Assessing Ontario's Regulated Price Plan

Assessing Ontario’s Regulated Price Plan Ahmad Faruqui Ryan Hledik Ontario Energy Board Consultation Meeting Toronto, Ontario December 21, 2010

The logic of Time-of-Use (TOU) pricing • Generation costs vary by pricing period but this variation is masked by non-TOU rates, thereby creating an unintended inequity Under non-TOU rates, customers who don’t consume much during peak periods pay more than their fair share of costs and those who consume much during peak periods pay less than their fair share • By reflecting this time-variation in costs, TOU rates eliminate an important unfairness in rate design • Additionally, by lowering rates during the off-peak period and raising them during the peak period, TOU rates provide customers an opportunity to reduce their monthly bills by curtailing consumption during peak periods and/or shifting it to off-peak periods • These benefits have been demonstrated consistently across a broad range of studies carried out in North America, Europe and Australia which have found that about 75 percent of customers are better off with TOU rates

We explored the merits of alternative TOU design options in Ontario Overview of Project Approach

Ontario’s transition to TOU pricing is in progress Transitioning from the tiered rate… … to a TOU rate Currently ~2.8 million enrolled Currently ~1.2 million enrolled Compared to the tiered rate, the TOU provides a discount during the off-peak period (59% of hours) and a higher price in the remaining hours Note: Prices represent only the generation component of the rate.

The majority of hours are in the low-priced off-peak period, an attractive feature for customers There is a larger share of peak hours in the winter than in the summer

Each defining characteristic of the TOU rate was benchmarked against industry best practices Results of Benchmarking

System load and hourly energy prices align well in shape with the TOU rate There is a fairly broad summer peak and a dual peak in the winter

The peak-to-off-peak price ratio is low relative to TOU rates elsewhere • RPP TOU Price Ratios • Generation Only: • 1.9 to 1.5 to 1 • All-in: • 1.4 to 1.2 to 1 Distribution of Price Ratios in Existing TOU Rates (Generation Only) RPP TOU ratio = 1.9 Mean ratio = 3.8 Note: Details on each TOU rate are provided in the appendix This ratio could be adjusted to better reflect system conditions

There are many ways to increase the price ratio Rate Design Option In Existing TOU… Alternative option… Likely Impact on Price Ratio Renewables Cost Reallocation Existing GA costs only, allocated uniformly across periods Allocate wind & solar to peak period, account for expected FIT costs Increases peak costs, decreases off-peak costs, and increases price ratio Peak Duration 6 hour peak, 8 hour mid-peak (opposite in non-summer months) Shorten peak and mid-peak period to 4 hours in both seasons Shorter peak period spreads capacity costs over fewer peak hours, increasing the peak price Seasonality Year-round Summer-only TOU with off-peak rate applying during the winter months Summer-only means fewer peak hours and therefore higher peak price Price setting methodology Set off-peak and mid-peak price, solve for peak price Set peak and mid-peak price, solve for off-peak price Changes in the supply cost structure could increase or decrease the price ratio under this approach Number of periods Three periods (peak, mid-peak, and off-peak) Remove mid-peak period to create 2 period rate Depends on how prices are set; combined with other rate design approaches, smaller number of periods could be beneficial

Collectively, these changes could produce a price ratio of 4.9:1, while an alternate approach could lead to a 4.1:1 ratio Note: Impact on price ratio is cumulative as shown in figure; incremental impacts of each change to the design would be different if implemented individually

The results of TOU pilots in Ontario can be used to predict customer response to the new rate designs • TOU pricing was tested in five Ontario pilots • Newmarket Hydro • Hydro One • Hydro Ottawa • Oakville Hydro • Veridian Connections • TOU enrollment in the pilots ranged from 40 to 180 participants (although one pilot was just 3 commercial buildings) • Treatment periods were in the 2006 to 2007 timeframe, with pilot durations lasting from 5 months to slightly over 1 year See Appendix A for details on the pilots

The pilots are moderately applicable for extrapolation of TOU impacts at the province level Based on this screening, we have selected the Hydro One, Newmarket Hydro, and Hydro Ottawa pilots for more detailed analysis

The results from the 3 most relevant pilots were benchmarked against informed expectations • Peak impacts from the Ontario pilots align fairly well with expectations from other pilots around North America • The other North American pilot impacts were calibrated to the price ratio of the RPP TOU rate and Ontario’s system conditions Notes: (1) The impact evaluations conducted by Oakville Hydro and Veridian Connections were excluded due to lack of applicability of results or statistically insignificant impacts. (2) “Other pilot” impacts are calibrated roughly to the rates tested in the Ontario pilots; results would vary slightly depending on which Ontario pilot rates they are being calibrated to, although this variation is not enough to produce any significant difference in the impacts (roughly +/- 0.1%)

There is significant variation in overall energy consumption impacts across the pilots • This variation is partly explained by Ontario pilot limitations (short pilot durations spanning different time periods, often with a small number of participants) • Also explained by lack of average customer cost neutrality at the utility level (customers experience change in rate level when moving from existing tiered rate to TOU) • This highlights the need for better understanding of the impact of the TOU rate in Ontario Notes: (1) The impact evaluations conducted by Oakville Hydro and Veridian Connections were excluded due to lack of applicability of results or statistically insignificant impacts. (2) “Other pilot” impacts are calibrated roughly to the rates tested in the Ontario pilots; results would vary slightly depending on which Ontario pilot rates they are being calibrated to, although this variation is not enough to produce any significant difference in the impacts (roughly +/- 0.1%)

Implied elasticities from the Ontario pilots were integrated into Brattle’s Price Impact Simulation Model (PRISM) The PRISM Modeling Framework

Our PRISM analysis relied on three elasticity scenarios Lower-bound elasticity assumption: • Roughly tied to results of the Newmarket Hydro pilot • 0.5% peak reduction at 3-to-1 price ratio, with little conservation effect Upper-bound elasticity assumption: • Roughly tied to results of Hydro One pilot • 3% peak reduction at 3-to-1 price ratio, but with smaller conservation effect • “Base Case” elasticity assumption: • Average of “low” and “high” elasticities • Aligns with range of simulated impacts from other North American studies

Four alternative TOU rate designs were developed based on our findings Alternative TOU Description Price ratio Rate #1: Wind/solar reallocation The existing TOU with the addition and reallocation of expected wind and solar GA costs to the peak period 2.7-to-1 Rate #2: Wind/solar reallocation + 4-hour peak Rate #1 but also with peak and mid-peak windows reduced to four hours 3.2-to-1 Rate #3: Wind/solar reallocation + 4-hour peak + summer only Rate #2 but also with TOU rate limited to summer months (May through October); flat rate applies other months 4.9-to-1 Rate #4: Alternative peak price + 2 period Peak price set equal to average peak energy price plus levelized cost of capacity ($100/kW-yr); off-peak solved for cost neutrality; summer only with 4 hour peak period 4.1-to-1 See Appendix B for details of these four alternative rate designs

The average peak impacts of the four rate alternatives range from 1% to 4% and could be as high as 7% Range of Average RPP Customer Response Projections Elasticity assumptions based on the range of reasonable elasticities derived from a review of the existing Ontario impact studies and supplemented by the results of other time-based pricing studies; For the midpoint, elasticity of substitution = -0.03 and daily elasticity = -0.11

The rates will impact each customer differently depending on their consumption profile • “Flat” usage customers will experience bill savings due to low consumption in the higher-priced periods • The opposite is true for “peaky” usage customers • Bill impacts have been estimated for a representative sample of roughly 500 utility customers that fall at various points along the spectrum of “flat” and “peaky” usage Three Illustrative Customer Consumption Profiles

Across samples from 5 utilities, changes in customer bills will range from -12% to +18% Distribution of Bill Impacts for Rate #3 (Before Response) Note: Results shown for Rate #3 before any customer response and are relative to today’s TOU

After customers shift consumption, a higher percentage will experience bill savings Bill Impacts Before and After Customer Response Note: Results shown for Rate #3 for Toronto Hydro sample; see Appendix C for full results

The aggregate response of 4 million customers on the TOU rate will lower peak demand and ultimately contribute to a reduction in generation costs, helping all Ontarians

In other rate scenarios, peak demand declines from a low of 0.2% to a high of 4.4%

The Path Forward If the top priority is to… Then the OEB could… But be aware… Minimize the implementation burden Continue with the current design and simply reallocate renewables costs to the peak period This only marginally improves the price ratio Improve the price ratio Consider significant rate design changes that decrease the number of peak hours (such as seasonality and a shorter peak period) Significant design changes will require re-education of utilities, policymakers, and customers regarding the new rate structure Simplify the rate-setting process Pursue an alternative approach where the peak period price is pegged to marginal capacity and energy costs, and the off-peak is solved for revenue neutrality This would require a major overhaul of the current methodology and would require significant research to determine the appropriate marginal cost assumptions Better understand customer responsiveness Conduct an impact assessment of customer consumption behavior after the full transition to the TOU rate While this option carries little risk, alone it does not lead to greater customer response rates Improve customer response and perception Work with utilities to initiate an education campaign around the rate and its benefits, possibly including the provision of enabling technologies Customer education improves response but cannot lead to greater bill savings if the rate design does not offer the opportunity to significantly reduce bills Combinations of these approaches could achieve balance across priorities, but would be more complex

Ahmad Faruqui • Ahmad Faruqui provides expert advice on time-of-use and dynamic pricing to utilities and government agencies. He has testified on rate design issues before a dozen state and provincial commissions and legislative bodies and spoken at a wide variety of energy conferences in Brazil, Canada, France, Ireland, Saudi Arabia, the United Kingdom and the United States. • During the past two years, he has assisted FERC in the development of the “National Action Plan on Demand Response” and in writing “A National Assessment of Demand Response Potential.” He co-authored EPRI’s national assessment of the potential for energy efficiency and EEI’s report on quantifying the benefits of dynamic pricing. He has assessed the benefits of dynamic pricing for the New York Independent System Operator, worked on fostering economic Demand Response for the Midwest ISO and ISO New England, reviewed demand forecasts for the PJM Interconnection and assisted the California Energy Commission in developing load management standards. His most recent report, “The Impact of Dynamic Pricing on Low Income Customers,” has just been published by the Institute for Electric Efficiency. • The author, co-author or editor of four books and more than 150 articles, papers and reports, he holds a doctoral degree in economics from the University of California at Davis.

Ryan Hledik • Ryan Hledik is a senior associate of The Brattle Group with specialized expertise in assessing the impacts of smart grid programs, technologies, and policies. He has assisted electric utilities, regulators, research organizations, wholesale market operators, and technology firms in the development of innovative demand response and energy efficiency portfolios and strategies. • Recently, Mr. Hledik contributed to the development of the Federal Energy Regulatory Commission’s (FERC) National Assessment of Demand Response Potential, which was submitted to U.S. Congress in June 2009. Mr. Hledik has been the lead developer of several energy market simulation tools for the purposes of wholesale price forecasting, asset valuation, and emissions analysis. • Mr. Hledik received his M.S. in Management Science and Engineering from Stanford University in 2006, where his concentration was in Energy Economics and Policy. He received his B.S. in Applied Science (with honors) from the University of Pennsylvania in 2002 with minors in Economics and Mathematics. Prior to joining The Brattle Group, Mr. Hledik was a research assistant with Stanford University’s Energy Modeling Forum and a research analyst at Charles River Associates.

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Appendix A: • Current TOU

Today’s TOU has a 10-hour off-peak period and a price ratio of 1.9

The seasonal definition lines up with historical IESO load data • Ontario is mostly a summer peaking region (2004 was last year with winter peak) • However, on average energy use is higher in the winter (by 3% to 9% since 2004), presumably due to electric space and water heating Summer (May – Oct)

There is a less pronounced seasonal pattern in the historical energy price data • Prices are more volatile in the summer season • In 2008, the price exceeded $200/MWh in 15 hours, most of which were in the summer Summer (May – Oct) Note: 2008 Hourly Ontario Energy Price (HOEP) was used, because it appears to be more representative of the average historical prices than the 2009 HOEP, which was quite low.

TOU pricing pilots in Ontario Notes: “MUSH” is municipals, universities, schools, and hospitals In some pilots the TOU rate changed over time. In this table, the range is provided.

Appendix B: • Alternate TOU Designs

Rate #1: Today’s TOU with re-allocation (and addition) of renewable GA costs • Existing and expected wind & solar GA costs are allocated entirely to the peak period • The peak period price increases, with minor changes to prices in other periods • Alternative allocations could be explored, such as allocating a larger share of hydro costs to the peak period as well • Note that the GA cost associated with new renewables leads to an overall rate increase of 7.5%

Rate #2: Today’s TOU with renewable cost re-allocation and a four-hour peak period • The peak and mid-peak duration are decreased to 4 hours each • 25% of peak period GA cost is assumed to be a capacity cost; as such, the absolute cost is spread over the peak hours • As the number of peak and mid-peak hours decreases, the average $/MWh capacity price increases • Note that the 25% estimate for the capacity portion of GA costs is subject to revision

Rate #3: Summer-only TOU with renewable cost re-allocation and a four-hour peak period • The TOU rate structure only applies during summer months • The rate is flat during the remaining months of the year (equal to the off-peak price of the summer TOU rate) • The capacity portion of peak GA costs is spread over fewer hours as a result, and the peak price rises

Rate #4: The peak price is set based on historical marginal energy and capacity costs • The peak price is equal to an average peak energy price of $0.068/kWh plus a capacity price of $100/kW-year, spread across the peak hours • The rate is summer-only • This is a common marginal cost-based approach to TOU rate design that has been adopted by utilities in other parts of North America

Appendix C: • Summary of Bill Impacts

Expected Bill Impacts: Commodity Portion Only (Percent)

Expected Bill Impacts: Commodity Portion Only (Dollar Amount)

Expected Bill Impacts: All-In Bill (Percent)

Appendix C: • Sources

Other TOU Rates (1)

Assessing Ontario's Regulated Price Plan