Honey, I’m Home - How Are Electricity Prices for Tomorrow? Lawrence Kotewa Project Manager, Community Energy Cooperative April 13, 2005 Community Energy Cooperative at the Center for Neighborhood Technology 2125 West North Avenue, Chicago, IL

Key characteristics of ESPP’s Real Time Pricing for Residential Customers  Unique consumer/utility partnership  Straight-forward program  Provides pricing and information  It’s low tech and low cost  People are saving money  People are changing behavior  People like it!

Purposes of Program  To incent efficient use of energy and reduction of peak demand  To provide benefit to small customers from deregulation  To provide options that can significantly reduce energy costs for households

The Conventional Wisdom: Why Retail Real-Time Pricing For Mass Market Customers Won’t Work  The market is too volatile and risky  There is no value for mass market consumers  The meters are too expensive  Mass market consumers won’t respond to price signals, are unable to manage risk and volatility and need to be protected ….Our experience to date runs counter to each of these

Community Energy Cooperative The Energy-Smart Pricing Plan SM

Community Energy Cooperative  Formed in 2000 by the Center for Neighborhood Technology  Supported by ComEd and other funders  The Cooperative has developed and managed a range of community- based demand reduction pilot programs

Energy Pricing  Rate RHEP: distribution charge plus variable energy charge based on wholesale prices  Models bundled rate/market rate differential in Illinois’ post-2006 environment  Day-ahead prices and RTO load shape used to create next day hourly prices  Cooperative created price cap at $0.50/kwh for energy

49,080 Hours Of Market Prices 89.5% of hours are below 5¢/kWh. Average Price is 2.51¢/kWh 98.5% of hours are below 10¢/kWh. Average Price is 2.86¢/kWh

Program Components  Interval recording meters  Prices available through web and phone  Energy management/price response tools  Information about usage  Instructions and tips on how to reduce usage during peak periods  Ongoing energy efficiency information  High price alerts via phone,

Web Access to Detailed Energy Use Data

Participant Demographics  750 participants in 2003; 1100 in 2004  A variety of air conditioning types:  40% Window air conditioning  40% Central air conditioning  20% No air conditioning  56% from the city of Chicago, rest suburban  10% speak Spanish  80% single-family homes and two-unit buildings  (average monthly use 658 kWh)  20% multi-family homes  (average monthly use 406 kWh)

Hourly Prices

One Member’s Response: Changing Thermostat Set Point In Response To Price Notification

Central Air Conditioner Users Respond To Price Alerts

Key Findings 1. Participants respond to peak period prices  Price elasticity of.042 across full range of prices  Over half of all participants showed significant response to high price notifications  Vast majority of participants showed some response  Aggregate demand reduction was as high as 25% during notification period  Over 80% of participants modified their AC use  Over 70% of participants reported modifying their clothes-washing patterns

Key Findings, cont. 2. Participants liked the program  Found it easy to understand and manage  82% said program was “quick and easy”  Participants were happy with the financial results of the program—average savings to date are approximately 12%  In addition to saving money, participants valued:  Bill control  Environmental impact  Greater understanding of energy use

Other Findings  Lower income participants were disproportionately represented in “high responder” group  Households with window ACs maintained their price-responsive behavior better across multiple high-priced hours  2004—overall price responsiveness increased; notification response reduced (likely due to weather effects)

Contrary to conventional wisdom--  Simple, understandable RTP program for residential customers is possible  Residential customers can and do respond to price signals.

For further information  Lawrence Kotewa, Project Manager 