Energy Behavior – Lessons from Low-Income Education Programs

David Carroll, Jackie Berger

ACEEE Summer Study on Energy Efficiency in Buildings

August 20, 2008

Session Outline

• Introduction

• Savings Potential

• Coaching Models

• Technology Assisted Models

• Low Cost Models

• Feedback Models

• Summary and Recommendations

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Introduction

• Potential – Can households change energy using behaviors and save energy over the long run?

• Mechanism – What change in knowledge, motivation, and feedback results in savings?

• Evidence – What types of programs have led to documented savings?

• Inference – What can we infer about the change mechanisms from the evidence?

• Limitations – How can we overcome our ignorance?3

Potential – Crisis

• 2000/2001 California Experience– Electric Crisis / Public Information Campaign

– 10% Reduction in Peak Demand / 7% Reduction in Usage

• 2001 RECS / 1997 RECS– 25% Gas Price Increase

– 16% Gas Usage Reduction

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Potential – Willingness• Heating Setback

– 51% Take Action / 14% Willing

• CFLS– 22% Take Action /53% Willing

• Cold Water Wash– 38% Take Action / 11% Willing

1996 NMPC LIHEAP Recipient Study5

Mechanism

• Models – Plentiful

• Small Scale Studies - Available

• Significant Research - ?????

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Program Models

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Coaching Example

• 1992 NPMC Power Partnerships Pilot– Alliance to Save Energy

– Experimental Design

– In-Home Energy Education / 3 Sessions

• Results– Control Group = -37 Therms

– WX Only = 304 Therms (16%)

– WX and Education = 445 Therms (26%)

• Incremental Service Delivery Costs = $500

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Coaching Inference

• H1- Experienced professional could improve on decisions made by WX service delivery personnel.

• H2 – Interaction between “educator” and client helped to identify additional opportunities

• H3 – 6-month follow-up visit identified WX problems and led to resolution.

• H4 – Client was better able to manage gas using systems in a way that saved energy.

Follow-Up Survey – Warmer, less drafty, healthier9

Coaching Extensions

• HPwES Add-On – “Coach” can potentially increase savings, resolve problems, increase client satisfaction

• HPwES Alternative - Next step after completing computer-based audit

• Point of Sale Consultant – Negotiate discount / plan upgrade strategy

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Technology Example

• Ohio Electric Partnership Program– Targeted High Users

– Used SMOC-ERS Software

– Trained Service Delivery Staff in Education Techniques

• Results– High Refrigerator / CFL Replacement Rate

– Cost Effective kWh Savings

– No Direct Measurement of Education Savings Possible

– Low Level of Reported Energy Saving Actions

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Technology Inference

• Goal– Technology Facilitates Diagnosis

– Information is Personalized

– Clients are Focused and Motivated

• Observations– Technology Can Disrupt Interaction

– Usage Pattern May Defy Explanation

– Lack of Follow-Up Limits Usefulness

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Technology Extension

• Computerized Audit – Linkage to bills / “where you stand” assessment

• Feedback Devices – High user diagnosis

• Demand Response – Management of usage subject to preferences

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Technology Limitations

• Feedback Device Issues– Time

– Motivation

– Knowledge

– Florida Solar Energy Study (2008)

• Bill Disaggregation Issues– Unpredictable Events

– Coincident Uses

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Low Cost Example

• Colorado First Response / Four Program Models

– Direct Install

– One-On-One / Education / Kit Delivery

– Direct Mail / Kit Delivery

– Business Reply Card / Direct Mail / Kit Delivery

• Results

– DI: Savings From Measures / Limited Behavior Change

– One-On-One: Savings ??? / Significant Behavior Change

– Direct Mail: Low Savings / Limited Behavior Change

– BRC: High Savings / Moderate Behavior Change

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Low Cost Inference

• One-On-One– Surprising Level of “Reported” Behavior Change

– Savings Results ???

– Limited Version of “Coaching” Model / Trusted Advisor

• BRC– Importance of Motivation

– Quality of Materials

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Follow-Up Example

• PECO LIURP

– Audit / Education Session

– Service Delivery

– Monthly Mailing

– Periodic Review / Feedback / Problem Resolution

• Results

– 600+ kWh of Saving Attributed to Education

– Significant Level of Report Energy Saving Actions

– Reported Actions Correlated with Savings

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Follow-Up Inference

• H1 – Experienced auditor / educator is effective.

• H2 – Review/Feedback resolves usage problems.

• H3 – Monthly newsletter reinforces client understanding / motivates client action.

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Low Cost/Follow-UpExtensions

• Energy Tip on Utility Bill Envelope

• Trusted Advisor???

• Other Ideas???

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Lessons• Individuals can be informed and motivated to change

energy using behaviors

• There are promising models that need additional testing and assessment

• Personal interaction and feedback seem to have the greatest impact

• For self-motivated households, even simple measures lead to savings

• Technology has limits / needs more work

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Recommendations

• If you want to achieve cost-effective savings existing models are available to deliver those benefits.

• If you want to maximize savings by changing energy behaviors, you need to design assessment and testing protocols that test models and lead to a better understanding of outcomes.

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Contact Information

David Carroll

APPRISE

32 Nassau Street, Suite 200

Princeton, NJ 08542

609-252-8010

david-carroll@appriseinc.org

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