Efficient (Smart) Electricity Pricing

1. Efficient (Smart) Electricity Pricing Steven Braithwait Christensen Associates Energy Consulting EEI Advanced Rate Course August 5, 2008

2. Agenda • Features of traditional vs. efficient rates • Why efficient pricing now? • Examples of efficient pricing • Evidence of customer price response • Selling efficient pricing to consumers and management

3. Historical Background • Traditional retail rates satisfy most accepted rate design goals • Revenue recovery • Rate & bill stability • Simplicity • Efficient pricing addresses an historically overlooked goal – economic efficiency in allocating resources

4. Traditional Retail Rates • Fixed rates reflect averagehistorical embedded costs • Flat or blocked energy prices • Demand charges • “One-size-fits-all” rates apply to broad classes of customers • Note exceptions – SCE (49 tariffs); Georgia Power (39 tariffs + many riders) • At same time, customers in most rate classes typically display a range of load profiles, implying a range of costs to serve, even though all face the same price • Creates inertia against moving from status quo rates

5. Efficient Electricity Pricing • Reflects the forward-looking, time-varying resource costs of consumers’ use of electricity • Reflects relevant risks to energy providers • Larger risk premium for products offering greater price certainty (insurance) • Offers optional price structures that acknowledge diverse customer risk preferences • Gives consumers opportunities to manage their energy costs • However, smart pricing requires smart meters

6. Why Efficient Pricing Now? • Falling reserves; Rising costs; Uncertainty • Expected market costs exceed embedded cost-based rates • High interest in demand response (DR) & resource efficiency as partial substitutes for new capacity (EPAct 2005) • New factors that support smart pricing: • Organized power markets provide transparent hourly wholesale prices – basis for retail prices • Expanding deployment, and improving business case for smart meters (AMI)

7. Cost-Saving Opportunities from Efficient Pricing • Traditional rates imply disconnectedwholesale and retail power markets: • Varying hourly wholesale costs • Fixed retail rates • Results: • Non-responsive electricity demand • Suppliers build extra generation capacity to reliably meet that non-responsive demand • Efficient pricing can reduce those costs

8. Value of Demand Response Under Smart Pricing Replaces the Cost of Extra Peaking Generation Typical DR target – 5% of max. demand; 1% of hours $20 - 40 million/yr cost savings for 10,000 MW system (1% of total cost) Peaking generation Load duration curve

9. Categories of Efficient Pricing Trade-off between risk & hedge premium Hedging Premium Fixed rates include hedging cost of “insurance” against price uncertainty Flat price High TOU rate CPP Hourly w/ hedge Low Hourly pricing 0 Time-based variability Low High

10. Critical Peak Pricing (CPP) Often combined with TOU • TOU rates designed to reflect average difference in marginal costs in peak and off-peak periods (e.g., $0.12 vs. $0.05/kWh) • Critical-peak price (CPP) replaces TOU peak rate on critical days • CPP reflects expected marginal energy and reliability costs in top 1 – 2 % of hours (e.g., $0.25 – 1.00/kWh, or more) • TOU peak price is discounted to reflect removal of highest-cost peak hours • Examples • Gulf Power (FL) – Residential • Several residential pilots • Wisconsin Public Service – C&I

11. Designing a Time-Based Rate • Information needed • Hourly loads of target population • Expected hourly marginal/market costs • Revenue requirements • Determine optimal TOU pricing periods • Minimize cost variability w/in TOU periods • Calculate load-weighted MC by period • Starting point for TOU prices • Adjust resulting TOUprices to recover revenue requirements at base usage • Prices may diverge from MC, but still reflect peak/off-peak differential

12. Variations on CPP/TOU (1) • Add CPP to standard non-TOU rate on critical days (avoids complications of designing voluntary TOU rate) • PG&E SmartRate for Residential & Small C&I • Variable CPP – More than one critical price e.g., “High” & “Very critical” • PG&E, SCE, SDG&E – CPP for C&I > 200 kW • Variable Peak – Day-ahead on-peak pricing – reflects costs more accurately • Proposed in Connecticut

13. Variations on CPP/TOU (2) • Day-type TOU – Low/medium/high TOU price profiles • Tempo residential rate in France • Peak-day rebate – (“Voluntary CPP”) • Credit for load reductions below baseline • Requires baseline calculation • Pilot examples • PSE&G (New Jersey) • PEPCO (Wash. D.C.) • Anaheim & SDG&E (California) • Georgia Power Co. • Ontario (Canada)

14. Variable CPP/TOU Rate CPP (Critical) CPP (High) TOU on-peak

15. Percent of Annual Hours in EffectExample of Gulf Power CPP Low Prices are less thanstandard rate in 87% of hours 28% 59 % 1% Critical (Maximum) Medium 12% High Critical pricing periods are most likely to occur Monday-Friday between 6:00 am - 10:00 am (winter) and 3:00 p.m. - 6:00 p.m. (summer).

16. Hourly Pricing • Hourly prices – announced day-ahead or hour-ahead, or real-time • Prices indexed to wholesale LMP (or utility’s marginal cost) • Residential RTP in Illinois • Often combined with financial contract (fixed price for fixed quantity) to manage risk • Block and indexed pricing in competitive markets • Two-part RTP in regulated markets (Georgia Power Co. – 2,100 C&I customers)

17. How Two-part RTP WorksCustomer pays standard rate for CBL, then Customer “sells” energy at high RTP prices CBL Actual load MWh Customer “buys” energy at low RTP prices (relative to CBL)

18. How Do Customers Respond to Dynamic Pricing? • Numerous studies show significant price response on average • Considerable variability among individual customers, though some typical patterns: • Most responsive – large; energy intensive; have facilitating technology (e.g., on-site generation; product storage; comm. & control) • Some evidence of 3 – 5% reduction in overall consumption – conservation effect

19. Residential Peak-Load Reduction(CPP, RTP & Peak rebate) CPP + Enabling technology CPP: No enabling technology RTP & rebate

20. Evidence on Customer Response to Dynamic Pricing – C&I • Sources of information: • CAEC research • Reviews of research reports & presentations = 600+ customers

21. Distributions of RTP Price Responsiveness by Business Type (Georgia Power) SIC 32 – Stone, clay & glass Office Buildings Backup generators SIC 35-39 – Machinery, etc Schools & Universities SIC 494 – Water supply

22. Like Having a choice Ability to manage energy usage and bills Control over energy costs Short peak periods (4 – 6 hrs) Access to lower prices in non-peak periods Technology that helps them control use Help from utility Don’t like Long peak periods (e.g., 12 hours) High prices when they need power the most (hottest summer afternoons)[Suggests a need for education on why prices vary, and how they can benefit] What Customers Like/Don’t Like about Time-Based Pricing

23. Barriers to Efficient Pricing • Metering/communication costs (becoming less important) • Lack of customer understanding • Lack of effective utility marketing • Perceived limits to utility benefits • Load response reduces costs; but lower sales reduce revenue toward fixed costs • Perceived customer resistance

24. Selling Efficient Pricing to Utility Management • Assure recovery of fixed delivery costs through non-volumetric rates (e.g., customer charges that vary by size, to protect small users) • Greater customer satisfaction w/ greater choice • Addresses EPACT 2005 requirements, if needed • Load response improves system load factor and reduces costs • Design rates so utilities benefit through sharing cost savings with participating customers

25. Conclusions • Looming electric industry crisis? • Declining reserve margins, high costs, limited options for new capacity, and considerable carbon uncertainty • Efficient pricing gets the right signals to consumers before it’s too late • AMI provides foundation for efficient pricing • Time to move forward!