Gas turbines require seasonal adjustment of flame temperatures and fuel splits, which is generally a manual process, and may take a few days to complete. However, manual seasonal tuning is only efficient for the precise conditions in which it was completed and does not respond to changes in ambient temperature or fuel properties.
GE Digital has recently introduced a software that ensures gas turbines operate with ideal combustion for reduced emissions and fuel consumption. Autonomous Tuning uses Artificial Intelligence (AI) to build a Machine Learning (ML) Digital Twin model of a gas turbine to continuously find optimal flame temperatures and fuel splits to 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.
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 reduce the need for seasonal remapping. The software is applicable to any OEM gas turbine platform. It is also fully bound by the turbine controls system’s safety-critical programming – ensuring it cannot harm the turbine.
Commenting on the software, Joe Perino, Principal Analyst at LNS Research, said, “This is a real-world application of AI for decarbonization with tangible reductions in emissions and fuel for gas turbine operators. This, and other building block sub-systems, are a step toward autonomous operations.”
