GE Digital’s Autonomous Tuning of Gas Turbines Accelerates the Energy Transition with AI and ML

By Craig Resnick

Company and Product News

GE Digital announced the introduction of software that helps to ensure that gas turbines operate at the most optimal combustion for reduced emissions and fuel consumption. Autonomous Tuning of gas turbines uses Autonomous Tuning of Gas TurbinesArtificial Intelligence (AI) to build a machine learning (ML) Digital Twin model of a gas turbine to continuously find the most optimal flame temperatures and fuel splits to help minimize emissions and acoustics. The on-premises software senses changes in ambient temperature, gas fuel properties, and degradation, and sends real-time automatic adjustments to the controls every two seconds.  

Gas turbines require seasonal adjustment of flame temperatures and fuel splits, which is generally a manual process performed by an expert after an outage and may take a few days to complete. However, manual seasonal tuning is typically only efficient for the precise conditions in which it was completed and often does not respond to changes in ambient temperature or fuel properties.

The goal of Autonomous Tuning is to allow for tracking of the turbine’s “sweet spot” (operational conditions with low acoustics and low emissions) in response to changes in environmental conditions, fuel properties, or physical degradation, and helps to reduce the need for seasonal remapping. The software is applicable to most OEM gas turbine platforms. The software is also fully bound by the turbine controls system’s safety-critical programming, which helps to ensure that it cannot harm the turbine.

Power generators who can benefit the most from this software are typically located in highly regulated regions or with constrained emissions, such as Europe, the United States and Canada, or in any location that does not have consistent weather patterns. In addition, any site subject to fuel-quality variability issues or sites looking to lower their Operations & Maintenance (O&M) costs by reducing manual tuning and fuel consumption can benefit. Power Generation plants have realized carbon monoxide reduction by up to 14 percent, nitrous oxide emissions reduction by up to 10 – 14 percent; and fuel and carbon dioxide reduction by between 0.5 and 1 percent.

Customers will have full-service deployment of the on-premises solution and calibration of the software to run autonomously without requiring plant personnel intervention.

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