Siemens Energy proposes a methodology to monitor & predict emissions based on design and operational knowledge of the SGT-300-2S through chemical kinetics model of the turbine and advanced statistical regression analysis.

Having constructed, commissioned, and operated several CEMS, we may have a cost-effective alternative once PEMS is certified and deployed. The research completed illustrates promising results for next stages of this project.

The corresponding report PO743-22201-R01 Validation of Next Generation Predictive Emissions Monitoring System for Gas Turbines describes field trial demonstration and validation of a Gas Turbine Predictive Emissions Monitoring System (PEMS) using engine data from Siemens Energy SGT-300 gas turbine compressor drivers at SoCalGas Blythe Compressor Station, California, USA.

The advanced PEMS model results are compared with CEMS data taken from process analyzers measuring emissions in the gas turbine exhaust. After the necessary corrections on emissions for water content and oxygen content in the exhaust, the values for PEMS and CEMS show good agreement across a wide range of operating conditions. Areas where there is deviation between the values are investigated and potential improvements and modifications are suggested.

The use of PEMS shows promise as a robust and cost-effective alternative to analyzer based CEMS and can be used to provide additional diagnostic information. Recommendations for future work are presented.