POWER January 2016 - 29

2016 INDUSTRY FORECAST
Sensors: Connecting Physical and Digital Worlds
Realizing the vision of the Industrial Internet
requires technology improvements
to many components of the power system.
Emerson Process Management is one of
the major companies supplying the sensors,
monitoring, and controls that are
essential to this vision. One of its latest
contributions is IntelliSAW technology, a
tiny passive wireless thermal monitoring
device combined with analytics. It provides
advanced warning to operators when
they are experiencing electrical reliability
issues like overheating switchgear, busses,
or other electrical systems.
According to Doug Morris, the company's
director of business development,
one challenge in implementing continuous
monitoring of such critical connection
points inside switchgear is that the system
must maintain the impulse-withstand
GE itself has benefitted from the IIoT. Immelt
told the M+M audience that the company's
H turbine was designed in half the time
and at a lower cost per megawatt because of
the Industrial Internet capabilities deployed
in its development.
Taking the long view, one of the keys to
maximizing the power of the IIoT is secure
information sharing among asset owners and
trusted partners, including equipment and service
providers, in order to share performance
data. That will necessarily involve integrating
data from competitors, because many generators
already rely upon equipment and services
from multiple vendors (see the sidebar " Remote
Monitoring and Maintenance " ).
Where to Start
The ARC authors acknowledge that " The
plethora of automation and other devices that
can potentially connect to the IIoT leaves
plenty of room for confusion. Some end user
organizations may opt to develop internal
management strategies by machine type; others
choose different criteria such as geography
or supplier. Companies should focus first on
connecting the specific types of devices that
are core to their schemes for specific operational
or asset-management improvements,
and then use that knowledge as the foundation
to roll out a broader IIoT strategy. "
" For starters, " the ARC authors write,
" original equipment manufacturer (OEM)
machinery will be one of the earliest and
largest IIoT adopters. IIoT offers a significant
value proposition in OEM machinery,
because it can remotely monitor, diagnose,
January 2016 | POWER
voltage, also known as basic impulse
level (BIL). This requirement eliminates
the most common types of direct contact
temperature monitoring systems, leaving
only non-intrusive systems to consider for
switchgear thermal monitoring.
As a wireless, passive surface acoustic
wave (SAW) sensor, the IntelliSAW can
directly mount onto critical measuring
points in harsh environments while ensuring
safe BIL requirements are met. It does
not require line of sight to the monitoring
location, offering installation flexibility,
and, because the sensors are manufactured
from quartz crystal, it offers a monitoring
solution for the lifespan of the switchgear,
without ongoing maintenance. The system
ties into a plant monitoring system, where
differential and maximum temperatures
can be monitored and trended over time.
troubleshoot, update, and cost effectively
manage this equipment. All these activities
contribute to reducing downtime and maximizing
machine performance-core value
propositions driving interest in the IIoT. "
As with many new technologies, there's a
" maturity model " -which extends from core
assets to adjacent assets to facility and finally
the enterprise-that grows " up " along this
path, according to one M+M presentation:
■ Data: Connect
■ What: Monitor
■ Why: Analyze
■ When: Predict
■ What if: Optimize
At M+M, Brian Hoff, director of emerging
technologies at Exelon Corp., admitted
that it can be hard to choose where to start
down the IIoT path. Exelon is starting its innovation
efforts in generation and later will
move out into its utilities, he said. The company
currently has five pilots (including one
at its Byron Nuclear Generating Station) and
wants more because people are excited. The
primary goals are " recovery of lost megawatthours "
and condition-based maintenance.
As Joan Knight, innovation director at Exelon
Generation, explained in another session,
equipment data collection at the company's
nuclear plans was " not all put together and
used " at the plant or fleet level. Exelon's partnership
with GE is taking a vertical and horizontal
view fleetwide and across all equipment
of the same sort across the fleet. Preliminary
results are impressive: a 10% decrease in lost
www.powermag.com
The Industrial Internet
Consortium
In addition to developing Predix, a custom
platform for the Industrial Internet
of Things (IIoT), General Electric is a
founding member of the Industrial Internet
Consortium (iiconsortium.org),
which covers a number of industry verticals,
including power.
The consortium includes more than
200 members, representing " large and
small industry, entrepreneurs, academics
and government organizations with
an interest in helping to shape and
grow the Industrial Internet. " The list
includes companies that are GE competitors
in the original equipment space,
such as Siemens, Toshiba, Hitachi, and
Mitsubishi.
The site has a Resource Hub that includes
articles, case studies, and technical
papers that offer deeper dives into
the topic than this article can provide.
megawatt-hours due to equipment reliability
issues, which has a value of $5 million.
Exelon's isn't the only nuclear fleet leveraging
data analytics. As Duke's Preston Gillespie notes
elsewhere in this issue, " Most nuclear fleets have
invested significantly over the years in analytics,
and Duke Energy is no exception. "
Duke Energy Nuclear Generation, modeling
a program successfully used by Duke's
fossil fleet, began a fleetwide project in late
2014 using the Schneider Electric Process
Information Signal Monitoring (PRiSM) Advanced
Pattern Recognition (APR) software
to " model " critical, large rotating equipment,
explained Howard Nudi, fleet engineering
support manager at Duke. APR software
can derive predictions for multiple variables
simultaneously based on empirical relationships
established during normal operation.
The software monitors assets 24/7, sampling
real-time data every 5 minutes. If the real-time
data falls outside APR software predictions,
a deviation is identified and a notification is
generated for the engineering group to evaluate.
APR software can also tell if there is a
deviation from predicted behavior and the
possible reason, based on subject matter expert
input programmed into the software.
Integrating PRiSM at the first site, Harris
Nuclear Plant, was completed in May
2015, Nudi said, with approximately 60
component models actively deployed. Duke
quickly realized positive results as the software
identified two unanticipated motor
cooler fouling issues in summer 2015 on
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http://www.iiconsortium.org http://www.powermag.com
POWER January 2016

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