Predicting CO and NOx emissions from gas turbines: novel data and a benchmark PEMS
Yükleniyor...
Dosyalar
Tarih
2019
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Tubitak Scientific & Technical Research Council Turkey
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
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.
Açıklama
Anahtar Kelimeler
Predictive emission monitoring systems, CO, NOx, exhaust emission prediction, gas turbines, extreme learning machine, database, Extreme Learning-Machine, Model
Kaynak
Turkish Journal of Electrical Engineering and Computer Sciences
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
27
Sayı
6
