GT Auto Tuner

Maintaining optimal firing temperatures is critical for both hardware longevity and fuel economy. Traditional measurement methods often face latency issues or sensor inaccuracies in extreme environments; however, our latest control architecture overcomes these hurdles through secondary verification and physical modeling.

With Siemens Energy's GT Auto Tuner, the turbine inlet temperature is estimated accurately by performing online energy balance in real time. Goal of the improved turbine inlet temperature control is to compensate the power degradation in combination with a continuous real time optimization of emissions and combustor dynamics.

Siemens Energy's GT Auto Tuner is an AI-driven optimization solution designed to maximize gas turbine efficiency. By integrating a Thermal Digital Twin with advanced Reinforcement Learning (RL), it enables real-time, autonomous adjustments to combustion and temperature control.

GT Auto Tuner improves combustion control and further minimizes seasonal tuning by supplementing the Omnivise T3000 controls with a trained reinforcement learning control policy together with a direct engine temperature control method.

• Power degradation recovery
• Increased part load efficiency
• Further reduction of seasonal tuning
• Reduced combustion dynamics and emissions: Possible ammonia reduction through improved emissions control as well as ~ 10% lower NOₓ output 
• Close loop control utilizing an AI control policy

The scope includes the control logic that is required for autonomous optimization. Depending on individual project requirements, it can also include controls hardware as well as additional instrumentation.