C
HARLES
R
IVER
A
SSOCIATES
September 23, 2004
Electricity Pricing for Rate Cases
An EUCI Conference
Denver, Colorado
Ahmad Faruqui and Steve George

Presentation Objectives
Define critical-peak pricing (CPP)
Discuss where it has been implemented
Specify a cost-benefit analysis framework
Review impact evaluation methodologies
Provide impact estimates from California’s statewide pricing pilot and associated demand curves
Discuss barriers to implementation
EUCI Pricing Conference
2

C
HARLES
R
IVER
A
SSOCIATES

CPP is a sub-set of dynamic pricing
Dynamic pricing is an advancement over traditional TOU pricing, which allows prices to vary across the day and perhaps seasonally, but where both prices and time periods are known a
priori and are fixed for some duration
Dynamic pricing includes all electricity tariffs that recognize the inherent uncertainty in supply costs
• Option 1: The timing for which known prices are in effect is uncertain
• Option 2: Both timing and price levels are uncertain
• Option 3: Timing, price levels and time blocks are all uncertain
EUCI Pricing Conference
4

Examples of dynamic pricing
Critical Peak Pricing (CPP): Layers a much higher critical peak price on top of TOU rates. The CPP is only used on a maximum number of days each year, the timing of which is unknown until a day ahead or perhaps even the day of a critical pricing day
Extreme Day Pricing (EDP): Similar to CPP, except that the higher price is in effect for all 24 hours for a maximum number of critical days, the timing of which is unknown until a day ahead
Real Time Pricing (RTP): Prices that vary hourly or sub-hourly all year long, for some or all of a customer’s load
EUCI Pricing Conference
5

Why focus on the mass market?
The largest number of customers are in the residential and small commercial and industrial market, often called the mass market
They account for a third or more of the energy consumption in many utilities and a bigger fraction of the peak demand
These customers often do not make attractive candidates for retailers and are often left out of the picture
Letting the incumbent utilities give them a choice of pricing products brings them back into the game
EUCI Pricing Conference
6

C
HARLES
R
IVER
A
SSOCIATES

The French are the global leaders in dynamic pricing for mass markets
About 10 million residential customers are on a two-part TOU tariff in France, out of a population of 31 million customers
Several hundred thousand customers are on a special rate, called tempo, which was initiated in 1996
Prices on the tempo TOU rate vary by day type, being the highest on 22 red days, followed by 43 white days and 300 blue days
The days are called at 4:30 pm the day before, through the
Internet, Minitel and a vocal system; they are posted at 8:30 pm on a compteur electronique
EUCI Pricing Conference
8

EDF’s offers TOU and tempo rates
50
45
40
35
30
25
20
15
10
5
0
10.32
6.32
5.44
4.39
10.5
8.87
45.71
16.39
Regular TOU tempo Blue
Day tempo White
Day
Peak Off-Peak tempo Red
Day
EUCI Pricing Conference
9

Gulf Power
The Good Cents Select program combines TOU and CPP pricing elements with sophisticated energy management technology for residential consumers
The voluntary program has been in place for roughly two years and has about 3,000 customers enrolled
Each customer pays roughly $5/month to participate and still saves 15% on their electricity bill
Average coincident peak demand reductions exceed 2 kW
40 percent reduction in peak period energy usage
96% customer satisfaction rating
EUCI Pricing Conference
10

The first PG&E experiment
In 1992, PG&E implemented a CPP rate that used two-way communication with automated thermostat control of air conditioners
• Peak/off-peak price ratio of roughly 4.5/1 and a CPP/off-peak price ratio of nearly 8/1
Usage during the CPP period dropped by roughly half for low, medium and high usage customers
Usage reductions on the hottest CPP days were slightly greater than on other CPP days
• That is, customers did not override their thermostat setbacks even on the very hottest days
EUCI Pricing Conference
11

The GPU experiment
In 1997, GPU implemented a CPP pilot program similar to the
PG&E pilot, and got similar results
3-Part TOU rate with occasional use of critical peak price for limited number of high-cost hours
Peak/off-peak price ratios of 4/1 and 5/1 for 3-part rate with critical price ratio closer to 8/1 (50 ¢/kWh)
Energy reductions
Peak Period 26%
Critical Peak 50%
EUCI Pricing Conference
12

California’s statewide pricing pilot
(SPP)
The SPP is an outgrowth of a regulatory proceeding initiated by the CPUC (R.02-06-001) in June 2002 on advanced metering and dynamic pricing
• The outcome of a working group process involving multiple stakeholders
• The first large-scale scientific experiment focused on dynamic pricing for mass-market consumers
It’s being carried out to narrow the range of uncertainty in assessing the benefits of deploying advanced metering infrastructure in the state
EUCI Pricing Conference
13

C
HARLES
R
IVER
A
SSOCIATES

Who do we need to carry out a costeffectiveness analysis?
Implementing dynamic rates typically requires a significant investment in advanced metering infrastructure (AMI), which can be a billion dollar capital investment for some companies
• Additional incremental costs might include higher data processing costs, changes to billing and customer service systems, and customer education and marketing costs
To determine whether such an investment is warranted, a company must compare these costs with potential offsetting benefits in the form of:
• Avoided meter reading costs and other operational savings
• Avoided G, T and D capacity investments
• Lower energy costs
• Potential reductions in environmental externalities
• Reduced risk for default suppliers, due to lower price volatility and risk sharing
EUCI Pricing Conference
15

California’s standard practice manual provide a way of determining cost effectiveness
Test
Participant Test (PT) Is the participant
Total Resource Cost
Test (TRC)
Key Question better off?
Benefits
Bill Decrease
Customer Incentives
Is resource efficiency improved?
Avoided supply-side costs
Costs
Program Costs
(Participant)
Participation Fees
Program Costs (Total)
Ratepayer Impact Test
(RIM)
Are rates lowered?
Avoided supply-side costs
Participant Fees
Revenue loss
Customer Incentives
Program Costs
(Utility)
Utility Cost Test (UC) Are revenue requirements lowered?
Avoided supply-side costs
Participant Fees
Customer Incentives
Program Costs
(Utility)
EUCI Pricing Conference
16

C
HARLES
R
IVER
A
SSOCIATES

There are at least four sets of challenges to implementing dynamic pricing
Utility
• Financial, cultural and operational
Regulatory
• Educational and political
Customer
• Financial and educational
Technology
• Scale, scope and density economies
EUCI Pricing Conference
18

C
HARLES
R
IVER
A
SSOCIATES

The four climate zones of SPP
EUCI Pricing Conference
20

We were able to estimate a single, statewide demand model
For the CPP-F residential analysis, separate demand models were initially estimated for four climate zones. Ultimately, the data were pooled over the zones and binary variables representing individual zones were interacted with the price term to determine whether price responsiveness varied across zones
• The zonal binary variables were significant in Zones 3 and 4
However, these zonal binaries became insignificant in the regression models once we introduced interaction variables that allowed price responsiveness to vary with weather conditions and the ownership of central air conditioning (CAC) equipment
That is, the variation across zones is due to variation in weather and CAC ownership. Once these two factors are accounted for, there are no significant differences in price response across zones
EUCI Pricing Conference
21

C
HARLES
R
IVER
A
SSOCIATES

Elasticities for the CPP-F tariff
The statewide elasticity of substitution, derived from the CES model, is –0.069 for the typical weekday and the statewide daily price elasticity is –0.023.
• The elasticity of substitution varies significantly across climate zones, rising from a low of –0.032 in Zone 1 to –0.111 in Zone 4.
The statewide own-price elasticity of demand for peak period energy use is –0.094. It varies from a low of –0.055 in Zone 1 to a high of –0.139 in Zone 4.
• The statewide cross-price elasticity of demand for peak use is –0.140
The statewide own-price elasticity of demand for off peak use is
–0.151. It rises from a low of –0.127 in Zone 1 to a high of –0.172 in Zone 3.
• The statewide cross-price elasticity for off-peak use is +0.01.
EUCI Pricing Conference
23

The elasticity of substitution varies with weather, daytype and CAC ownership
Climate
Zone
1
2
3
4
State
Average Household Household with no
CAC
CPP day Non-CPP
Day
CPP Day Non-CPP
Day
-0.04
-0.06
-0.03
-0.05
-0.04
-0.05
-0.03
-0.04
-0.10
-0.12
-0.08
-0.09
-0.11
-0.07
-0.08
-0.10
-0.06
-0.07
-0.09
-0.05
Household with CAC
CPP Day Non-CPP
-0.07
-0.08
-0.11
-0.13
-0.10
Day
-0.06
-0.08
-0.10
-0.12
-0.09
EUCI Pricing Conference
24

Key findings for the CPP-V tariff
The elasticity of substitution is considerably larger on CPP days, with a value of –0.204, than on non-CPP days, with a value of –0.012
The elasticity of substitution on CPP days is much higher for the
CPP-V rate than for the CPP-F rate
However, it is important to note that these elasticities pertain to single family households with central air conditioning in climate zone 3 who had already volunteered into an earlier pilot program involving smart thermostats. They can be generalized to a similar population but not to the residential population as a whole
EUCI Pricing Conference
25

C
HARLES
R
IVER
A
SSOCIATES

Impact analysis is based on the weighted average prices for treatment customers in each climate zone
Residential Price For Consumer At Midpoint of Tier 3
(Weighted Average, Climate Zone 2)
40
30
20
10
0
80
70
60
50
71.5
23.7
7.5
51.7
21.3
11.0
61.0
22.5
Control Group
Average Price
13.3 cents/kWh
9.4
CPP-F High Ratio CPP-F Low Ratio
CPP Period Peak Period Off-Peak Period
Average
EUCI Pricing Conference
27

Impact of CPP-F rate on CPP and non-CPP days
Percent Change In Peak Energy Use
For Average SPP Prices
0
-5
-10
-15
-20
-8.35
-1.91
Zone 1
-9.61
-3.32
Zone 2
-13.37
-5.59
Zone 3
CPP Day
-6.83
-17.13
Zone 4
Non-CPP Day
-12.5
-4.8
All
EUCI Pricing Conference
28

C
HARLES
R
IVER
A
SSOCIATES

Ahmad Faruqui:
Demand curves for peak, off-peak and daily
Need to update use have been derived through simulation curves
Peak Period Demand Curve, Statewide
0.90
0.80
0.70
0.62
0.60
Average CPP Price
0.50
0.40
0.30
0.22
0.20
0.13
0.10
Average TOU Price
Average Control Price
0.00
0.95
1.00
1.04
1.05
Peak Period kWh/hour
1.10
1.12
1.15
1.16
1.20
EUCI Pricing Conference
30

Demand curves vary by climate zone
Peak Period Demand Curves by Zone
$0.900
$0.800
$0.700
0.62
$0.600
$0.500
$0.400
$0.300
$0.200
0.13
$0.100
$0.000
0.3
0.46
0.49
0.6
0.77
0.84
0.9
Zone 1
1.04
1.16
1.2
Peak Period kWh'
Zone 2 Zone 3
1.46
Zone 4
1.5
1.65
Statewide
1.72
1.8
EUCI Pricing Conference
31
2.02
2.1

Conclusions
Studies have shown that CPP can produce large economic gains for utilities and their customers
However, utilities and commissions face several barriers before such gains can be harnessed
Many utilities are seriously studying the economics of dynamic pricing and conducting experiments to overcome the barriers
The tools and data for analyzing and overcoming these barriers are available
Ultimately, the decision to roll out CPP as the default rate will partly be a philosophical decision, partly a political decision and partly an economic decision
EUCI Pricing Conference
32

C
HARLES
R
IVER
A
SSOCIATES

Bibliography
Ahmad Faruqui and Stephen S. George, “Dynamic Pricing for the Mass Market: The California experiment,” Public Utilities
Fortnightly, July 1, 2003, pp. 33-35.
Ahmad Faruqui, “Toward post-modern pricing: guest editorial,”
The Electricity Journal, July 2003.
Ahmad Faruqui and Stephen S. George, “Demise of PSE’s TOU program imparts lessons,” Electric Light & Power, January
2003, pp.1 and 15.
Ahmad Faruqui and Stephen S. George, “Reforming pricing in retail markets,” Electric Perspectives, September/October 2002, pp. 20-21.
EUCI Pricing Conference
34

Bibliography (continued)
Ahmad Faruqui and Kelly Eakin (editors), Electricity Pricing in
Transition, Kluwer Academic Publishers, 2002.
Ahmad Faruqui and Melanie Mauldin, “The barriers to real-time pricing: separating fact from fiction,” Public Utilities
Fortnightly, July 15, 2002, pp. 30-40.
Ahmad Faruqui and Stephen S. George, “The value of dynamic pricing,” The Electricity Journal, July 2002, pp. 45-55.
Ahmad Faruqui and Stephen S. George, “Time to get serious about time-ofuse rates,” Electric Light & Power, February
2002, Volume 80, Number 2, pp. 1-8.
Ahmad Faruqui, Hung-po Chao, Vic Niemeyer, Jeremy Platt and
Karl Stahlkopf, “Getting out of the dark,” Regulation, Fall
2001, pp. 58-62.
EUCI Pricing Conference
35

Bibliography (concluded)
Ahmad Faruqui, Hung-po Chao, Vic Niemeyer, Jeremy Platt and
Karl Stahlkopf, “Analyzing California’s power crisis,” The
Energy Journal, Vol. 22, No. 4, pp. 29-52.
Ahmad Faruqui, Hung-po Chao, Vic Niemeyer, Jeremy Platt and
Karl Stahlkopf, “California syndrome,” Power Economics, May
2001, Volume 5, Issue 5, pp. 24-27.
Ahmad Faruqui and Steve Braithwait, “The choice not to buy: energy savings and policy alternatives for demand response,”
Public Utilities Fortnightly, March 15, 2001.
Ahmad Faruqui and Kelly Eakin (editors), Pricing Electricity in
Competitive Markets, Kluwer Academic Publishing, 2000.
EUCI Pricing Conference
36