Engineering Systems Division: The Energy Box

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Engineering Systems Division: The Energy Box

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Title: Engineering Systems Division: The Energy Box


1
Engineering Systems Division The Energy Box
  • Integrating Energy Efficiency and Consumer
    Behavior into the Energy Box Design
  • by
  • Kat Donnelly, PE
  • June 3, 2008
  • kdonnell_at_mit.edu
  • Presentation for the House-n event Energy
    Behavior Change Low-Energy Homes

2
Energy Efficiency (1970s) Dan Yergin Amory
Lovins
  • With serious commitment
  • Could consume 40 less
  • Quality energy source
  • Stimulates employment, innovation, environment,
    economy
  • cheapest, safest, most
    productive alternative
  • readily available in large amounts

Slide 2
Kat Donnelly, PE kdonnell_at_mit.edu May 20, 2008
Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
Slide 2
3
Energy Efficiency (1970s) Dan Yergin Amory
Lovins
  • Does not
  • threaten international monetary system
  • emit much carbon dioxide
  • generate waste problems like nuclear
  • cause Geopolitical issues

http//www.oiladdict.com/icons/bookcover_home.jpg
Slide 3
Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
4
Yet EE is lagging. Why? Policy
http//www.epa.gov/solar/energy-programs/state-and
-local/efficiency_actions.html
Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
Slide 4
5
Yet EE is lagging. Why? Market Economics
  • Externalities (oil priced well below social
    costs) 15 to 50/bbl
  • Military/security
    diplomatic/geopolitical
  • Climate
  • Other environmental
  • Oil subsidies
  • Bad price signals
  • Little real/time, time-of-use pricing
  • Little monitoring/feedback to customer

http//www.treehugger.com/cars-piled-up.jpg
Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
6
Traditional Economics Assumptions
  • Agents
  • Are rational,
  • controlled,
  • informed,
  • selfish, and
  • calculating
  • Preferences are known, stable, and ordered
  • Maximize their welfare
  • Market conditions optimal

http//www.carbon-cutters.com/Energy_Security.htm
Slide 6
Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
7
Yet, EE is lagging. Why? Behavioral Economics
  • People do not maximize welfare
  • Follow suboptimal decision strategies
  • Have very high implicit discount rate (/
    60/year) high time value of money, short-term
    view!
  • Information asymmetries--lack good information on
    end-use efficiency alternatives

http//www.inhabitat.com/wp-content/uploads/_dl09.
jpg
Slide 7
Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
8
Do people know their preferences?
  • Initial and relative positions/situations
  • Affects perception of possible outcomes
  • Inhibits rational energy consumption
  • Psychological value function. People
    are
  • Risk adverse for potential gains
  • Risk seeking for potential losses
  • Which means,
  • Emphasize losses in marketing campaigns
  • Use strategies with biggest impacts
  • Reference Points Matter
    (set them effectively)

Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
9
Effective EE Strategies Goal Setting and
Commitment
  • Increases motivation, commitment, direction
  • Increases adoption of
    sustainable behaviors
  • See progress
    progress
    needed
  • Develop new
    strategies
  • Assess goals

Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
10
CommitmentGoal Setting
Total Goal (X.XX, X.XX kWh) Resets Daily or
Monthly
140.00 1000.000 kWh
(Cumulative Counter)
Halfway through time period (daily/monthly),
electricity pace should be half of the
goal Example expected electricity use as of May
14 relative to May goal
Counter
Real-time Consumption Gauge (kW)
Pace percent relative to expected electricity
use Projection expected end-of-month
electricity use given current pace
Zero
Goal Tracker (Resets Daily or Monthly)
Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
Slide 10
11
Effective EE Policy Feedback
  • 1. Learning better understand how behavior
    influences energy usage
  • 2. Forming habits
    new knowledge alters

    activities and causes a
    routine change
  • 3. Internalization of behavior new
    habits change attitudes to suit
    new behaviors.

http//i181.photobucket.com/albums/x176/weirdscien
ce_photos/powercord_glow.jpg
Slide 11
Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
12
Use Technology ToDrive Behaviors
  • Rational decision making shaped by
  • 1. Abundance of raw data
  • 2. Dearth of meaningful information
  • Behavior and technology are closely interwoven
    throughout life
  • Role of technology receives surprisingly modest
    attention in psychology and in policy making.
    (2007, Midden, C.)

http//fivepercent.us/images/electricity-use-sm.pn
g
Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
Slide 12
13
The Energy Box What Is It?
  • Home computer running specially-developed
    software especially intended to achieve peak load
    shaving
  • controlling a combination of hardware that makes
    it possible to turn appliances on or off
    according to supply conditions
  • Users can download and install (or write their
    own!)
  • software onto their home computer
  • different algorithms for different appliances
  • Future migration to a Web-browser interface
  • Can also be a stand-alone display in the house

Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
Slide 13
14
Developing an Energy BoxA Systems Solution to
Energy Efficiency
  • Address weakness in Consumer Behavior literature
  • Achieve energy efficiency behavior change

ESD 2007
15
Beyond Smart MeteringBehavioral aspects
  • Consider consumer comfort and preferences
  • Change attitudes (environmental, economic,
    geopolitical)
  • Modify consumption patterns
  • Take advantage of social marketing

Slide 15
  • From Filipe Rodrigues, IST, MIT-Portugal Program

Kat Donnelly, PE kdonnell_at_mit.edu May 20, 2008
16
Communication with the Consumer (Supply, Personal
consumption characteristics)
The Enabling TechnologyMeter Prototype Design
Source MIT Design Contest,
RPI Electronics Club Team Submittal
Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
Slide 16
17
Upgrading the Technology Processing on-board
Source Dane Kouttron,
Project Update May 27, 2008
Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
Slide 17
18
Upgrading the Technology Disaggregating the
signal
Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
Source Dane Kouttron,
Project Update May 27, 2008
Slide 18
19
Future Study Consumer Behavior Surveys
(forthcoming)
  • Consumer Behavior Surveys Learn the
    attitude/behavior/intention relationship
  • Demographic variables, dwelling and energy use
    characteristics
  • Energy price and usage knowledge
  • Attitudes toward energy scarcity, energy
    conservation, energy efficiency, sustainability,
    mandatory or voluntary conservation
  • What kinds of things can people do to save energy?

http//www.concord.org/btinker/guide/footprint/in
dex.html
Slide 19
Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
20
Future Study Consumer Behavior Experiments
(forthcoming)
Slide 20
Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
21
Future Study Consumer Behavior Experiments
(forthcoming)
Social networking Establish personal
sustainability identification
Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
Slide 21
22
My Research Expected Contribution
  • Low-hanging fruit
  • Achieve 10 reduction in home energy use for
    pilot group
  • Develop detailed user interface to influence
    consumer behavior
  • detailed application of behavioral principles to
    energy conservation
  • Barrier busting of current information
    asymmetries
  • Develop supportive pricing and technology policy
    recommendations

Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
Slide 22
23
References
  • Ariely, Dan. (Fall 2007). Consumer Behavior Class
    Lectures and Predictably Irrational (2008).
  • Bagozzi, R. P. (1999). Utpal Dholakia, Goal
    Setting and Goal Striving in Consumer Behavior.
    Journal of Marketing, Vol. 63, Fundamental Issues
    and Directions for Marketing, 19-32.
  • Bazerman, M. H. (1992). Neale, M.A.,
    Introduction to Rational Thinking in Negotiation,
    Part 1 Common Mistakes in Negotiation. In
    Negotiating Rationally (pp. 1-64). New York The
    Free Press.
  • Darby, Sarah. (2006). "The Effectiveness of
    Feedback on Energy Consumption A review for
    DEFRA of the Literature on Metering, Billing, and
    Direct Displays." Environmental Change Institute,
    University of Oxford.
  • Diamond, P. (Ed.). (2007). Vartiainen, Hannu,
    Behavioral economics and its applications,
    Princeton, N.J Princeton University Press.
  • Ester, P. (1985). Consumer Behavior and Energy
    Conservation. Dordrecht, The Netherlands,
    Martinus Nijhoff Publishers.
  • Houwelingen, J. H. v. (1989). W. Fred van Raaij,
    The Effect of Goal-Setting and Daily Electronic
    Feedback on In-Home Energy Use. The Journal of
    Consumer Research, 16(1), 98-105.
  • Katzev, R., and Johnson, Theodore (1987).
    Promoting Energy Conservation An Analysis of
    Behavioral Research. Boulder, CO, Westview Press.
  • Kelly, S. (2006). Customer Intelligence From
    Data to Dialogue. Chichester, West Sussex,
    England John Wiley and Sons.
  • Lovins, A. (2007). Energy Efficiency Concepts
    and Practices Implementation Lecture, March 29,
    2007, Stanford University. (from iTunesU)
  • Midden, C. J. H. (2007). Florian G. Kaiser, and
    L. Teddy McCalley, Technologys Four Roles in
    Understanding Individuals Conservation of
    Natural Resources, Eindhoven University of
    Technology. Journal of Social Issues, 63(1),
    155-174.
  • Sheehy, L. (2003). Dingle, P., Goal Setting,
    Education, and Sustainability Living Smart in
    the City of Fremantle University of Australia.
  • Yergin, D. Conservation The key energy source,
    In R. Stobaugh D. Yergin (Eds.) Energy future
    Report of the Energy Project at the Harvard
    Business School. New York Random House, 1979

Kat Donnelly, PE kdonnell_at_mit.edu June 3, 2008
24
Policy and Behavior Interventions
Slide 4
Kat Donnelly, PE kdonnell_at_mit.edu May 20, 2008
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