Power generation is a costly affair. The huge turbines that
generate the power are to be constantly monitored for all those critical
parameters; day-in and -out. When a few minutes of downtime can attract losses
in terms of millions of dollars, it is normal that power generating companies
opt for predictive analytical solutions to help them maximize the availability
of operations, increase system uptime, create additional revenue opportunities,
lower maintenance costs, etc.
Analytics help you to identify the wear and tear of your
machines in advance, lower maintenance cycles, identify potential barriers
before they occur, fix minor issue before they snowball into catastrophic
events, and dynamically adjust parameters to tune the machines for optimized
performance.
Fuel quality, power generation forecasting, etc., are a few
critical factor that needs to be checked time and again while generating power.
Besides, pollution, environmental compliance, etc., are a few factors that are
increasingly challenging and are spinning and spanning a wide array of issues. With
the help of sensors, both physical and virtual, not only you can check the
areas of risk but also monitor and diagnose the overall health of the
infrastructure equipment and components every fraction of a second.
Predictive analytic models, when applied on the gathered
sensor and historical data, project different intuitive charts and graphs which
display the future trends of power generation on your snazzy dashboard.
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