Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
EN
|
EL
| URI | http://purl.tuc.gr/dl/dias/CEDD6D1C-646D-4214-9E13-8FF8DFF69D23 | - |
| Αναγνωριστικό | http://pubs.acs.org/doi/abs/10.1021/ef800964f | - |
| Αναγνωριστικό | https://doi.org/10.1021/ef800964f | - |
| Γλώσσα | en | - |
| Μέγεθος | 7 pages | en |
| Τίτλος | Lignite quality uncertainty estimation for the assessment of CO2 emissions | en |
| Δημιουργός | Galetakis Michalis | en |
| Δημιουργός | Γαλετακης Μιχαλης | el |
| Δημιουργός | Vamvouka Despoina | en |
| Δημιουργός | Βαμβουκα Δεσποινα | el |
| Εκδότης | American Chemical Society | en |
| Περίληψη | In this study, models were developed for the estimation of CO2 emissions from lignite- fired power plants based on routinely measured quality parameters of lignite and the power-plant efficiency. These models could be incorporated into the production scheduling optimization plan of the lignite mining. A probabilistic methodology for uncertainty assessment of CO2 emissions and assigning this uncertainty to different sources (lignite quality, activity, and operational data of power plants) was performed. A Monte Carlo uncertainty and sensitivity analyses method was found appropriate because of the strong correlations between input quality parameters. This method was applied to the largest power plant in Greece for the estimation of the uncertainties in annual, monthly, and daily CO2 emissions. Sensitivity analysis revealed that the variance of CO2 emissions was mainly determined by the uncertainty of the quality parameters of lignite, with carbon content being the most dominant parameter. | en |
| Τύπος | Peer-Reviewed Journal Publication | en |
| Τύπος | Δημοσίευση σε Περιοδικό με Κριτές | el |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2015-10-27 | - |
| Ημερομηνία Δημοσίευσης | 2009 | - |
| Θεματική Κατηγορία | Lignite | en |
| Θεματική Κατηγορία | Carbon dioxide | en |
| Βιβλιογραφική Αναφορά | M. Galetakis and D. Vamvouka, “Lignite quality uncertainty estimation for the assessment of CO2 emissions”, Energy Fuels, vo. 23, no. 4, pp. 2103-2110, Apr. 2009. doi:10.1021/ef800964f | en |
Copyright © DIAS 2013
