Computer Engineering Commons^™

Predicting Co And Nox Emissions From Gas Turbines: Novel Data And A Benchmark Pems, Heysem Kaya, Pinar Tüfekci̇, Erdi̇nç Uzun

Turkish Journal of Electrical Engineering and Computer Sciences

Predictive emission monitoring systems (PEMS) are important tools for validation and backing up of costly continuous emission monitoring systems used in gas-turbine-based power plants. Their implementation relies on the availability of appropriate and ecologically valid data. In this paper, we introduce a novel PEMS dataset collected over five years from a gas turbine for the predictive modeling of the CO and NOx emissions. We analyze the data using a recent machine learning paradigm, and present useful insights about emission predictions. Furthermore, we present a benchmark experimental procedure for comparability of future works on the data