Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI | http://purl.tuc.gr/dl/dias/CEDD6D1C-646D-4214-9E13-8FF8DFF69D23 | - |
| Identifier | http://pubs.acs.org/doi/abs/10.1021/ef800964f | - |
| Identifier | https://doi.org/10.1021/ef800964f | - |
| Language | en | - |
| Extent | 7 pages | en |
| Title | Lignite quality uncertainty estimation for the assessment of CO2 emissions | en |
| Creator | Galetakis Michalis | en |
| Creator | Γαλετακης Μιχαλης | el |
| Creator | Vamvouka Despoina | en |
| Creator | Βαμβουκα Δεσποινα | el |
| Publisher | American Chemical Society | en |
| Content Summary | 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 |
| Type of Item | Peer-Reviewed Journal Publication | en |
| Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2015-10-27 | - |
| Date of Publication | 2009 | - |
| Subject | Lignite | en |
| Subject | Carbon dioxide | en |
| Bibliographic Citation | 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 |
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