Transcript Smart Meters” An Unwise Choice for Low

“Smart Meters”/Prepayment Meters:
An Unwise Choice for Low-Income
Presentation to Indiana Community Action Conference
Presented by:
Roger D. Colton
Fisher, Sheehan & Colton
Belmont, MA
October 2008
What is a “smart meter”
“. . .a concept embracing two distinct
elements: meters that use information and
communications systems that can capture
and transmit energy use information as it
happens, or almost as it happens.”
New York State Research and Development Authority (NYSERDA)
The objectives of “smart meters”
 “Real time pricing”
• Assumes viability of “price signals”
 “Demand response” strategies
• Assumes capacity of consumer to respond to
price signals
Smart meters and rate impacts

Sharp increase in value of “rate base”
• Substitute investment for companies that do not/cannot
invest in power plants as they used to do.

Replacement of old (and depreciated] meters
with new [and undepreciated] meters.
• Continue to pay for remaining depreciation on old meters
anyway.

Rapidly obsolete --quick depreciation
• 30 year depreciation vs. 7 year depreciation
• Akin to telecommunications equipment
Costs beyond the cost of the meter:
 Cost to accumulate data
 Cost to archive data
 Cost to access and process data
Electric usage by income
Total
<
$10 $30 $50,000 Below
$10,000 $29,999 $49,999 or more 100% FPL
Total kWh
10,656
7,290
8,906
10,545
13,131
8,152
Appliances (not
fridge)
5,435
3,239
4,335
5,360
6,998
3,889
Space heating kWh
3,524
2,837
3,203
3,624
4,014
3,015
Heated Square feet
1,399
786
1,035
1,296
2,072
866
Central a/c’g use by income (cont’d)
2001
Total
< $10,000
$10 - $25,000 $25 - $50,000
$50,000 or
more
Use central air
54.8%
33.7%
49.3%
57.2%
66.8%
All summer
26.5%
16.6%
21.8%
27.7%
33.4%
Quite a bit
11.3%
6.4%
9.2%
11.4%
14.9%
Only a few times
15.7%
9.1%
15.7%
16.6%
17.,8%
Not at all
1.3%
Q
2.6%
1.1%
0.8%
Low-income energy risks by risk attribute
High Winter
Bill Burdens
No Control
over
Expenses
1
3
No HH
Savings
Long-term
Recent
1.02
2.19
1.00
Unforeseeable
Foreseeable
1.86
2.24
3.00
Controllable
Uncontrollable
1.76
1.81
2.86
Permanent
Temporary
1.68
1.68
2.86
SOURCE: Roger Colton (March 2006). Georgia REACH Project Energize: Final
Program Evaluation, Georgia Department of Human Resources: Atlanta (GA).
Alternatives to smart meters
 Inclining block rates
 Seasonal rates
 Direct load control
• Baltimore Gas and Electric Energy Saver Switch
• Florida Power & Lights: “On Call” program
• Allegheny Power: programmable thermostat
switch
Recommendations:
 Target to high usage with usage profile of
peak contribution.
 Costs to be paid by customers who take
service that requires use of such meters.
 Shall not require to install as condition of
receiving basic service.
 State regulators to find, after hearing that
benefits exceed the costs.
Recommendations (cont’d):

Proponents must test, and document, the impact
on variety of residential customers
• Housing type, usage profiles, income levels,
demographic characteristics.
Must be completely voluntary, with no costshifting to nonparticipants or to those who use
less than average consumption.
 Must not make condition as a result of
nonpayment or inability to pay.

Prepayment meters:
Payment troubles and low-income status
 Census: 32.4% of LI behind vs. 9.8% non-LI
 Similar state figures:
• Indiana ( 40% 20%)
• Iowa (25% / 12%)
• Pennsylvania (40% / 15%)
Prepayment meters:
The narrowing of choices
 Lack of payment plan option
 Lack of short-term arrears option
 NEADA surveys (2004 and 2005)
•
•
•
•
Medical care
Food
Home energy
Consumer debt
Prepayment meters:
Consider the working poor
76 percent of workers in the bottom quartile of
family income lack regular sick leave.
 58 percent of workers in bottom quartile do not
have consistent vacation leave.
 78% of workers beneath the median income level
cannot choose or change their starting and
quitting times, or take days off to care for their
sick children.

Prepayment meters:
The problem of hidden shutoffs
Rather than having a disconnect for non-payment,
the meter simply runs out of money.
 Great Britain: Nearly 4 million customers use
prepayment meters.
 One-third of gas customers self-disconnected.
 More than one-quarter of electric customers selfdisconnected.
 Compare to 5% - 6% disconnect rate

Prepayment meters:
Salt River Project not a good comparison
 58% are homeowners
 Average family income: $31,000
 Average family: 4 persons
 Average customer: > 10 years
Prepayment meters:
Not good economic sense
 Cost of meters: $7.50/mo x 12 mos =
$90/year
 Average savings: 10% x 7,000 kWh x
$0.10/kWh = $70
 SRP savings only arose from aggressive
energy education program.
The fallacy of “consent”
in the face of disconnection
 Consent is vitiated by “duress”
 One recognized cause of duress is
“economic coercion”
 Economic coercion occurs when consumer
believes no real choice.
 When duress is present, no “consent” can
be found.
Prepayment meters:
The fallacy of the “price signal”
 Don’t pay full bills with which to begin
 Make payment trade-offs on a regular basis.
 Programs such as LIHEAP destroy “price
signals”
 Programs such as budget billing destroy price
signals
 Assumes ability-to-pay—response to prices
Summary of conclusions:
Inappropriate to
 Require utilities to install
 Require customers to use
 Allow installation unless cost-justified.
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