Architecting the Future of Dynamic Pricing session 1... · ACCC/AER Regulatory Conference 2014 3| brattle.com In the U.S., we lose $10 billion each year due to flat rate pricing 33%

Copyright © 2014 The Brattle Group, Inc.

Architecting the Future

of Dynamic Pricing Dynamic Retail Pricing for More Efficient Outcomes

ACCC/AER Regulatory Conference 2014

Brisbane, Queensland

Ahmad Faruqui

Au g u s t 8 , 2 0 1 4


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Agenda

  Benefits of dynamic pricing

  Barriers to dynamic pricing and seven myths debunked

  Results of experimental roll-outs: case study #1 at BGE

  Results of full-scale roll-outs: case study #2 in Ontario

  Opt-in vs. opt-out: case study #3 at SMUD

Benefits of Dynamic Pricing


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In the U.S., we lose $10 billion each year due to flat rate pricing

  33% of the nation’s 114 million households are on smart meters

  But only 1% are on time-based rates ▀ And only 1% of these are on dynamic pricing rates

  That prevents us from harnessing the benefits of universal dynamic pricing

▀ $7B/year in lower energy costs

▀ $3B/year in reduced cross-subsidies


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Seven Myths Stand in the Way


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The seven myths about dynamic pricing

  Myth #1: Customers don’t respond to dynamic pricing

  Myth #2: Customer response does not vary with dynamic pricing

  Myth #3: Enabling technologies don’t boost demand response

  Myth #4: Customer response does not persist over time

  Myth #5: Dynamic pricing will hurt low-income customers

  Myth #6: Customers have never encountered dynamic pricing

  Myth #7: Customers don’t want dynamic pricing

Dynamic Pricing

Myth #1: Customers don’t respond to dynamic pricing

Myth #2: Customer response does not vary with the magnitude of the price signal

Myth #3: Enabling technologies don’t boost demand response

Myth #7: Customers don’t want dynamic pricing

Myth #6: Customers have never encountered dynamic pricing

Myth #4: Customer response does not persist over time

Myth #5: Dynamic pricing will hurt low-income customers


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Myth #1: Customers don’t respond to dynamic pricing

  Because results vary widely, some conclude that we have learned nothing about customer response


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60% of the tests have produced peak reductions of 10% or greater


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Grouping results by tariff design helps explain some of the variation in impacts


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Myth #2: Customer response does not vary with the magnitude of the price signal

  Not only do customers respond, but the magnitude of their response varies with the price incentive. The higher the incentive, the greater their demand response

  To study this relationship between price incentive and peak energy reduction, we have estimated the Arc of Price Responsiveness. The Arc is based on 212 time-varying pricing treatments from around the world


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We plot demand response against the peak to off-peak price ratio

TOU Impacts (price only) Dynamic Pricing Impacts (price only)


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Myth #3: Enabling technologies don’t boost demand response

TOU Impacts Dynamic Pricing Impacts

  The data shows that enabling technologies boost price responsiveness


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Myth #4: Customer response does not persist over time

  We observe that customer response has persisted in long-lived pilots

▀ California, Washington, D.C., Oklahoma for 2 years

▀ Maryland for 4 years

  TOU programs have been in place for decades

▀ The French tempo tariff goes back to 1965

▀ Arizona’s TOU rates go back to 1980


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Myth #5: Dynamic pricing will hurt low-income customers

  Nearly 80% of low income customers are paying more under flat rates


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Low income customers are price responsive, so they will save more with dynamic pricing


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Myth #6: Customers have never encountered dynamic pricing

  Consumers experience dynamic pricing in everyday purchases

  In the 1990s, Robert Cross highlighted the trend toward setting prices dynamically to maximize profit*

  Today, dynamic prices are used by a variety of capital-intensive industries such as airlines, hotels, rental car firms, and railroads

  Since 2009, tickets for San Francisco Giants baseball games have varied according to the value of the game

*Source: Cross, Robert. Revenue Management: Hard Core Tactics for Market Domination, Broadway Books, 1997.


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Myth #7: Customers don’t want dynamic pricing

  In Connecticut Light and Power’s Plan-it Wise pilot, post-pilot surveys and focus groups were carried out to examine how customers felt about their participation in the pilot. Residential customers who participated in the survey had an overall satisfaction rating of 5.1 out of a possible 6, with 92 percent saying they would participate again

  Customers showed similarly high levels of satisfaction with pilots at Consumers Energy, Baltimore Gas and Electric, Hydro One and California utilities


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Customers are not inconvenienced by time-varying pricing

  Related to the myth that customers do not want dynamic

  pricing is the idea that customers will have to resort to extreme measures to save money on dynamic rates, such as getting up at 2 AM to do the laundry

  In a recent survey of customers who participated in the Hydro One TOU pilot, only 4 percent found the changes in their daily activities to be inconvenient

  Most customers value the opportunity to save money by making small adjustments in their energy consumption schedules


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Results of Experimental Roll-outs


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Case Study #1: Baltimore Gas & Electric’s Smart Energy Pricing (SEP) Pilot

Scientifically valid sample design and M&V method

Continued for four consecutive summers (2008-2011)

▀ The Brattle Group carried out the impact evaluation for each of the summers and analyzed whether price-responsiveness persists over time

More than 11 different treatments tested over the course of four years with nearly 950 treatment customers at its height

Yielded invaluable information for the design of BGE’s full-scale pricing program


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SEP pilot tested 11 treatments over the course of four years


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Findings informed BGE’s full scale deployment of dynamic pricing

  Customers were responsive to the price signals

▀ Customers responded similarly to the CPP and PTR rates

▀ Elasticity of substitution ranged from 0.100 to 0.149 (depending on weather conditions)

▀ The peak impacts ranged from 23 to 34 percent at a 10:1 price ratio (depending on the weather)

▀ Daily price elasticity was estimated at -0.05

Customers who were on the price-only treatment for four years showed persistence in their price responsiveness

BGE rolled out opt-out PTR rates to 315,000 customers in the summer of 2013

▀ 82% of the customers engaged


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Results of Full-scale Roll-outs


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Residential dynamic pricing is transitioning to a new phase: full-scale deployment

Several utilities are achieving significant participation through aggressive opt-in programs

▀ Time-of-use (TOU) rates at APS and SRP in Arizona

▀ Variable peak pricing (VPP) at OG&E in Oklahoma

  Others are rolling out default programs for the mass market

▀ Pepco in Delaware and Maryland

▀ BGE in Maryland

▀ Sacramento Municipal Utility District (SMUD) in California

▀ The Province of Ontario, Canada


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Case Study #2: Ontario’s Residential TOU Program

Besides Italy, Ontario is the only region in the world to deploy Time-of-Use (TOU) rates for generation charges to all customers who stay with regulated supply

TOU rates were deployed in Ontario to incentivize customers to curtail electricity usage during the peak period and possibly to reduce overall electricity usage

The Brattle Group was retained by Ontario Power Authority to undertake the impact evolution of the TOU program

▀ Three year assignment; the 1st Year Impact Evaluation results are presented here, the 2nd year study is underway


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Impact evaluation challenges

Presence of more than 70 local distribution companies (LDCs) in the province

Sheer size of data (hourly data on four million customers over three years)

Non-experimental design

Mild-peak to off-peak price ratio (1.5:1)

Multiple pricing periods

Customers could opt-out of regulated TOU tariff and switch to retail providers


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Impacts measured in the study

For each LDC analyzed in the Study, we quantified the following impacts and elasticities by customer class and by season:

▀ Load shifting impacts

▀ Peak demand impacts

▀ Conservation impacts

▀ Elasticity of substitution

▀ Overall conservation elasticity

These results and the details of the study are discussed in, “Impact Evaluation of Ontario’s TOU Rates: First Year Analysis”, report prepared for Ontario Power Authority, November 2013 http://www.brattle.com/system/publications/pdfs/000/004/967/original/Impact_Evaluation_of_Ontario's_Time-of-Use_Rates-First_Year_Analysis_Faruqui_et_al_Nov_26_2013.pdf?1386626350

http://www.brattle.com/system/publications/pdfs/000/004/967/original/Impact_Evaluation_of_Ontario's_Time-of-Use_Rates-First_Year_Analysis_Faruqui_et_al_Nov_26_2013.pdf?1386626350









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In the 1st Year Study, we analyzed hourly customer data from four LDCs

These LDCs were selected based on their previous experience with TOU pilots, general size and geographic location

They represent roughly 50 percent of the Ontario population

Most LDCs have a sufficiently long period of pre-TOU data to allow impact evaluation to be carried out

Customers who are at the tail end of the deployment constitute the control group

We examined residential and general service classes


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Our models were estimated over several pricing periods

Summer Time Periods (May-October)

Winter Time Periods (January- April, November and December)


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Overview of residential class results

There is significant evidence of load shifting across all LDCs

▀ Reduction in usage in the peak and mid-peak periods (generally highest in the peak periods), increase in usage in the off-peak periods

Load shifting is higher in the summer rate period than the winter

▀ Summer peak period impacts range from -2.6% to -5.7%

▀ Winter peak period impacts range from -1.6% to -3.2%

  Peak period substitution elasticities range from -0.12 to -0.27

  Evidence on energy conservation was inconclusive


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Opt-in vs. Opt-out Roll-outs


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Should TOU rates be rolled out as the default tariff?

  The average TOU enrollment level is 28% under default flat rates. When TOUs are the default, the average enrollment rate rises to 85%

Residential TOU Enrollment Rates


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The dynamic pricing enrollment levels are similar to those of the TOU offerings

Residential Dynamic Pricing Enrollment Rates

  The average dynamic pricing enrollment is 20% under default flat rates and 84% when dynamic prices are the default


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Should we roll out dynamic pricing as the default rate?

  In general, there are three types of customers:

Type A customers Highly interested in TVR (time varying rates)

Type B customers Somewhat interested in TVR

Type C customers Not interested in and may be hostile to TVR)


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We develop three hypotheses for the impact of a default time varying rate:

  H1: Aimpact + Bimpact = Aimpact

▀ Only Type A customers respond to the TVR, so the impact of the TVR for Type B customers is zero

  H2: Aimpact + Bimpact < Aimpact

▀ There is consumer backlash to the default TVR so that all Type B customers and even some Type A customers opt out

  H3: Aimpact + Bimpact > Aimpact

▀ All Type A customers and some Type B customers respond to the TVR


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We expect that H3 is the most likely outcome

  Overall demand response savings will always be greater under default TVR than a default flat rate, provided the impact for group B is positive

Participation in TVR Under Different Default Options


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Case Study #3: Opt-in vs. opt-out at SMUD

  A pilot by Sacramento Municipal Utility District tested both opt-in and opt-out rates. By assigning the entire opt-in impact to Type A customers, we can calculate the Type B customers’ impact according to the equation:

▀ ImpactA+B = ImpactA ∗ (ShareA

ShareA+B) + ImpactB ∗ (

ShareB

ShareA+B)

▀ Filling in the values and rearranging, we estimate that Type B customers have an impact of 2% on default TOU rates, one third of the impact of Type A customers

Opt-In TVR Default TVR Opt-In TVR Default TVR

Enrollment Rate 28% 85% 20% 84%

Peak Reduction for Participating Customers 6% 3.4% 18% 8.9%

Aggregate Peak Reduction (MW) 34 57 72 149

Notes:

Assumed Coincident Demand (MW): 2,000

TOU CPP

Peak Reductions for SMUD


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The Transition


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Transitioning to dynamic pricing


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Presenter Information

AHMAD FARUQUI, PH.D. Principal│ San Francisco [email protected] +1.415.217.1026 +1.925.408.0149 (cell)

Dr. Ahmad Faruqui is a Principal with The Brattle Group whose work is focused on the full spectrum of customer-side issues involving demand forecasting, rate design, energy efficiency, demand response, and the smart grid broadly speaking. He has worked for more than three dozen utilities around the globe and testified before a dozen state and provincial commissions and legislative bodies. His work has been cited in The Economist, The New York Times, the Washington Post and USA Today. He has appeared on Fox Business News and National Public Radio. The author, co-author or editor of four books and more than 150 articles, he holds a Ph.D. in economics from The University of California at Davis and B.A. and M.A. degrees in economics from The University of Karachi, Pakistan.

The views expressed in this presentation are strictly those of the presenter and do not necessarily state or reflect the views of The Brattle Group, Inc.


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Additional Resources

  Cross, Robert. “Revenue Management: Hard Core Tactics for Market Domination.” Broadway Books, 1997.

  Faruqui, Ahmad, Ryan Hledik, and John Tsoukalis. “The Power of Dynamic Pricing.” The Electricity Journal: Volume 22: April 2009, pp. 42-56.

  Faruqui, Ahmad, Ryan Hledik, and Neil Lessem. “The ABC’s of Default Time-Varying Rates.” The Brattle Group. June 13, 2014.

  Faruqui, Ahmad, and Jennifer Palmer. “Dynamic Pricing and its Discontents.” Regulation: Fall 2011, pp. 16-22

  Sergici, Sanem. “Dynamic Pricing: Transitioning from Experiments to Full Scale Deployments.” The Brattle Group. June 30, 2014.


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About Brattle

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  We are distinguished by our credibility and the clarity of our insights, which arise from the stature of our experts, affiliations with leading international academics and industry specialists, and thoughtful, timely, and transparent work. Our clients value our commitment to providing clear, independent results that withstand critical review.


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Architecting the Future of Dynamic Pricing session 1... · ACCC/AER Regulatory Conference 2014 3| brattle.com In the U.S., we lose $10 billion each year due to flat rate pricing 33%