A Solution for Improving Gas Turbine Performance Degradation and Emissions: The “GT Auto Tuner” Product
Authors: Gagnani Mayur , Nandagopal Pugalenthi , Sueselbeck Kai 
Published: February 2024

The main causes of gas turbine performance degradation in natural gas combined cycle power plants are corrosion, fouling, and high turbine inlet temperatures which increase the oxidation in the blades and vanes. Blade coatings, effective filters, and cutting-edge turbine cooling technology can all be used to solve this problem. It can be quite difficult to stop the degradation of gas turbine parameters like the compressor flow, compressor efficiency, and turbine efficiency. Turbine Inlet Temperature (TIT) deterioration, on the other hand, is a phenomenon exclusive to the gas turbine sector that results from traditional gas turbine control systems. The employment of a soft sensor technique in conjunction with an Optimization of control system approach can totally stop Turbine Inlet Temperature (TIT) degradation.

The fleet’s gas turbine-based combined cycle power plants run on a conventional exhaust temperature management strategy. Normally, during base load operations, Gas Turbines should operate at a constant design turbine inlet temperature. With the current exhaust temperature control approach, the turbine outlet temperature is maintained. As there is a direct correlation between inlet temperature and outlet temperature for a new and clean engine, the TIT can be maintained as well. Due to the degradation in the turbine sections, the correlation gets affected. This leads to decreased turbine inlet temperatures when controlling exhaust temperature. As a result of TIT’s ongoing degradation, Gas Turbines produces less power comparing to new and clean turbine.

By continuously changing the exhaust temperature, Siemens Energy’s GT Auto Tuner solution addresses gas turbine degradation and maintains an appropriate turbine inlet temperature. Furthermore, by controlling the fuel split and exhaust temperature, this product controls pollutants and combustion dynamics.

The GT Auto Tuner’s (machine learning’s) main goals are to create control-related techniques that can adapt to changing operational circumstances, take advantage of untapped potential, and adjust as necessary for degradation recovery and emission control. A system that reduces engineering efforts while enhancing relevant customer key performance indicators (KPIs) and flexibility is developed utilizing existing engineering information (such as thermodynamics, combustion) and artificial intelligence.

The focus of this article is on how the GT Auto Tuner package is an initiative of Siemens Energy digitalization stream and it can aid in restoring gas turbine performance due to TIT deterioration, emission reductions and limit combustion dynamics based on combustion behavior. A few units have the GT Auto Tuner package already installed. This study will also cover data collection, data filtration, thermodynamic analysis, and in-depth fleet validation, along with the crucial operational data process.

This paper’s objective is to help readers understand the benefits of using the GT Auto Tuner product in their gas turbine in terms of power and emissions.