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3E analyses and multi-objective optimization of a liquid nitrogen wash based cogeneration system for electrical power and LNG production.

Authors :
Yang, Sheng
Wen, Jiakang
Liu, Zhiqiang
Deng, Chengwei
Xie, Nan
Source :
Energy. Jun2024, Vol. 297, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

A liquid nitrogen wash based novel system is proposed for electricity generation and LNG production. This system utilizes cold energy of methane rectification for power generation, and realizes the LNG production through methane recovery from exhaust gas. Effects of operational parameters on net generation capacity (NEG) and energy efficiency are studied. Exergy destruction/efficiency and exergy cost are obtained. Advanced exergy/exergo-economic analyses are conducted to clarify the improvement potential and improvement strategy. Finally, the optimal solutions are obtained in multi-objective optimization. Results show that propane could be used as the organic working medium and the maximum NEG is 675.95 kW and the energy efficiency is 19.34 %. As 88.8 % of the system investment cost is for the equipment, reduction on exergy destruction cost of equipment should be considered. Advanced analysis indicates that 27.27 % of the exergy destruction, 30.02 % of the exergy cost and 7.20 % of the investment cost can be avoided. The thermodynamic optimization shows that the highest energy efficiency is 67.26 %, the highest exergy efficiency is 76.95 % and the lowest exergy cost per unit is 28.45 $/GJ. The economic optimization shows that exergy efficiency is improved by 2.83 % and NEG is improved by 47.95 % when increasing the investment cost for 6.13 %. • A liquid nitrogen wash based system is proposed for electricity and LNG production. • Advanced exergy/exergo-economic analyses are conducted for the system evaluation. • 27.27 % of exergy loss, 30.02 % of exergy cost and 7.20 % of investment can be avoided. • The highest energy efficiency and exergy efficiency are obtained as 67.26 % and 76.95 %. • Optimal operation of this cogeneration system is achieved using the genetic algorithm. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03605442
Volume :
297
Database :
Academic Search Index
Journal :
Energy
Publication Type :
Academic Journal
Accession number :
176867722
Full Text :
https://doi.org/10.1016/j.energy.2024.131331