Flamelet LES of pulverized coal combustion and NO formation characteristics in a supercritical CO2 boiler
•Flamelet LESs of the typical combustion area of a S-CO2 boiler are conducted.•An extended FPV model with fuel-N partitioning are employed for NO prediction.•The combustion and NO formation characteristics are investigated under different conditions.•The effect of wall temperature is slight while fl...
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Veröffentlicht in: | Applications in energy and combustion science 2024-09, Vol.19, p.100274, Article 100274 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •Flamelet LESs of the typical combustion area of a S-CO2 boiler are conducted.•An extended FPV model with fuel-N partitioning are employed for NO prediction.•The combustion and NO formation characteristics are investigated under different conditions.•The effect of wall temperature is slight while flue gas recirculation can reduce NO formation.
In the present study, LESs of a modeled typical combustion zone of a 1000 MW S-CO2 coal-fired boiler using a hybrid flamelet/progress variable model are conducted for the first time. In the hybrid model, both the fuel-N from volatiles and char are considered, and two progress variables are used for major species and NO, respectively. The combustion and NO formation characteristics at different regions are qualitatively and quantitatively investigated. The results indicate that the mixture of primary air and secondary air, the high-temperature wall as well as the adjacent flame can promote the pulverized coal combustion (PCC) and NO formation. In addition, the effects of wall temperature and flue gas recirculation on PCC and NO formation are investigated. The results show that compared with the supercritical H2O boiler, a slight rise of 2.08% and 3.05% for temperature and NO production can be observed in the supercritical CO2 boiler due to a higher wall temperature; flue gas recirculation with a recirculation rate of 27% can effectively reduce the production of NO by 57.6% in the supercritical CO2 boiler. |
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ISSN: | 2666-352X 2666-352X |
DOI: | 10.1016/j.jaecs.2024.100274 |