Dynamic Pricing - Potential and Issues
Joe Wharton and Ahmad Faruqui
Kansas Corporation Commission Workshop on
Energy Efficiency March 25, 2008
2
Policy of Dynamic Pricing raises important questions
1. What is the potential impact of dynamic pricing on peak demand?
2. What is the value of this demand response (DR)?
3. How much does customer price responsiveness vary by customer and region?
4. How can rate design make dynamic pricing more attractive to customers?
3
Dynamic pricing can lower system peak demand by 5 percent, considerably below the economic and technical potential
Estimates of Total Potential Peak Demand Reduction
5%
15%
52%
0%
10%
20%
30%
40%
50%
60%
Market Projection Economic Potential Technical Potential
Red
uct
ion
in
Pea
k D
eman
d
4
A 5 percent reduction in US peak demand could be worth $31 billion over a 20-year period, just on avoided costs
Assumptions
• 5% demand reduction in 757 GW
• $52/kW-year capacity price
• 20 year horizon
• 15% discount rate
• 2% peak growth rate
• Avoided cost of energy is 36% of avoided cost of capacity*
• Value of wholesale price reduction is 278% of avoided cost of capacity*
*Derived from a study on the value of DR in PJM:
The Brattle Group, 2007, Quantifying Demand Response Benefits in PJM, Prepared for PJM and MADRI NPV of Avoided Costs = $31 billion
Annual Value of a 5% Reduction in Peak Demand
5.50.7
2.0
0.0
1.0
2.0
3.0
4.0
5.0
6.0
Avoided Costs Wholesale Price Reduction
An
nu
al F
inan
cial
Val
ue
(Bil
lio
ns
of
$)
Avoided EnergyCost
Avoided Capacity
Cost
5
There is a range of pricing options – from static (fully hedged) to dynamic
Risk (Variance in
Price)
Reward (Discount from Flat
Rate)
10%
5%
10.5
RTP
CPP-F
VPP
Flat Rate
TOD
Seasonal Rate
CPP-V
0%0
PTR?
Inverted Tier Rate
Risk Averse Customers
Risk Seeking Customers
6
What peak demand reductions come from dynamic pricing - results from pricing pilots
7
Across the TOU pilots, there is solid evidence of demand response
Percentage Reduction Estimates from Reviewed TOU Pilot Programs
0%
5%
10%
15%
20%
25%
30%
35%
Ontario- 1 Ontario- 2 SPP PSEG PSEG ADRS- 04 ADRS- 05 Gulf Power-1
Pilot Program
% R
edu
ctio
n i
n L
oa
d
TOU TOU w/ Tech
8
Dynamic pricing gives rise to greater peak reductions
Percentage Reduction Estimates from Reviewed CPP/PTR Pilot Programs
0%
10%
20%
30%
40%
50%
60%
Pilot Program
% R
edu
ctio
n i
n L
oa
d
CPP PTR CPP w/ Tech
9
The Peak Time Rebate (PTR) rate has achieved demand response in two pilots
Comparison of Peak Time Rebate (PTR) Program Tariffs and Resulting Impacts
-0.30
-0.20
-0.10
0.00
0.10
0.20
0.30
0.40
0.50
Ontario Anaheim
Pilot Program
Ra
te (
$/k
Wh
) o
r
Lo
ad
Im
pa
ct (
as
a f
ract
ion
of
tota
l lo
ad
)
Existing Off-Peak Mid-Peak
Peak PTR Load Impact
10
Different Critical Peak Pricing (CPP) tariffs induce different load impacts during “event days”
Comparison of Critical Peak Pricing (CPP) Program Tariffs and Resulting Impacts
-0.50
-0.40
-0.30
-0.20
-0.10
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
PSE&G Ontario AmerenUE SPP Idaho
Pilot Program
Ra
te (
$/k
Wh
) o
r
Lo
ad
Im
pa
ct (
as
a f
ract
ion
of
tota
l lo
ad
)
Existing Off-Peak Mid-Peak
Peak CPP Load Impact
Note: PSE&G load impact on CPP days is not provided in the reviewed study. The load impact is calculated using the reported kWh reductions and an estimate of consumption during peak on CPP days.
11
Enabling technologies magnify demand response
Role of Technology on Pilot Program Impacts
0%
5%
10%
15%
20%
25%
30%
35%
40%
PSE&G (TOU) PSE&G (CPP) SPP (CPP) AmerenUE-2004 (CPP)
AmerenUE-2005 (CPP)
Pilot Program
% R
edu
ctio
n i
n L
oa
d
No Technology Technology
Note: PSE&G load impacts on CPP days are not provided in the reviewed study. The load impacts are calculated using the reported kWh reductions and an estimate of consumption during peak on CPP days.
12
Mass Market customers’ response varies by enabling technologies and the customers’ end uses
Peak Demand Reduction by Customer Type
-35%
-30%
-25%
-20%
-15%
-10%
-5%
0%
0.00 0.20 0.40 0.60 0.80 1.00
Critical Peak Rate ($/kWh)
De
cre
as
e i
n C
riti
ca
l P
ea
k D
em
and
Non-CAC
Average
CAC
CAC w/ Technology
13
Applying these relationships, one expects to find customer responses will vary by region
Demand Response Comparison Across Regions
-25%
-20%
-15%
-10%
-5%
0%
0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40
Critical Peak Rate ($/kWh)
Pea
k D
eman
d R
edu
ctio
n
HawaiiPacific NorthwestBaltimoreCalifornia - Zone 4
14
But there is equity issue: could Bills rise for 50% of the customers choosing dynamic pricing
Distribution of Bill Impacts
-15%
-10%
-5%
0%
5%
10%
15%
20%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Percentile of Customer Base
Ele
ctri
city
Bil
l In
crea
se (
Dec
reas
e)
Customers with Peakier ConsumptionCustomers with Flatter Consumption
15
A discount could be build-in for the “insurance or risk premium” incorporated in flat or hedged rates
• Empirically, this “insurance premium” is estimated to range from 3 to 13 percent for different types of time-varying rates
• Illinois used a value of 10 percent in its RTP pilot for residential customers
• Monte Carlo simulations with a standard financial equation suggest a mean value of 11 percent
• A conservative estimate is 3 percent
16
By adjusting for conservative risk premium, dynamic pricing rates become attractive for 70% of customers
Distribution of Bill Impacts
-25%
-20%
-15%
-10%
-5%
0%
5%
10%
15%
20%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Percentile of Customer Base
Ele
ctri
city
Bil
l In
crea
se (
Dec
reas
e)
Revenue neutral
Credit for hedging cost premium
Customers with Peakier ConsumptionCustomers with Flatter Consumption
17
Also factoring in the demand response expands the appeal to 90%
Distribution of Bill Impacts
-25%
-20%
-15%
-10%
-5%
0%
5%
10%
15%
20%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Percentile of Customer Base
Ele
ctri
city
Bill
Incr
ease
(D
ecre
ase)
Revenue Neutral
Credit for Hedging Cost Premium
Demand Response Plus Credit for Hedging Cost Premium
Customers with Peakier ConsumptionCustomers with Flatter Consumption
18
Conclusion: the way forward should involve a careful look at the range of dynamic pricing options
Risk (Variance in
Price)
Reward (Discount from Flat
Rate)
10%
5%
10.5
RTP
CPP-F
VPP
Flat Rate
TOD
Seasonal Rate
CPP-V
0%0
PTR?
Inverted Tier Rate
Risk Averse Customers
Risk Seeking Customers
19
Footnotes
See A. Faruqui and L. Wood, Quantifying the Benefits of Dynamic Pricing in the Mass Market, for EEI, Jan 2008.
Note: Percentage reduction in load is defined relative to the different bases in different pilots. Following notes are intended to clarify these different definitions. TOU impacts are defined relative to the usage during peak hours unless otherwise noted. CPP impacts are defined relative to the usage during peak hours on CPP days unless otherwise noted.
• Ontario- 1 refers to the percentage impacts during the critical hours that represent only 3-4 hours of the entire peak period on a CPP day. Ontario- 2 refers to the percentage impacts of the programs during the entire peak period on a CPP day
• TOU impact from the SPP study uses the CPP-F treatment effect for normal weekdays• PSEG program impacts represented in the TOU section are the % impacts during peak period on non-CPP days.• PSEG program impacts represented in the CPP section are derived using the reported kWh reductions and the
estimated consumption during the peak period on CPP days• ADRS- 04 and ADRS- 05 refer to the 2004 and 2005 impacts. ADRS impacts on non-event days are represented
in the TOU with Tech section• CPP impact for Idaho is derived from the information provided in the study. Average of kW consumption per hour
during the CPP hours (for all 10 event days) is approximately 2.5 kW for a control group customer. This value is 1.3 kW for a treatment group customer. Percentage impact from the CPP treatment is calculated as 48%.
• Gulf Power-1 refers to the impact during peak hours on non-CPP days while Gulf Power-2 refers to the impact during CPP hours on CPP days.
• Ameren-04 and Ameren-05 refer to the impacts respectively from the summers of 2004 and 2005.• SPP- A refers to the impacts from the CPP-V program on Track A customers. Two-thirds of Track A customers
had some form of enabling technologies.• SPP-C refers to the impacts from the CPP-V program on Track C customers. All Track C customers had smart
thermostats.