GE Introduces Autonomous Tuning Software To Reduce Emissions And Fuel Consumption In Gas Turbines

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GE Digital, on Thursday, announced the introduction of its new software that ensures gas turbines operate with ideal combustion for reduced emissions and fuel consumption. The Autonomous Tuning Software 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. 

It is expected that the software will enable the customers to enjoy full-service deployment of the on-premises solution and calibration of the software to run autonomously without plant personnel intervention. The company said, ‘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. The software is also fully bound by the turbine controls system’s safety-critical programming – ensuring it cannot harm the turbine.’

“Gas turbines are becoming increasingly critical as the world looks to produce energy from lower carbon sources. While they offer a better alternative to coal, they can be made more efficient with software. Digital solutions like Autonomous Tuning are no longer optional. The energy transition demands we employ every measure for efficiency.”

Linda Rae, General Manager of GE Digital’s Power Generation and Oil & Gas business

Gas turbines require seasonal adjustment of flame temperatures and fuel splits. This seasonal adjustment is generally a manual process performed by an expert after an outage and may take a few days to complete. But manual seasonal tuning works for the precise conditions in which it was completed and does not respond to changes in ambient temperature or fuel properties. The on-premises software identifies the needed changes in ambient temperature, gas fuel properties, and degradation, and sends real-time automatic adjustments to the controls every two seconds.

“With Autonomous Tuning, GE Digital has introduced a practical industrial example of the use of machine learning in closed loop supervisory control, and all running at the Edge,” according to Joe Perino, Principal Analyst at LNS Research. “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.”

Power generators in highly regulated or emission-constrained regions, such as Europe, the United States, and Canada, or in any location with inconsistent weather patterns, will benefit the most from this software. Furthermore, any site with fuel-quality variability issues, as well as those intending to lower their Operations & Maintenance (O&M) costs by minimizing manual tuning and fuel use, will benefit. Power Generation plants have realized carbon monoxide reduction by 14%, nitrous oxide emissions decreased by 10% – 14%; and fuel and carbon dioxide reduction between 0.5 and 1 percent.

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