| Today’s accelerating drive toward reduced carbon emissions, and the operational demand of changing duty cycles on power generating assets, come at the expense of reduced performance and increased maintenance requirements under operating conditions that accelerate wear and tear and consume component life at a faster rate. Given the increasing focus on operating flexibility, from rapid start-stop cycles and almost instant loading to fill the generating gaps associated with intermittent renewable energy systems, the impact on equipment life (systems and components) poses a formidable challenge.
Changes in plant operating environment as dictated by shifting market demand has created a real-time need for information not foreseen when the current fleet of gas turbine plants was designed. Data and knowledge relevant to equipment condition has become of first order value to the owner operators confronted by these challenging operating scenarios.
This all points to the need for enhanced operator decision-making capability to anticipate equipment issues before they happen and allow time for preventive measures to avoid downtime and keep plants in a ready-to-run condition. Data Fusion offers that capability. Time-series operating data and physics-based models combined with near real-time data and analytics hold the key to improving predictive capability.
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