Case Studies
Explore how Turbine Logic helps companies like yours optimize the performance of your assets through advanced analytics, diagnostics, and engineering expertise.
A client sought to better understand the real-world performance benefits of bifacial photovoltaic modules compared to traditional monofacial installations. With growing industry interest in bifacial technology, there was a need for rigorous, data-driven analysis to quantify actual performance gains and identify the factors that most significantly influence energy production from these advanced solar modules.
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.
Other Studies
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 utility-scale solar plant operator sought to transition from reactive and preventative maintenance practices toward more cost-effective condition-based approaches. The challenge was identifying performance anomalies and equipment issues early enough to reduce energy losses and maintenance costs, while minimizing false alarms that waste operational resources.
A client in the power generation sector needed specialized support for an internal software tool used to analyze and benchmark operational data. Over time, the tool had grown in complexity and adoption, creating a need for expert review of its underlying architecture and hands-on assistance with applied use cases.
Gas turbine monitoring and diagnostics centers frequently encounter false alarms that consume valuable time and resources. Many of these false alarms stem from issues within the instrumentation chain: sensors that have drifted, failed, or produced corrupted data during transmission or storage.
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