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.