Automation Insight
April 2011
Does Giving Customers the Ability to
OPT-OUT of AMI Programs Create
New Problems?
By Afshin Tajian
During the long, drawn-out case of PG&E’s smart metering project, the
president of the California Public Utilities Commission (CPUC), Michael
Peevey, made an announcement in which he directed the president of
PG&E to “bring to this commission a proposal or a series of proposals
that will allow customers with an aversion to wireless devices the option
of being metered without the use of wireless technology.”1 Peevey
added: “In other words, I am directing PG&E to prepare a proposal for
our consideration that will allow some form of opt-out for customers
who object to these devices—at reasonable cost, to be paid by the
customers who choose to opt-out.”2
Although the recommendation to have customers opt-out might “calm
some of the emotion around this issue,”3 as Peevey stated, and earn
back some level of customers’ trust for the short term, implementing
this recommendation would potentially harm the smart grid movement
by settling on a lower version of an AMI system. This version would
change accepted AMI and data collection principles, and delay deployment, and it could set a poor model for future smart grid projects in the
residential sector.
Negative public perception toward PG&E has arisen since the 2009
class action lawsuit, which in itself followed the company’s bankruptcy
in the midst of the California energy crisis of 2001-2001. Thus, it’s
not entirely shocking that a large number of customers may want to
distance themselves from the noise and the fear of the unknowns
associated with PG&E’s smart grid deployment by choosing this option.
Their personal decisions, however, would have societal impacts that
affect many more people.
Assuming that even a small number of customers chose to opt-out, the
situation could potentially erode the value of the economic and performance benefits that were projected for full-scale deployment. A mixed
environment of smart and traditional meters inevitably would create a
hodge-podge system that may ultimately require a new set of tools and
processes for management and maintenance. Such a constantly changing
environment would require, at a minimum, a customized meter reading
practice—one that would need to know who has a meter that must be
manually read today and who in the route would have one in the next
cycle. This environment ultimately could result in disparities among meter
data management, data analysis, and the billing process, which likely
could defeat significant meter reading values behind the smart metering
system in the first place and impact plans for using this information for
more effective smart-grid operations in the future.
As utilities migrate from their older types of metering methods toward AMI,
they could gradually limit the meter reading routes in each area or city,
and will eventually seek to eliminate them when the entire system in the
area is mature enough for remote reading meters. This approach could be
compromised if there are adopters of the opt-out option. Also, with smart
meters, data is not limited to billing only; it contains outage information,
tamper indication, power quality, and more, which a supporting communication system collects more than once a month. There are many internal
uses for frequently transmitted information that is captured by a data
acquisition system or meter data management system, such as monitoring trends and power quality, and plotting demand graphs for small and
large geographical zones, which provide significant value to help optimize
responses to identified issues like outages, alarms/events, power quality
abnormalities, and over/under voltages.
For a utility to have a mixed environment of both old and smart meters,
the management would now need to optimize their focus of a “meter-forbilling-only” philosophy and practice, and possibly forego the value-added
services of frequently transmitted data that goes beyond the revenue cycle
needs. If data for a large number of customers remains limited to consumption data (kilowatt-hours), data analysis, and trend analysis for any other
parameter such as power quality, then it becomes less meaningful or limited
to those areas where a significant number of volunteers participate in these
programs. Likewise, monitoring energy consumption and demand for an
entire territory or large zones in any time period smaller than a month (e.g.,
weekly or daily) would become almost impossible. This could push the utility
back to make projections from sampling and surveying, which could result in
inaccuracies and ineffectiveness in the data that major visions of smart grid
initiatives such as demand response programs are dependent on.
Since the business case and economics of AMI are based on a saturation
model that includes uniformity of coverage, rate designs, and time of use
programs, such offerings have their foundation in uniform services. Customers’ option to opt-out from this large-scale project will make the business
case analysis of the project even more difficult for the utility.
Furthermore, utilities would need to track customers that still use old meters
and customers that have the new ones. This new subclass of customers
would lead to stock and inventory management database issues. Also, the
call centers would have to be provisioned to distinguish these subclasses
and offer vastly different treatment regimes. This would become more
complicated as customers move and churn, since the new owner of a house
or property may choose a different metering option than the previous owner
had. These issues would not be impossible to resolve, but they would be
time consuming and costly for any utility regardless of its size.
In regard to communication networks, design and installation of an appropriate system to communicate with a large number of metering devices would
require knowledge of their quantities and positions—information that the
utility will no longer possess. Local area networks (LAN) are usually designed
to transmit metering data from the point of metering to the backhaul
infrastructure. Wide area networks (WAN) are designed to carry data to
the meter data management systems. The best solution for a utility with a
mixture of remote-reading and manual-reading meters would be to design
and implement an inclusive and scalable communication infrastructure that
accommodates the maximum and minimum service coverage. The utility
most likely would have to opt for the maximum condition, even if today there
were less need for that, to avoid risks of major upgrades in the future due to
more manual-reading meters that may later join the remote-reading system.
Such a large infrastructure would function far less efficient, since it would
communicate with only parts of the metering system at any given time.
The CPUC, which is focused on making California a national leader in
modernizing the electric grid4, may now be setting a precedence that could
become a wrong model for energy utilities and their customers around
the nation, by implementing smart grid systems that sacrifice many of the
benefits of new technology.
Some of the main objectives raised by customers in regard to smart meters
have been: fire safety, wireless signal power (or electromagnetic field radiation), and metering accuracy.
There is no difference between traditional and smart meters in terms of the
fire hazard associated with electric meters. In the rare occasion that a meter
is not installed correctly/tightly into the socket, a situation known as “hot
socket” could develop, which can cause the temperature at the connection
point to rise to a potentially hazardous level. Utility employees throughout
the country usually go through special training to prevent and deal with hot
socket incidents. This situation does not depend on the type of meter. With
smart meters, the utility receives alarms when a major parameter changes
(e.g., loss of a phase), so it is more likely to be notified and react to such a
condition and prevent consequences such as fire.
Research indicates that the power range of wireless signals from smart
meters is much less severe than customers’ WiFi networks in their homes
or places of work or recreation (including Starbucks and McDonalds), which
are likely located near cell towers or often accessed by customers that use
their wireless or cell phones to make phone calls.
It is crucial for utilities to educate customers about the myths and facts
of communication with smart meters. Not all smart meters communicate
through wireless meshes. A considerable portion of such communication
takes place through industrial wires such as fiber optics, phone lines, serial
communication wires, and power line carriers. Meters that do communicate
wirelessly transmit signals in power ranges much lower than the limits set
by the U.S. Federal Communications Commission (FCC). The Maine Center
for Disease Control & Prevention (an office of the Maine Department of
Health and Human Services) conducted a health study on smart meters
(http://www.maine.gov/dhhs/boh/smart_meters.shtml), reported to the
Maine Public Utilities Commission. As part of this study, a comparison was
made between the non-ionizing radiation of smart meters and other wireless
devices used in today’s common households. In the following table, the findings suggest that the smart meter’s average and maximum radiation power
are not greater than those of a regular wireless router or cell phone.
Page 2
Frequency in
GHz
Power (max) in
Watts
Power (average)
Watts
2.4
1
0.100
G router
2.4
1
depends on use
N router
2.4 or 5.0
1
depends on use
Cordless Phone
2.4
0.25
0.010
Cell Phone
1.9
3
depends on use
FM Radio Tower
0.1
100,000
100,000
Cell Phone Tower
0.8 to 1.99
48,000
depends on use/loc
Item
Smart meter
Also, a recent research study by the Electric Power Research Institute (EPRI)
indicates that even radiation generated by a rack of 10 smart meters has
much less power than the limits set by the FCC.5
In regard to customers’ concerns about inaccurate billing, a significant
number of evaluation tests on smart meters by various entities under various
conditions have now proven that smart meters are more accurate than traditional ones in many ways, from the class accuracy under standard condition
(maximum ±0.2% or ±0.5% for smart meters vs. ±2% error for most
traditional meters), to operating with consistent accuracy under unstable
conditions such as temperature, voltage, load, and frequency.
Peevey had also previously said, “We spent $1.5 million with a firm in Houston who looked into the accuracy of the smart meters because that was
the first claim that people made. We found them to be 99.9995 percent
accurate, much more accurate than the current meters that can be off by 2
percent. Frankly, the problem has been that old meters, when they ran slow,
nobody complained.”6
The CPUC should rely on the outcomes of scientific and economic investigations into smart meters and educate customers as much as possible
about the benefits and nature of a smart grid and energy management.
In addition, the CPUC should support the utilities to achieve their visions,
remain active in the irreversible path of the industry, and try to solve the
problems as they appear, instead of setting a precedent, which would offer a
solution that makes the problem even more complex.
References:
1. “Peevey orders PG&E to let customers opt-out of AMI,” SmartGridToday.
com, March 11, 2011,
www.smartgridtoday.com/members/Peevey_orders_PG.cfm.
2. Ibid.
3. Anna McCarthy, “SmartMeter opt-outs proposed,” Mill Valley Herald,
March 16, 2011, http://is.gd/R42A1b.
4. California Public Utilities Commission, “Fact Sheet: California Leads the
Nation in Modernizing its Electric Grid,” July 2010, 1,
www.cpuc.ca.gov/PUC/energy/smartgrid.htm.
5. Electric Power Research Institute, “Radio-Frequency Exposure Levels
from Smart Meters: A Case Study of One Model,” Southern California Gas
Company website, February 2011,
www.socalgas.com/documents/ami/EPRI_1022270.pdf.
6. “CPUC President Bullish on Smart Meters,” SmartMeters.com, March 14,
2011, www.smartmeters.com/the-news/2034-cpuc-president-bullish-onsmart-meters.html.
7. Application of Pacific Gas and Electric Company (U 39 M) for Approval
of Modifications to its SmartMeterTM Program A. 11-03-014, before the
Public Utilities Commission of the State of California, March 24, 2011,
http://media.baycitizen.org/uploaded/documents/2011/3/pge-smartmeterproposed-opt-out-program/PGEOptOut.pdf.
8. Jesse Burst, “PG&E files game-changing smart meter opt out plan. But
will it work?” SmartGridNews.com, March 25, 2011,
http://www.smartgridnews.com/artman/publish/news/PG-E-to-anti-smartmeter-customers-Sure-we-ll-shut-em-off-for-a-price-3577.html.
For information on the 2009 class action lawsuit against PG&E, please visit:
http://www.nbcbayarea.com/news/local/PGE-Faces-New-Class-ActionLawsuit-104385644.html.
In its response to the CPUC’s order, which was filed on March 24, 2011,
PG&E has offered to allow customers the option to have their meters’ radios
turned-off. To do this, the customer would incur “a reasonable up-front
charge and an ongoing monthly charge—either in the form of a fixed
monthly fee or a volumetric per-kWh rate adder applied to the customer’s
energy usage.”7 In this proposal, PG&E presented a table that includes various fixed and monthly options for customers, with figures that are subject to
change based on the actual number of customers that choose to opt-out.
Early reports indicate that the customers are not pleased with this proposal.8
Page 3
Engaging the customer — The power
behind the meter
Utility customers continue to demand greater reliability and cost containment
even as their lives become more electricity-intensive. While the utility industry
has achieved remarkable gains in the reliability, cost, and environmental
impact of generating and transmitting electricity, the same cannot generally
be said for the delivery aspects of the business. This shortcoming has, in
turn, limited the gains that can be made in the other parts of the value chain.
Enter smart grid.
The global energy delivery industry is moving at various paces toward
adopting smart grid distribution technology. And as the industry makes this
infrastructure transition to an intelligent network there is growing recognition
that the information aspects of this network pose new challenges and opportunities with respect to the distribution customer relationship.
In the Americas, stories of customer backlash and regulatory rejection of
smart grid projects that do not provide clear customer benefits have underscored the magnitude of the challenge in the past year. The clear message
for energy delivery companies is that they must engage their customers and
regulatory stakeholders in ways they have generally not done before.
At the same time, it is apparent to all stakeholders that the deployment of a
more intelligent network becomes the strategic enabler for a host of services
and relationships—some not yet even contemplated. Indeed, there is
general agreement among executives polled by KEMA that the introduction
of intelligent networks and digital technology into the distribution system on
both sides of the customer meter could lead to the traditional utility company
being disintermediated from its customers.
How then, do the energy industry and its stakeholders consider the investments to be made? What role should third parties play in the evolution of
the network? What business models should evolve to enable the full value
of energy resources to be captured by society and individual investors? How
can investments made today enable the customer relationship of the future?
An American focus notwithstanding, we anticipate that this third volume
in our Utility of the Future Leadership Guidebook series provides the
knowledge to help build more engaging customer relationships and make
informed technology and business model choices.
Drawing on concrete experience primarily in North America, the volume
documents changing customer attitudes toward energy and trends that are
changing use profiles. From the perspective of the Americas, we examine
market structures, look at technologies that are changing the relationship
customers have with their utilities and energy providers, and provide analysis
of various product and pricing programs and results. Finally, we bring it all
together—the automated smart grid, customer behavior, and renewable
generation—in a vision of how the utility of the future may operate, as a kind
of virtual power plant.
For more information or to order a
copy of the guidebook, visit
www.kema.com/PowerBehindtheMeter.
4th Annual Utility of The Future
Leadership Forum
Utility industry leaders and experts will convene June 6-8 in Denver,
Colorado, for KEMA’s 2011 forum: Shaping the Future. Discussions will
focus on industry game changers, new business models, and customer
engagement to build for the future. Register at:
www.kema.com/UtilityFuture2011/.
As KEMA globally addresses these questions for our clients, a common
theme has emerged. Leveraging lessons learned and research gathered
over the last two decades in helping our clients understand how their
customers respond and adapt to new programs and technologies, we have
developed unique insights that can inform and illuminate our path moving
forward. KEMA’s third Utility of the Future leadership guidebook, Engaging
the Customer: The Power Behind the Meter, seeks to address how customer
interactions may shape the future of the industry and how stakeholders can
leverage these relationships.
Page 4
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