Improving Reliability with Early Warning of Increased Combustion Dynamics on a Gas Turbine

Industry: Power Generation
Region: Middle East
Asset Type: Gas Turbine, GE Vernova 9FA

A deviation in a gas turbine at a power generation site in the Middle East was identified by GE Vernova's SmartSignal Predictive Analytics. Specifically, the digital twin of the gas turbine indicated that the combustion dynamics in multiple cans were intermittently increasing and breaching model thresholds during part-load operations, exceeding the APM early warning limits in some combustion cans.

This customer has the GE Vernova enhanced monitoring package, M&D+ Powered by SmartSignal. Having the enhanced monitoring and diagnostic service, the GE Vernova Engineering team, Industrial Managed Services (IMS) collaborated with the Gas Power Combustion Engineering team for further review.

Following the early alert from the assigned GE Vernova Engineer from the Industrial Managed Services (IMS) team, a detailed review was conducted in collaboration with GE Vernova's Gas Power Engineering team. The focus was on the combustion tunable parameters and the composition of the fuel gas. The analysis revealed that certain tunable parameters were not optimized for the current operational conditions, which was causing the combustion dynamics in multiple cans to intermittently exceed acceptable thresholds.

Specifically, the combustion engineering team identified the need to adjust by tuning it. This parameter adjustment was crucial in stabilizing the combustion process, as it helped mitigate the fluctuations that were causing the dynamics to breach model thresholds, particularly during part-load operations.

The customer implemented these recommended changes, and the gas turbine was subsequently subjected to enhanced monitoring by both the site and the GE Vernova Engineering teams to ensure that the adjustments effectively addressed the issue.

The early notification and subsequent intervention provided significant value to the customer by enabling timely adjustments to the operational parameters of the gas turbine. By making the necessary changes to the tunable parameters, the customer was able to bring the combustion dynamics back within the safe operational range, specifically reducing the lean blowout tones. This proactive approach helped prevent prolonged exposure to high combustion dynamics, which could have led to severe damage to the combustion hardware. Such damage could have resulted in costly runbacks and trips, negatively impacting operational efficiency and reliability.

The intervention also facilitated continuous safe operation, thereby avoiding the potential financial implications of hardware damage and unplanned outages. The estimated cost savings from this proactive maintenance strategy are approximately $347,000, based on the avoidance of North American average production losses. This example highlights the critical role of predictive analytics and collaborative problem-solving in maintaining operational integrity and optimizing the performance of power generation assets.