Triple-objective optimization and electrochemical/technical/environmental study of biomass gasification process for a novel high-temperature fuel cell/electrolyzer/desalination scheme

Yao Zhang, Mohamed Salem, Yasser Elmasry, Anh Tuan Hoang, Ahmed M. Galal, Dang Khoa Pham Nguyen and Makatar Wae-hayee

Renewable Energy, 2022, vol. 201, issue P1, 379-399

Abstract: To meet demands in agricultural sectors, the way of waste-to-useful products is an alternative to conventional processes capable of generating on-site products. This is an innovative method leading to designing a novel combined system in the current work. By means of a precise chemical and electrochemical simulation, the rice husk (an agricultural biomass fuel) is processed through a gasifier with a steam agent and is utilized in a molten carbonate fuel cell. The fuel cell's waste heat is delivered to thermal-based desalination utilizing humification and dehumidification processes. In addition, a solid oxide electrolyzer cell creates hydrogen by consuming power supplied by the fuel cell. Consequently, the system is able to meet some demands like electricity, irrigation, and chemical fertilizers. Accordingly, the system's applicability is measured by comprehensive electrochemical, technical, and environmental sensitivity analyses along with an advanced triple-objective optimization using the method of artificial neural network (ANN) + multi-objective grey wolf optimization. Regarding the objective functions, i.e., exergetic efficiency (ExEtot), exergoenvironmental impact index (EIItot), and carbon dioxide emission (CDEtot), the optimum state brings ExEtot=29.98%, EIItot=2.28, and CDEtot=391.1kg/MWh. Also, the variability of studied variables is further affected by the fuel cell's current density; its mean sensitivity index equals 0.48.

Keywords: Agricultural biomass fuel; Electrochemical simulation; Molten carbonate fuel cell; Exergoenvironmental impact index; Hydrogen generation; Multi-objective grey wolf optimization (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:201:y:2022:i:p1:p:379-399

DOI: 10.1016/j.renene.2022.10.059

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