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Crespi, F.; Rodríguez de Arriba, P.; Sánchez, D.; Ayub, A.; Di Marcoberardino, G.; Invernizzi, C.M.; Martínez, G.S.; Iora, P.; Di Bona, D.; Binotti, M.; Manzolini, G.
Energy (Oxford), 01/2022, Letnik: 238Journal Article
The present paper explores the utilisation of dopants to increase the critical temperature of Carbon Dioxide (sCO2) as a solution towards maintaining the high thermal efficiencies of sCO2 cycles even when ambient temperatures compromise their feasibility. To this end, the impact of adopting CO2-based mixtures on the performance of power blocks representative of Concentrated Solar Power plants is explored, considering two possible dopants: hexafluorobenzene (C6F6) and titanium tetrachloride (TiCl4). 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 CO2-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 sCO2 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 •CO2 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.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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in: SICRIS
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