- Turkish Journal of Electrical Engineering and Computer Science
- Vol: 27 Issue: 6
- Predicting CO and NOx emissions from gas turbines: novel data and a benchmark PEMS
Predicting CO and NOx emissions from gas turbines: novel data and a benchmark PEMS
Authors : Heysem KAYA, Pinar TÜFEKCİ, Erdinç UZUN
Pages : 4783-4796
View : 5 | Download : 1
Publication Date : 9999-12-31
Article Type : Makaleler
Abstract :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 dataKeywords : Predictive emission monitoring systems, CO, NOx, exhaust emission prediction, gas turbines, extreme learning machine, database