Customer-Friendly Demand Response

1. Customer-Friendly Demand Response Chris King Chief Strategy Officer, eMeter Chair, SVLG Demand Response Subcommittee

2. Who’s eMeter? Company Background & Qualifications Founded in Silicon Valley in 1999 by original executive group from CellNet Team pioneered advanced metering infrastructure technology Develop and sell Advanced Meter Information Systems (AMIS) software Advanced Metering Business Process Management (BPM) Meter Data Management AMI Integration Platform Experience in all aspects of AMI implementation AMI technologies, Software implementation, Data collection and management, Deployment & operations, Business and regulatory strategy Business Focus Software & professional services Strategic consulting on AMI issues

3. Why is Demand Response Important? • Price-based • Tool for customers to manage bills • Keeps wholesale prices in check • Reliability • Protects the grid • Prevents rolling blackouts Case Study 1: Loss of 1,000 MW Power Plant

4. Main Job of Customers is Not Energy Source: Primen

5. Even Facility Managers Spend Little Time on Energy Source: Primen

6. Customers & Utilities Don’t Speak the Same Language Source: Primen

7. Primary Customer Energy Concerns Source: Primen

8. Tools That Help With Pricing Source: Primen

9. Market Research – Commercial Customer Concerns • Statements regarding energy efficiency investments Source: Quantum Research

10. Commercial Pricing Preferences Source: NYSERDA

11. What is DR: Price-Based vs. Reliability Programs • Price-based • Goal is to provide price signal • Demand reductions occur via voluntary end-use customer response • Reductions are included in load forecasts • Response levels become more predictable as a function of: • Transparency/foreknowledge of prices • Weather • Experience • Diversity (number and types of customers) • Examples: critical peak pricing, real-time pricing

12. What is DR: Price-Based vs. Reliability Programs • Emergency/reliability • Goal is “load acting as a resource” • Demand reductions occur via dispatch by system operators • Reductions are included in resource/supply portfolio • Same as a power plant (with limitations) • Response levels more variable • Minimal foreknowledge by end-use customers • Dispatch reasons varied • Less diversity in loads involved • Examples: interruptible programs or demand bidding programs with penalties

13. Customer-Friendly Demand Response • Principles developed by SLVG (subset) • Voluntary • Default programs must have no penalty for “opting-out” • PUC ruling on critical peak pricing for large commercial customers adopted SVLG’s principle • Easy to participate • Minimize complex forms and procedures • Avoid specific peak reduction targets (e.g. minimum of 100 kilowatts) • Easy to understand • Maintain stable programs over time • Easy to reduce demand • Promote availability of automation technology through incentives and rebates • Good value • Customers should be fairly rewarded for their efforts • The benefits should be maximized relative to the cost

14. Case Study 2: CPUC Ruling on Critical Peak Pricing • Decision in spring 2006 • Requires utilities to implement “default” critical peak pricing for customers above 200 kW • Decision does not say when • Decision says the rate design will be covered in a “future” rate case • Unlikely to see anything before the summer of 2008 • Customer-friendly features • Promoted by SVLG in the proceeding • Adopted in decision • Key customer protections • CPP is to be voluntary, meaning customers can opt-out with zero penalty to their current time-of-use rate • Opting out must be very easy – no more than a phone call or email • Customers have bill protection for their first year • Can pay no more on the CPP price than the TOU • Customers must be fully informed as to the likely bill effects

15. Critical Peak Pricing: What is it? Critical Peak (12-6 pm) Critical Peak Notification to Customer (by 5 p.m.) Peak (12-6 pm) Off-Peak

16. Case Study 3: Two-Part Real-Time Pricing • Georgia Power Company • Very high participation • 1,700 customers (80% of those eligible) • > 5,000 MW peak load; 500 to 1,000 MW peak reduction • Voluntary • Day-ahead (75%) and hour-ahead (25%) hourly pricing • Prices based on wholesale market with adjustments • Features • Customer pays for baseline level of usage at standard tariff prices • Deviations from baseline – increases or decreases – billed at RTP price

17. Two-part RTP Example Customer “sells” load at high RTP prices kW Baseline Customer “buys” load at low RTP prices Actual load 1 24 Hour of Day Source: Christensen Associates

18. Reference Load Load at moderate prices Load at highest prices Highest prices Moderate prices Reference prices Load Response, by Price Day-type Source: Christensen Associates

19. Elasticity is the amount load is reduced when the on-peak price is doubled Price Elasticities: Commercial Office Buildings Source: Christensen Associates

20. Price Response Curve • Utility able to predict response accurately based on price level, using historical data Source: Christensen Associates

21. Case Study 4: Anaheim Peak Time Rebate • Program concept • Identify critical peak days a day in advance based on forecast high temperatures in Anaheim • Notify customers a day in advance via automated telephone and, if desired, email • Customers reduce consumption between noon and 6 p.m. on critical peak days • Reduction is recorded via hourly meters and the data sent back after midnight • Customers receive a rebate of $0.35 per kWh for each kWh below their “baseline” usage on the event day (what they normally would have used from noon to 6 p.m.) • Program benefits • Provide customers with choices • Realize bill savings by curtailing peak demand during the top 50 to 100 hours per year (“critical” peaks) • Reduce utility cost to serve • Lower peak capacity needs in the long run once programs are in place, tested, and shown to deliver reliable load reductions

22. Peak-Time Rebate • Establish customer baseline • Three highest of previous 10 non-event weekdays • Rebate is reduction times the price (30 cents per kWh rebate) • No risk to customer • No need to meet specific reduction targets Peak reduction Peak hours kW 1 12 24 Hour of Day

23. Program Operations • Experimental sample provided with meters • Sample designed by Professor Frank Wolak of Stanford University • Recruitment • Recruitment via direct mail • No incentive payment • Customer education • Customers sent fact sheets and a refrigerator magnet • Webpage added to anaheim.net with FAQs and other info • Customer service via 800 number and email enabled • Events • 12 events in 2005 • Included both days when California grid had problems • Results • 13% peak reduction – same as reduction measured in critical peak price program • SDG&E has proposed rolling this out to all of its small business and residential customers

24. Case Study 5: Auto-DR • Nationwide test by Lawrence Berkeley National Labs • Automated response to hourly prices • Prices published on server • Customer systems grab prices automatically • Energy management system controls load in response to prices

25. Auto DR Results

26. Auto DR Results: Office Buildings

27. Customer Shed Strategies

28. Conclusions • Demand response and energy information are of interest to a subset of businesses • For whom controlling energy costs is a major concern • Who are provided with tools to manage energy costs • Some good success stories • Customer-friendly demand response programs are: • Simple • Easy to participate in • Are supported by automation tools and automated response • Have risks that are known and easily managed • Stable over time • Offer good value for customer efforts