Energy Behavior – Lessons from Low-Income Education Programs

1. Energy Behavior – Lessons from Low-Income Education Programs David Carroll, Jackie Berger ACEEE Summer Study on Energy Efficiency in Buildings August 20, 2008

2. Session Outline • Introduction • Savings Potential • Coaching Models • Technology Assisted Models • Low Cost Models • Feedback Models • Summary and Recommendations 2

3. 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

4. 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

5. 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

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

7. Program Models 7

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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

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

15. 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

16. 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

17. 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

18. 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

19. Low Cost/Follow-UpExtensions • Energy Tip on Utility Bill Envelope • Trusted Advisor??? • Other Ideas??? 19

20. 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

21. 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

22. Contact Information David Carroll APPRISE 32 Nassau Street, Suite 200 Princeton, NJ 08542 609-252-8010 david-carroll@appriseinc.org 22