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Thermal efficiency gains enabled by using CO2 mixtures in supercritical power cycles.
- Source :
-
Energy . Jan2022:Part C, Vol. 238, pN.PAG-N.PAG. 1p. - Publication Year :
- 2022
-
Abstract
- The present paper explores the utilisation of dopants to increase the critical temperature of Carbon Dioxide (sCO 2) as a solution towards maintaining the high thermal efficiencies of sCO 2 cycles even when ambient temperatures compromise their feasibility. To this end, the impact of adopting CO 2 -based mixtures on the performance of power blocks representative of Concentrated Solar Power plants is explored, considering two possible dopants: hexafluorobenzene (C 6 F 6) and titanium tetrachloride (TiCl 4). The analysis is applied to a well-known cycle - Recuperated Rankine - and a less common layout - Precompression -. The latter is found capable of fully exploiting the interesting features of these non-conventional working fluids, enabling thermal efficiencies up to 2.3% higher than the simple recuperative configuration. Different scenarios for maximum cycle pressure (250–300 bar), turbine inlet temperature (550–700 ° C) and working fluid composition (10–25% molar fraction of dopant) are considered. The results in this work show that CO 2 -blends with 15–25%(v) of the cited dopants enable efficiencies well in excess of 50% for minimum cycle temperatures as high as 50 ° C. To verify this potential gain, the most representative pure sCO 2 cycles have been optimised at two minimum cycle temperatures (32 ° C and 50 ° C), proving the superiority of the proposed blended technology in high ambient temperature applications. [Display omitted] • CO 2 blends enable thermal efficiencies higher than 50% at high ambient temperatures. • For a given layout, sCO2 blends enable 4–5 pp higher efficiency than pure sCO2 cycles. • Precompression is the most interesting layout to better exploit CO2– C6F6 blends. • The composition of the best-performing blend depends on ambient temperature. • Cycle layout and dopant composition/fraction are independent optimisation variables. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03605442
- Volume :
- 238
- Database :
- Academic Search Index
- Journal :
- Energy
- Publication Type :
- Academic Journal
- Accession number :
- 153707670
- Full Text :
- https://doi.org/10.1016/j.energy.2021.121899