Intelligent Utility Jan-Feb 2013

eported out or is predicted out, it’s
in the list,” Rhoades said. “So it comes
back, and the meters start coming off
the list, and if a meter does not report
back in, the system automatically
pings the meter and determines if the
outage is cleared or not. If the outage
is not cleared, naturally operations
would roll somebody there. We can
do it all in a matter of 10 minutes
versus waiting until somebody makes
a phone call. It has improved our
outage management system and
restoration times. It was one of the
first things we did.”
Rhoades said that, to make it all
work, a utility has to have its interfaces
right, and it has to
monitor those interfaces.
At Southern “
Company, everything
runs on a bus system,
so it is essential to
make sure the bus systems
are operational,
“Because once you
start depending on all
these outages coming
in from your meters,
you need to make sure that systems
are up and operational. It’s taken us a
while to get all the right monitoring
points to make sure they’re flowing
properly,” Rhoades said, “But we got
all that done.”
Alabama Power had some problems
with the ping response time from its
OMS system that reduced the success
rate below an acceptable level, but
setting the priority messages correctly
fixed the problem. “Everything works
fairly well, and it’s a good project,” he
said. “It really helps our distribution
people in managing outages.”
ONCOR Theft detection
and outages
Oncor has 175,000 smart meters
left to install to reach its goal of
3.2 million installed. Jonathan
Pettit, advanced meter system
(AMS) manager at Oncor Electric
Delivery, said the key at Oncor is AMS for a variety of reasons, including analytics
and automation.
“Currently, we have about 250,000 automated operations a day for which, in
the past, we would have had to roll a truck. To date, the automation has saved
between 4 million and 4.5 million truck rolls, along with the associated fuel
and man hours.”
Analytics also help Oncor protect its revenue from loss through theft. The
protection involves the use of manual queries. Pettit said that although the queries
are automated, Oncor doesn’t kick out service orders automatically. He said
the utility wants to reach the point of 90 to 95 percent assurance of true theft or
revenue protection. “The processes have an average 80 percent hit rate in a range
from 60 to 90 percent,” Pettit said. “The one that’s 90 percent is about ready to be
automated. There are many ways to steal electricity, and it’s amazing what people
will do. You’ll find that theft is probably twice as high as you ever thought it was,
and people are twice as smart as you thought they were, too.”
According to Pettit, there is an urban myth that meters give false indications
of outages. “They actually are telling you there’s something wrong with your
secondary,” he said. “Even our meter vendor hadn’t
thought about this. But in 100 percent of the cases
where we had a false indication, we had a loose
terminal or a problem with the transformer. With
predictive analytics, you can learn that there’s
something wrong out there. So we have a team that
does nothing but go around fixing these potential
problems before they occur.”
Pettit described the integration of various systems,
including OMS and DMS, as a “big find,”
but something the utility should roll out in bits
and pieces. However, Oncor’s distribution operation
center said, “This is great!” and all of a sudden, Oncor turned on all of the
integration. “They’ve been happy,” he said. “And now it’s as though they can’t
live without it.”
Pettit said that utilities will likely find that most OMS systems are not ready
to deal with a high quantity of messages. Oncor had an outage that affected a
half-million people. He said the systems are not scaled for millions of outage
messages. “You have to find a way to filter, modify or otherwise limit the amount
of messages,” he said.
Automation has saved
between 4 million and
4.5 million truck rolls,
along with the associ-
ated fuel and man hours.”
The future of analytics
Regardless of the project or challenges, utilities have their eyes open for the next
killer app in analytics.
Rhoades said as Alabama Power integrates its AMI and SCADA data, it would
like to improve light feeders. “Why is one feeder two percent more inefficient
than the next feeder when it should be just like it with the same miles of line?”
he asked. “That’s something in the future we’re looking at.”
Pettit said much of the future for data analytics in Oncor’s projects is unknown.
He said although the smart grid and smart meter programs have been
going on for a long time, they represent the biggest change in the electric utility
industry in 100 years.
H. Christine Richards is the director of knowledge services for the Utility Analytics Institute.
You may reach her at crichards@energycentral.com
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