Session: 04-22 Combustion - Emissions II

Submission Number: 174982

Physics-Informed Predictive Emissions Monitoring for Industrial Gas Turbines: Digital Twin Modeling, Validation, and Deployment 

Operators are increasingly seeking cost-effective alternatives to Continuous Emissions Monitoring Systems (CEMS) to meet regulatory and Environmental, Social, and Governance (ESG) goals. This paper presents the development and validation of a Predictive Emissions Monitoring System (PEMS) for industrial gas turbines, offering a digital solution that predicts NOx and CO emissions using operational data and advanced modeling techniques.

PEMS employs a hybrid modeling approach that combines machine learning with physics-based principles, ensuring that predictions remain grounded in combustion fundamentals. The models incorporate engine-specific parameters, including critical dimensions, fuel properties, and thermodynamic relationships, and are trained and validated using statistically rigorous methods on hundreds of data points from factory and field tests. Results demonstrate prediction accuracy consistent with EPA PS-16 guidance i.e. within ±2 ppm for NOx levels below 10 ppm.

PEMS is deployed via a digital platform, enabling real-time emissions monitoring, model management, and cloud/edge integration. Integrated health monitoring supports model reliability by continuously evaluating key indicators during engine operation and providing alerts when values deviate from defined limits.

This work demonstrates how digitalization and advanced, physics-informed modeling can provide a scalable, low-maintenance solution for emissions reporting and optimization, reducing the need for costly hardware-based monitoring systems while supporting compliance and sustainability initiatives.

Presenting Author: Stephen Theron Solar Turbines

Presenting Author Biography: Stephen Theron is a Senior Principal Engineer at Solar Turbines, where he focuses on combustion systems, thermal analysis, and digital engineering. His work includes supporting the development and deployment of predictive emissions monitoring tools and contributing to initiatives in emissions reduction and additive manufacturing. Stephen has experience working across engineering and software teams to develop simulation methodologies and digital platforms that support gas turbine design and analysis. He has co-authored technical publications and holds patents related to emissions modeling and exhaust system design. Stephen is particularly interested in practical applications of simulation and data analytics to improve engineering workflows and support sustainability goals in the energy sector.

Authors:

Stephen Theron Solar Turbines
Cody Allen Solar Turbines