Case Studies

Power generation operators managing multiple assets often struggle to balance competing priorities: responding quickly to grid demands, maintaining optimal efficiency, and minimizing maintenance impacts across their fleet. Traditional dispatch approaches rely on static models that fail to account for real-time equipment health, leading to suboptimal bidding strategies and reduced profitability.

A client sought to expand their capabilities in gas turbine performance monitoring and analysis. They needed both educational resources to help their team understand and apply digital twin technology, as well as refinements to calibration software that would meet rigorous quality standards for deployment.

A client faced a growing compatibility challenge with a critical performance monitoring tool that had been in use for years. The software relied on older architecture that was becoming increasingly incompatible with modern computing environments as industry standards evolved.

A client needed to expand their gas turbine monitoring and diagnostic capabilities to cover additional equipment types within their fleet. Existing digital twin models were limited to certain turbine configurations, creating gaps in their ability to perform comprehensive performance analysis across all assets.

A power generation company sought to enhance their gas turbine fleet monitoring capabilities, particularly around combustion dynamics. They needed a solution that could provide early detection of anomalous behavior related to instrumentation issues, tuning problems, and potential hardware damage before these issues led to costly unplanned outages or equipment damage.

A power generation client needed to understand whether maintenance activities had impacted the firing temperature of their heavy-duty gas turbine fleet. Changes in firing temperature can significantly affect both performance and component life, making accurate assessment critical for operational decision-making and long-term asset management.