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 2

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 4

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 Study 5

Mechanism Models – Plentiful Small Scale Studies - Available Significant Research - ????? 6

Program Models 7

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 8

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, healthier 9

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 10

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 11

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 12

Technology Extension Computerized Audit – Linkage to bills / “where you stand” assessment Feedback Devices – High user diagnosis Demand Response – Management of usage subject to preferences 13

Technology Limitations Feedback Device Issues –Time –Motivation –Knowledge –Florida Solar Energy Study (2008) Bill Disaggregation Issues –Unpredictable Events –Coincident Uses 14

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 15

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 16

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 17

Follow-Up Inference H1 – Experienced auditor / educator is effective. H2 – Review/Feedback resolves usage problems. H3 – Monthly newsletter reinforces client understanding / motivates client action. 18

Low Cost/Follow-Up Extensions Energy Tip on Utility Bill Envelope Trusted Advisor??? Other Ideas??? 19

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 20

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. 21

Contact Information David Carroll APPRISE 32 Nassau Street, Suite 200 Princeton, NJ