POWER June 2011 - 28

INFORMATION TECHNOLOGY
network part of the design of a new power
facility may be slow and arduous.
Neural Network Watchdog. Perhaps a
more likely scenario for widespread implementation
of AI in power generation is a
neural network that can essentially " sit on
top " of a plant's existing DCS. Such an AI
system will monitor, learn, and make value
judgments about potential changes in state to
optimize plant operation in order to improve
safety or, perhaps, plant reliability. These artificial
neural networks are relatively mature
and commercially available today.
With the growth in automation in power
generation facilities, the incredible complexity
of monitoring plant operations, noting
anomalies, diagnosing those anomalies, and
taking action in a timely manner can quickly
become unwieldy and unmanageable using
conventional controls technology. On
the other hand, artificial neural systems can
" view " numerous process variables almost
instantly, recognize trends or deteriorating
conditions or opportunities to improve conditions,
review a library for potential reactions,
and make weighted judgments on the best action.
The result can be significant benefits to
plant operations.
The neural network systems offered
by some of the major process technology
providers are open systems that work with
various suppliers' DCS platforms. These
commercial systems are available to automatically
make decisions to optimize
performance of a plant subsystem, such
as combustion controls. AI systems can
also be configured to act as an operator
consultant-a decision-support system-
to make recommendations on operating
adjustments.
Targeted Process Neural Network
Watchdog. AI systems currently used in
power plants are usually targeted to specific
application areas of process control
such as combustion optimization or plant
performance. Much as with the advance of
digital controls, this stepwise adoption of
the technology provides sufficient testing
to make users comfortable with the intelligent
algorithms without exposing early AI
system adopters to the risk of reduced plant
reliability.
Already, numerous operating plants incorporate
some form of targeted neural networks.
Some plants have used some form of
AI-based controls to reduce NOx
production
and to optimize their boiler cleaning or sootblowing
systems. Some of the applications
have years of operating experience at power
generation facilities.
Watson as Your Virtual
Plant Operator
Claims of improvements up to 1.5% in plant
heat rate, reductions in emissions levels, improvements
in equipment availability, improvements
in steam turbine ramp rates, and
improvements in start-up efficiencies are all
claims made by vendors of AI networks. The
promised benefits are significant, but there
are consequences to moving forward on AIbased
plant controls.
Critics of AI systems are quick to point
out the potential vulnerabilities that are introduced
with regard to cybersecurity when so
many systems are operating over plant networks
(voice over Internet protocol, security,
plant network, operations network, and the
like). This is a significant issue that warrants
study, particularly in light of recent North
American Electric Reliability Corp. requirements
for Critical Infrastructure Protection.
Network defense systems and monitoring are
sufficient to protect against unwanted intrusions,
but clearly, widespread implementation
of AI at power plants may make control
networks more vulnerable.
Another consideration is that AI-based
If you need information on the
global power generation industry,
look to
first.
control systems " learn " from prior experiences.
Any system will require time to " think "
through the innumerable possible combinations
of process variables and operating
scenarios before it matures and develops a
library of operating scenarios and responses.
The system will also require clear exit paths
and mitigation programs should its complex
networks get " stumped. "
Finally, expect some resistance to acceptIN
PRINT, IN PERSON, AND ONLINE
POWER magazine * POWER news * COAL POWER
Managing POWER * POWER Handbook * POWERmag.com
POWER connect * Careers in POWER * ELECTRIC POWER
www.powermag.com
To subscribe, visit www.powermag.com/subscribe
or call 847-763-9509.
ing AI-based controls at a more philosophical
level. Some system designers believe that
intelligent control systems have the potential
to breed a culture of superficial knowledge.
Today, many plants can still be operated
manually by experienced operators. When,
in the future, reliance on AI systems is the
norm, what will be the motivation to push for
more understanding of the operating nuances
and situational responses necessary when operating
a plant? Will the hands-on operator
become obsolete?
On the other hand, the adoption of intelligent
systems may be one solution to the
expected loss of a vast amount of operating
knowledge as the baby boomer generation
approaches retirement age. How to capture
that knowledge remains problematic and is
the subject of current research.
What we have learned so far is that Watson
has proven to be a great game show player. But
we also know that it (he?) is not ready to operate
a major power generation facility . . . yet. ■
-James H. Brown, PE, PMP (james
.brown@fluor.com) is senior director of
engineering for Fluor Corp.'s Power Group.
28
www.powermag.com
POWER | June 2011
http://www.POWERmag.com http://www.powermag.com http://www.powermag.com/subscribe http://www.powermag.com
POWER June 2011

Table of Contents for the Digital Edition of POWER June 2011
