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HOW RETAIL PRICING CAN DELIVER CUSTOMER VALUE IN A SMART GRID WORLD
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Transcript of HOW RETAIL PRICING CAN DELIVER CUSTOMER VALUE IN A SMART GRID WORLD
Copyright © 2009 The Brattle Group, Inc.
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HOW RETAIL PRICING CAN DELIVER CUSTOMER VALUE IN A SMART GRID WORLD
Ahmad Faruqui, Ph. D.Pacific Northwest Demand Response Project
July 15, 2010
2PNDRP
The state of play
♦ The smart grid is being rolled out in many jurisdictions and the federal government has awarded utilities billions of dollars to expedite its deployment
♦ As most of these deployments have not focused on customer benefits, there has been a backlash among customers in some communities who see their monthly bills going up to cover smart grid costs without any commensurate benefits
♦ Customer concerns about costs, privacy and cyber security dominate the agenda of state regulators
3PNDRP
Retail pricing innovation is a means of engaging with the customer
♦ Customers, especially the new and emerging generation, are concerned about using energy wisely, having a smaller carbon footprint and lowering their utility bills
♦ However, for the vast majority of customers, the price of electricity provides them with very little information about how to achieve these objectives
♦ Most customer-side programs focus on providing rebates or creating standards and assume that electric rates cannot be touched
♦ Price matters in every industry except the electric
♦ Customer-side programs can be turbo-charged if complementary changes in electric rates accompany their rollout
4PNDRP
A classic example is inclining block rates
♦ About two-thirds of Americans today receive electric service on either flat or declining block rates
♦ The one-third that receive service on inclining block rates do not get much of an incentive to conserve from existing designs
♦ It has been shown that moderately inclining rates can boost energy efficiency levels at very low cost
♦ When coupled with time-varying rates, they can provide the best way to reward customers for using energy wisely and for encouraging them to invest in distributed generation and renewable energy options
5PNDRP
The full range of retail pricing options
Rate Description
Time-of-Use (TOU)Charges a higher price during all weekday peak hours and a discounted price during off-
peak and weekend hours
Super Peak TOUSimilar to the TOU with the exception that the peak window is shorter in duration (often
four hours), leading to a stronger price signal
Inclining Block Rate (IBR)Customer usage is divided into tiers and usage is charged at higher rates in the higher tiers;
meant to encourage conservation
Critical Peak Pricing (CPP)Customers are charged a higher price during the peak period on a limited number of event
days (often 15 or less); the rate is discounted during the remaining hours
Variable Peak Pricing (VPP) Critical Peak Pricing rate with added variability
CPP-TOU CombinationA TOU rate in which a moderate peak price applies during most peak hours of the year, but
a higher peak price applies on limited event days
Peak Time Rebate (PTR)The existing flat rate combined with a rebate for each unit of reduced demand below a pre-
determined baseline estimate during peak times of event days
Real Time Pricing (RTP)A rate with hourly variation that follows LMPs, but with capacity costs allocated equally
across all hours of the year
Critical Peak RTPA rate with hourly variation based on LMPs and with a capacity cost adder focused only
during event hours, creating a strong price signal at these times
6PNDRP 6
0
5
10
15
20
25
30
0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000
kWh / Month
Ce
nts
/ kW
h
Average Customer
Rate A
Rate B
Rate C
Rate D
Existing Flat Rate
Four illustrative inclining block rate designs
7PNDRP 7
Energy use could decline by up to 5.9 percent and customer bills by up to 9.1 percent
Avg Percent Change in UsagePrice Elasticity Rate A Rate B Rate C Rate D
Short Run Mean -5.9% -2.2% -1.0% -0.5%Std Dev 2.0% 0.8% 0.3% 0.2%
Long Run Mean -18.4% -6.7% -3.1% -0.7%Std Dev 6.5% 2.4% 1.1% 0.4%
Avg Percent Change in Class RevenuePrice Elasticity Rate A Rate B Rate C Rate D
Short Run Mean -9.1% -3.1% -1.0% -1.4%Std Dev 3.1% 1.1% 0.4% 0.5%
Long Run Mean -28.4% -9.4% -3.3% -2.6%Std Dev 9.9% 3.4% 1.1% 1.0%
8PNDRP 8
Price response mitigates the impact on high use customers by shifting the breakeven point
-70%
-60%
-50%
-40%
-30%
-20%
-10%
0%
10%
20%
30%
100 200 300 400 500 600 700 800 900 1,000 1,100 1,200 1,300 1,400 1,500 1,600 1,700 1,800 1,900 2,000
Customer Size
Ch
an
ge
in M
on
thly
Bill
No price elasticity
With price elasticity
Break-even point
Tier 1
9PNDRP
Each rate offers a different value proposition to each type of customer
Risk (Variance in
Price)
Reward (Discount from Flat
Rate)
10%
5%
10.5Flat Rate
RTP
CPP
VPP
Inclining Block Rate
Seasonal Rate
TOU
Less Risk, Lower
Reward
More Risk, Higher Reward
Super Peak TOU
PTR
Potential Reward
(Discount from Flat
Rate)
Incr
easi
ng R
ewar
d
Increasing Risk
10PNDRP
Utilities can evaluate these innovative rates against five criteria to configure their menu
Criteria Description
Simplicity & Ease of Understanding
Will customers be able to quickly understand the rate? Is it actionable?
Customer value proposition
Does the rate provide customers with a significant bill savings opportunity?
Retail-wholesale market connection
Does the rate satisfy legislative and regulatory requirements regarding connection to the wholesale market?
Incentive to reduce peak demand
Is the rate expected to produce significant reductions in peak demand?
Incentive for permanent load shifting
Will the rate encourage customers to permanently shift load from higher cost hours to lower cost hours?
11PNDRP
Scoring the rates – an illustration
SimplicityValue
Proposition
Retail-Wholesale Connection
Peak Reduction
Load Shifting Score
Description
Super Peak TOU
3 1 2 2 2 10Provides incentive for permanent load
shifting with strong price signal
CPP 2 3 2 3 1 11Simple, focused rate for targeted reductions
during top load hours
CPP/TOU 2 3 3 3 2 13Provides combined incentive of load shifting
and demand response
PTR 2 2 1 3 1 9
Residential rate produces no immediate “losers”; potentially most applicable for low income residential customers; interruptible
tariff could be used for C&I
RTP 1 1 - 3 3 1 2 8 - 10 Conveys variability in hourly LMPs
CP RTP 1 1 - 3 3 3 2 10 - 12CP RTP provides additional curtailment
incentive beyond LMP during top load hours
Degree to which criterion is satisfied: 3 = High 2 = Medium 1 = Low
12PNDRP
The pure CPP rate provides a strong demand response signal
Illustrative CPP Rate for Residential Class - SummerAll-In Rates
$0.00
$0.20
$0.40
$0.60
$0.80
$1.00
$1.20
$1.40
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
All
-In
Rat
e ($
/kW
h)
Existing Rate = 12.6 cents
Off Peak Rate = 11.4 cents
Critical Peak Rate = 123.4 cents
Illustrative CPP Rate for Residential Class - WinterAll-In Rates
$0.00
$0.20
$0.40
$0.60
$0.80
$1.00
$1.20
$1.40
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24A
ll-In
Rat
e ($
/kW
h)
Existing Rate = 12.6 cents
Off Peak Rate = 11.4 cents
• Customers pay a flat rate for all kWh every day unless a critical day is called• On critical days during the critical peak period customers pay a premium for all kWh used• The critical peak price is equal to the cost of capacity plus the average critical peak LMP• Spreading the off-peak discount over all non-critical hours of the year provides a cost savings
to customers
13PNDRP
The CPP-TOU rate ties more closely to actual system costs than the pure CPP rate
Illustrative CPP/TOU Rate for Residential Class - SummerAll-In Rates
$0.00
$0.20
$0.40
$0.60
$0.80
$1.00
$1.20
$1.40
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
All
-In
Rat
e ($
/kW
h)
Existing Rate = 12.6 cents
Critical Peak Rate = 123.4 cents
Peak Rate = 20.5 centsOff Peak Rate = 10.2 cents
Illustrative CPP/TOU Rate for Residential Class - WinterAll-In Rates
$0.00
$0.20
$0.40
$0.60
$0.80
$1.00
$1.20
$1.40
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24A
ll-I
n R
ate
($/k
Wh
)
Existing Rate = 12.6 cents
Peak Rate = 20.5 centsOff Peak Rate = 10.2 cents
• Every day is divided into peak and off-peak periods• Customers pay lower rate for off-peak usage and higher rate for peak period usage• On critical days during the critical peak period customers pay a premium for all kWh used• The critical peak price is equal to the cost of capacity plus the average critical peak LMP• The low off-peak rate provides heating customers with an opportunity to save as compared to a flat rate
14PNDRP
Like the CPP rate, the CPP-TOU rate has lower rates in most hours of the year
Hours of the YearCPP-TOU Rate
Peak Hours
98411%
Critical Peak
Hours601%
Off-Peak Hours771688%
15PNDRP
The PTR is a mirror image of the CPP and pays customers to reduce peak demand
Illustrative PTR Rate for Residential Class - SummerAll-In Rates
-$1.40
-$1.00
-$0.60
-$0.20
$0.20
$0.60
$1.00
$1.40
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
All
-In
Rat
e ($
/kW
h)
Existing Rate = 12.6 cents
Peak Rebate = -110.8 cents
Illustrative PTR Rate for Residential Class - WinterAll-In Rates
-$1.40
-$1.00
-$0.60
-$0.20
$0.20
$0.60
$1.00
$1.40
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
All
-In
Rat
e ($
/kW
h)
Existing Rate = 12.6 cents
• Customers pay the default rate for all kWh used; if they make no changes in their usage they continue to pay the default rate with no extra costs (“carrot only” approach)
• On critical days customers can earn a rebate reductions in usage below an estimate of what they otherwise would have consumed (their “baseline” calculation)
• The rebate amount is equivalent to the critical peak price of the CPP and the CPP-TOU• Baseline calculation method and where customer payment originates are important issues to resolve
16PNDRP
All these rates can yield substantial amounts of demand response – illustrative case
Projected Change in Critical Peak Demand
-20%-20%
-12%
-13%
-21%
-12%
-14%
-20%
-14%-15%
-25%
-20%
-15%
-10%
-5%
0%
Residential Small C&I Medium C&I
Ch
ang
e in
Dem
and
Du
rin
g E
ven
t H
ou
rs
PTRCPPCPP-TOUCP RTP
PTR impacts are shown for the average low-income residential
customer
17PNDRP
The CPP-TOU rate will produce the greatest amount of permanent load shifting – illustration
A slight increase in non-event peak demand could occur under the CPP due to the discounted price during these hours
Projected Change in Non-Event Peak Demand
0% 0.4% 0.3% 0.3%
-5%
-2% -3%-1% -1% -2%
-25%
-20%
-15%
-10%
-5%
0%
5%
Residential Small C&I Medium C&I
Ch
an
ge
in D
eman
d D
uri
ng
No
n-E
ven
t P
eak
Ho
urs
PTRCPPCPPTOUCP RTP
18PNDRP
Bill savings are larger for customers with flatter load shapes – illustration
Distribution of Dynamic Pricing Bill ImpactsResidential Customers on CPP-TOU Rate
-15%
-10%
-5%
0%
5%
10%
15%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Ch
an
ge
in
Av
era
ge
Mo
nth
ly B
ill
Before customer price response
After customer price response
"Losers""Winners"
19PNDRP
Low income customers have demonstrated significant price responsiveness in recent experiments
Low income customer response ranges from 22% to 214% of the average customer
22%
50%66% 66%
84% 100% 100%
200%214%
0%
50%
100%
150%
200%
250%
California SPP: CARE vs. Average
PG&E SmartRate
2009: CARE vs. Average
PG&E SmartRate
2008: CARE vs. Average
CL&P's PWEP
Program (PTP high): Hardship vs.
Average
California SPP: Low Income vs. Average
BGE 2008: Known Low Income vs.
Known Average
Customer
CL&P's PWEP
Program: Known Low Income vs.
Known Average
Customer
Pepco DC (price only): Low Income vs. Average Residential
Pepco DC (price +
thermostat): Low Income vs. Average Residential
Pea
k R
edu
ctio
nLow Income Customer Responsiveness Relative to Average Customer Response
Average customer response
20PNDRP
Up to 88% of low-income customers could experience bill
savings when enrolled in a CPP-TOU rate – illustration
Distribution of Dynamic Pricing Bill ImpactsLow Income Residential Customers on CPP-TOU Rate
-15%
-10%
-5%
0%
5%
10%
15%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Ch
ang
e in
Ave
rag
e M
on
thly
Bill
Before customer price response
After customer price response
"Winners" "Losers"
21PNDRP
References
Faruqui, Ahmad, “Inclining toward efficiency,” The Public Utilities Fortnightly, August 2008.
Faruqui, Ahmad, Sanem Sergici, and Jenny Palmer, The Impact of Dynamic Pricing on Low Income Customers, The Institute for Electric Efficiency, June 2010. http://www.edisonfoundation.net/iee/reports/IEE_LowIncomeDynamicPricing_0610.pdf
Faruqui, Ahmad, Ryan Hledik and Sanem Sergici, “Rethinking pricing: the changing architecture of demand response,” The Public Utilities Fortnightly, January 2010.
Faruqui, Ahmad, Ryan Hledik, and Sanem Sergici, “Piloting the smart grid,” The Electricity Journal, August/September, 2009.
Faruqui, Ahmad and Sanem Sergici, “Household response to dynamic pricing of electricity–a survey of the experimental evidence,” January 10, 2009. http://www.hks.harvard.edu/hepg/. Journal of Regulatory Economics, Forthcoming.
FERC, “A National Assessment of Demand Response Potential,” June 2009, http://www.ferc.gov/legal/staff-reports/06-09-demand-response.pdf .
22PNDRP
Biography
Ahmad Faruqui is an expert on how the smart grid affects electricity customers. He has performed cost-benefit analysis of smart grid programs for utilities in two dozen states and testified before several state and provincial commissions and legislative bodies. He has designed and evaluated some of the best known pilot programs involving dynamic pricing and in-home displays and his early experimental work is cited in Bonbright’s canon. 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 and a bachelor’s degree from the University of Karachi, Pakistan.