POWER July 2020 - 30

OPERATIONS & MAINTENANCE
Using Data Analytics to
Support Asset Management
and Optimization
In the competitive power market that exists today, utilities must utilize data to
optimize their assets. With proper analysis, individual units, as well as fleets of
plants, can balance operating costs, efficiency, and reliability, maximizing value to
companies' bottom lines.
Cliff Watson
C
ompetition dynamics within the
power generation industry have
never been more intense than
those that exist today. The prices of fuel
and power, variance of technologies, and
numerous other drivers require companies
to be agile and vigilant to ensure asset
competitiveness. The potential exists
for short-term financial decisions to overshadow
a long-term strategy that better
positions a company for success.
To maintain both short-term viability
and long-term sustainability, it is important
for companies to fully employ one
of their most valuable resources-their
data. Data analytics can be used as an
effective tool to optimize plant efficiency
and reliability, which will in turn contribute
to economic success. The most
effective asset management and optimization
systems are data-driven-valuing
and utilizing data as a foundation to
support informed decision-making that
brings long-term value.
Consider three primary keys to success
within the power generation industry:
operating cost, efficiency, and
reliability (Figure 1). During economically
challenging times, the " quick " answer
may lead to a focused emphasis on reducing
operating costs. Caution should
be used, however, before making this
conclusion. As depicted in the graphic,
the " keys " are interrelated-they are all
important to the overall economic performance
of the facility. Emphasis in one
area will have a direct (or indirect) influence
on the others.
Using Data Advantageously
Without effective data analytics, the
likelihood exists for the development
and execution of projects or operational
changes with too narrow of a focus on a
specific benefit. In other words, a company
may end up focused on efficiency
for the sake of controlling efficiency,
headcount for the sake of controlling
headcount, and spending for the sake
of controlling spending. As stated previously,
data in the real world is all interrelated.
Spending, or lack thereof, can
affect efficiency positively or negatively.
People decisions, such as hiring, workforce
reductions, and training, can also
affect reliability performance positively
or negatively. These singularly focused
decisions, in effect, could result in suboptimization,
which positively impacts
one area and negatively affects another.
As part of the data analytics equation,
it is important to clearly understand
the asset's " market mission " -a
factor that will likely vary from company
to company, and even asset to asset.
For example, reliability is typically of
highest importance to a cogeneration
facility, whereas operating cost may be
of greatest priority to an electric-only
power producer.
The quantity of data available at a power
generation facility is typically not in
question. What to do with the very large
sum of data produced is worth discussing.
A few related points and examples
to consider follow.
Operational Data. Assessing event
data can identify negative trends and facilitate
root cause analysis that will minimize
the potential for repeat events. As
an example, cogeneration facilities are
typically very effective at this assessment
because of their market mission
for high reliability. Data research reveals
the equivalent forced outage rate (EFOR)
at cogeneration facilities is 40% better
than their equivalent electric-only peers.
Root cause analysis with follow-up action
planning and execution is a proven
method for eliminating repeat events.
Additionally, findings at the plant level
can (and should) cascade across the fleet
to minimize the potential for a similar repeat
failure-thereby improving availability
(and revenue) for the entire fleet and
company. There are numerous related
benefits that can result from addressing
issues that are identified through operational
data analysis.
Financial Data. It is important to un1.
Keys to success in power generation. Courtesy: Solomon Associates
30
www.powermag.com
derstand the all-in cost of operating and
maintaining a facility as if it was an independent
business entity. Organizing
financial accounting records to include
segmentation of fixed and variable expenditures
at the plant level and the allocated
corporate expense is an important
starting point. Effectively utilizing a computerized
maintenance management
POWER | July 2020
http://www.powermag.com
POWER July 2020

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