 1.5% Savings Over The Last 2 Years
Average Savings of 1.5%
Program Impact: Overall
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Minnesota Requires Utilities to Cut Energy Savings by 1/3»Minnesota utilities can only claim 1/3 of the savings
achieved in behavioral programs towards goals
»Regulators and environmental groups concerned about sustainability of savings
»Ruling is impacting programs and goals
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Past Performance Used To Estimate Savings filed for 2014-2016
Otter Tail filed Opower savings goal of ~1,600
MWh per year from 2014-2016, ~5% of filed total kwh goal
Program Impact:MWh Savings By Year, Actual & Forecasted
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Million Dollar Questions
»How do utilities forecast long-term savings from behavioral change?
»How should utilities forecast long-term savings from behavioral change?
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Agenda
1. Behavioral Science & Home Energy Reports2. Measuring & Forecasting Savings3. Otter Tail Case Study4. Other Cool Findings
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0%
20%
40%
60%
80%
100%
120%
140%
160%
180%
200%
12:00 a.m. 4:00 a.m. 8:00 a.m. 12:00 p.m. 4:00 p.m. 8:00 p.m.
Peak Time Savings
Peak Increase
Savings Relative To Average Program SavingsIndexed, Average = 100%
How do savings change by time of day or month of year?
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0%
50%
100%
150%
200%
250%
12:00 a.m. 4:00 a.m. 8:00 a.m. 12:00 p.m. 4:00 p.m. 8:00 p.m.
Peak Savings are Consistent Across Utilities
Average savings curve
A reliable source that may be included in cost effectiveness calcs as avoided capacity
The same shape is seen across savings curves in many groups & climate typesSavings Relative To Average Program SavingsIndexed, Average = 100%
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Thank You
Kerry KasemanSenior Resource [email protected]
Lauren MacMillanAnalytics [email protected]