Reduction in Specific Energy Consumption of Overall Biogas Upgrading and Biomethane Liquefaction Process: Energy and Exergy Analysis

被引:13
作者
Khan, Javed [1 ]
Saif-ul-Allah, Muhammad Waqas [1 ]
Qyyum, Muhammad Abdul [2 ]
Ahmed, Faisal [1 ]
Yasin, Muhammad [3 ]
Hussain, Arif [1 ]
Gillani, Zeeshan [4 ]
Bazmi, Aqeel Ahmed [1 ]
机构
[1] COMSATS Univ Islamabad, Proc & Energy Syst Engn Ctr PRESTIGE, Dept Chem Engn, Lahore Campus, Lahore, Pakistan
[2] Sultan Qaboos Univ, Coll Engn, Dept Petr & Chem Engn, Muscat, Oman
[3] COMSATS Univ Islamabad, Dept Chem Engn, Lahore Campus, Lahore, Pakistan
[4] COMSATS Univ Islamabad, Dept Comp Sci, Lahore Campus, Lahore, Pakistan
关键词
Biogas upgrading and biomethane liquefaction; Deep eutectic solvent; Single mixed refrigerant; Teaching -learning self -study optimization; Exergy analysis; LIQUEFIED BIOMETHANE; IONIC LIQUIDS; OPTIMIZATION; ABSORPTION; SIMULATION; EFFICIENT; SOLVENTS;
D O I
10.1016/j.enconman.2022.116269
中图分类号
O414.1 [热力学];
学科分类号
摘要
Biogas is considered one of the most promising alternative renewable fuels, but raw biogas needs to be upgraded before its use in vehicles or injection into the natural gas grid, and the resulting biomethane be liquified to be transported to distant areas. Both, absorption for upgrading, and compression for liquefaction are energy -intensive processes that require performance enhancement in terms of reduction of specific energy consump-tion. For the commissioning of biogas upgrading and biomethane liquefaction at a single plant, it is indispensable to optimize the overall process of biogas upgrading and biomethane liquefaction. According to the best of the authors' knowledge, the overall process has not yet been optimized for minimum specific energy consumption. This study proposes a fast-converging teaching learning self-study optimization approach to the overall process with a careful selection of decision variables and their bounds without breaching the process constraints. The results of optimization are compared with the base case in terms of parametric and composite curves analysis. The parametric analysis shows that teaching-learning self-study optimization has reduced the specific energy consumption of the overall process by 15.4 % as compared to the base case that optimized the upgrading and liquefaction processes independently. The individual-specific energy consumption of upgrading and liquefaction sections is reduced by 20.4 % and 5.8 %, respectively. The composite curves analysis reveals that the gap be-tween hot and cold composite curves is reduced as compared to the base case that depicts the reduction in specific energy consumption. Moreover, the detailed thermodynamic evaluation revealed that the exergetic ef-ficiency of the upgrading process compared to the base case significantly increased from 51.43 % to 92.98 % while the exergetic efficiency of the liquefaction section slightly increased from 80.23 % to 80.83 %, thus, resulting in an increase in exergetic efficiency of the overall process by 20.9 % compared to the base case. Additionally, the overall sustainability index of the upgrading and liquefaction processes has increased from 3.78 to 9.04. This study would be significantly helpful for the process engineers to overcome the challenges related to the reduction in specific energy consumption in the biogas upgrading and liquefaction industry.
引用
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页数:16
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