WILL THE SMART GRID
PROMOTE SMART CUSTOMER
DECISIONS?
Ahmad Faruqui, Ph.D.
Principal, The Brattle Group
925.408.0149
The Smart Grid enables energy efficiency and
demand response
• Rising fuel prices and capacity costs, shrinking reserve
margins and greenhouse gas emissions are setting the
policy maker’s agenda today
• Utilities and state commissions are placing a renewed
emphasis on the demand side of the equation to deal with
these issues
• Both energy efficiency and demand response can play a
vital role in meeting future customer energy needs while
controlling rising bills and making sure the lights stay on
• The Smart Grid opens new vistas when it comes to dealing
with tomorrow’s customers who will be born into the digital
age
2
In the new century, we need a multi-faceted
approach for reaching the customer
• Information about energy costs as they are incurred
and ideas on how to manage those costs
• Codes and standards for new appliances, buildings
and industrial processes
• Enabling technologies that control costs in real-time
conditions such as two-way communicating
thermostats
• Rebates and financing for accelerating the adoption
of smart end-use technologies
• Smart rate design such as inclining block rates and
dynamic pricing rates
3
The smart grid will help customers make smart
energy buying decisions
¾Providing real-time feedback to customers on their
energy consumption should help them better
manage their energy behavior
¾New empirical evidence from a number of pilots
shows that in-home displays and similar devices
that are enabled by the smart grid can lower energy
use by up to 6 percent
¾This has been observed to happen even with
existing rate designs
¾Of course, greater impacts will be observed if the
rate designs are changed as well
4
What will be the likely impact of
inclining block rate designs?
5
Four illustrative inclining block rate designs
30
Average Customer
Cents / kWh
25
Rate D
20
15
Rate C
10
Rate B
5
Existing
Flat Rate
Rate A
0
0
200
400
600
800
1,000 1,200 1,400 1,600 1,800 2,000
kWh / Month
6
Representative customer billing distribution
Percent of Customer Population
16%
14%
12%
10%
8%
6%
4%
2%
0%
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 (kWh/month)
7
Energy use could decline by up to 5.9 percent and
customer bills by up to 9.1 percent
Price Elasticity
Short Run
Long Run
Rate A
Mean
Std Dev
Mean
Std Dev
Long Run
-2.2%
0.8%
-6.7%
2.4%
-1.0%
0.3%
-3.1%
1.1%
Rate D
-0.5%
0.2%
-0.7%
0.4%
Avg Percent Change in Class Revenue
Rate B
Rate C
Rate D
Rate A
Price Elasticity
Short Run
-5.9%
2.0%
-18.4%
6.5%
Avg Percent Change in Usage
Rate B
Rate C
Mean
Std Dev
Mean
Std Dev
-9.1%
3.1%
-28.4%
9.9%
-3.1%
1.1%
-9.4%
3.4%
-1.0%
0.4%
-3.3%
1.1%
-1.4%
0.5%
-2.6%
1.0%
8
Price response mitigates the impact on high use
customers by shifting the breakeven point
Change in Monthly Bill
30%
20%
10%
0%
-10%
-20%
Break-even
point
-30%
-40%
-50%
No price elasticity
-60%
With price elasticity
Tier 1
-70%
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
9
What will be the likely impact of
The likely
impactpricing
of dynamic
rates
dynamic
ratepricing
designs?
10
An illustrative dynamic pricing rate design
Price Duration Curve
1.20
Rate ($/kWh)
1.00
Cost-Based CPP/TOU Rate
0.80
0.60
0.40
Current Rate
0.20
0.00
0
500
1000
1500
2000
2500
Number of Hours in Summer Period
11
A
na
O hei
nt m
a
O riont
ar 1
io
-2
O
nt
a
O riont
ar 1
io
-2
A SPP
us
tr
al
ia
A Id
m ah
er o
A e nm
er 04
en
-0
5
0%
PTR
CPP
SP
PSP A
A
m Per C
A en
m -0
er 4
e
A n- 0
D
R 5
A S- 0
G DR 4
ul SfP 0
ow 5
er
-2
% Reduction in Load
Customers respond to dynamic pricing
60%
50%
40%
30%
20%
10%
CPP with Technology
12
Enabling technologies magnify demand response
Role of Technology on Pilot Program Impacts
40%
No Technology
Technology
% Reduction in Load
35%
30%
25%
20%
15%
10%
5%
0%
PSE&G (TOU)
PSE&G (CPP)
Note: PSE&G load impacts on CPP days are not provided in the reviewed study.
The load impacts are calculated using the reported kWh reductions and an
estimate of consumption during peak on CPP days.
SPP (CPP)
Pilot Program
AmerenUE2004 (CPP)
AmerenUE2005 (CPP)
13
Customer response in the mass market varies by
segment
Decrease in Critical Peak Demand
Peak Demand Reduction by Customer Type
0%
-5%
-10%
-15%
-20%
-25%
-30%
-35%
0.00
Non-CAC
Average
CAC
CAC w/ Technology
0.20
0.40
0.60
0.80
1.00
Critical Peak Rate ($/kWh)
14
Crediting customers for the hedging premium
broadens the appeal of dynamic pricing
Distribution of Bill Impacts
High CPP Rate
Electricity Bill Increase (Decrease)
50%
Revenue Neutral
40%
3% Premium, No Demand Response
30%
3% Premium, With Demand Response
20%
10%
0%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
-10%
-20%
-30%
-40%
Customers with Flatter Consumption
Customers with Peakier Consumption
-50%
Percentile of Customer Base
15
The way forward is to offer customers a menu of
pricing options
Reward
(Discount
from Flat
Rate)
Less
Risk Averse
Customers
More
Risk Averse
Customers
10%
RTP
VPP
5%
CPP
TOU
Seasonal Rate
Inverted Tier Rate
Flat Rate
0.5
1
Risk
(Variance in
Price)
16
The smart grid enables smart energy buying
decisions
• Providing real-time feedback to customers can lower
energy use by a few percentage points
• Inclining block rates can reduce energy consumption
by up to 6 percent in the short run and may
additionally lower peak demand
• Dynamic pricing rates can reduce demand by 13 to 27
percent during critical peak periods
• Taken together, these measures can make a
substantial contribution to meeting Indiana’s future
energy needs at a reasonable cost
17
The digital library
¾ Ahmad Faruqui, “Retooling Rate Design for Energy Efficiency,”
forthcoming, Public Utilities Fortnightly, August 2008
¾ Ahmad Faruqui and Sanem Sergici, “The Power of Experimentation,”
Discussion Paper, The Brattle Group, May 11, 2008 (Downloadable from
www.brattle.com)
¾ The Brattle Group, “Quantifying the benefits of dynamic pricing,” Edison
Electric Institute, January 2008 (Downloadable from www.eei.org/ami)
¾ Plexus Research, Inc., “Deciding on Smart Meters,” Edison Electric
Institute, September 2006 (Downloadable from www.eei.org/ami)
¾ Federal Energy Regulatory Commission, “Demand Response and
Advanced Metering,” Staff Report, August 2007 (Downloadable from
www.ferc.gov)
¾ US Department of Energy, “Benefits of Demand Response in Electricity
Markets and Recommendations for Achieving Them,” February 2006
(Downloadable from www.oe.energy.gov/information_center/reports.htm)
18