Comparative analysis and multi-objective optimization of hydrogen liquefaction process using either organic Rankine or absorption power cycles driven by dual-source biomass fuel and geothermal energy

被引:35
作者
Meng, Yue [1 ]
Wu, Haoyue [2 ]
Zheng, Yuhang [3 ]
Wang, Kunpeng [4 ]
Duan, Yinying [1 ]
机构
[1] Sichuan Agr Univ, Coll Business & Tourism, Chengdu 611830, Peoples R China
[2] Sichuan Agr Univ, Coll Management, Chengdu 611830, Peoples R China
[3] Univ Elect Sci & Technol China, Sch Management & Econ, Chengdu 610054, Peoples R China
[4] Chengdu Univ Technol, Coll Geophys, Chengdu 610059, Peoples R China
关键词
Biomass to power; Comparative study; Geothermal energy; Hydrogen liquefaction; Multi-objective grey wolf optimization; Waste-to-energy; MUNICIPAL SOLID-WASTE; THERMODYNAMIC ANALYSIS; PERFORMANCE ASSESSMENT; EXERGY ANALYSIS; HYBRID SYSTEM; GENERATION; KALINA; GASIFICATION; INTEGRATION; GASIFIER;
D O I
10.1016/j.energy.2022.124078
中图分类号
O414.1 [热力学];
学科分类号
摘要
The present work presents a novel approach of employing two renewable energy sources for power and liquefied hydrogen cogeneration. Meanwhile, the main scheme comprises a biomass-fed (municipal solid waste) Brayton cycle using a digester, a geothermal-based flash binary cycle, and a Claude cycle for hydrogen liquefaction; the heat recovery is also performed through either an organic Rankine cycle (case A) or a Kalina cycle (case B) joint to the main scheme having two different configurations. Regarding the waste-to-energy framework designed for high performance, the system is comprehensively studied and optimized from the energy, exergy, and economic aspects. In this regard, thermodynamic-and economic-based sensitivity analysis, net present value method, and multi-objective grey wolf optimi-zation are implemented; the multi-criteria optimization is performed in three scenarios containing exergy efficiency-NPV, exergy efficiency-liquefied hydrogen's unit cost, and NPV-liquefied hydrogen cost. According to the results, the first scenario offers higher exergetic efficiency; the third scenario also provides a better hydrogen cost. As a result, the better optimum exergetic efficiency and liquefied hydrogen cost are equal to 10.95% and 3.84 $/kg for case A, and 10.38% and 3.74 $/kg for case B.(c) 2022 Elsevier Ltd. All rights reserved.
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页数:21
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