Performance analysis and optimization of syngas composition for reversible solid oxide fuel cells in dual-mode operation based on extreme learning machine-Reference-Cited by-同舟云学术

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Performance analysis and optimization of syngas composition for reversible solid oxide fuel cells in dual-mode operation based on extreme learning machine

Published:2024-09 Issue: Volume:614 Page:234982
ISSN:0378-7753
Container-title:Journal of Power Sources
language:en
Short-container-title:Journal of Power Sources

Author:

Wang Lina,Guo Weihao,Zhang Zhiheng,Wang Fu^ORCID,Yuan Jinliang

Publisher

Elsevier BV

Reference54 articles.

1. Fossil fuel sustainability index: an application of resource management;Ediger;Energy Pol.,2007

2. Design and optimization of hydrogen production by solid oxide electrolyzer with marine engine waste heat recovery and ORC cycle;Wang;Energy Convers. Manag.,2021

3. Development and modelling of a novel electricity-hydrogen energy system based on reversible solid oxide cells and power to gas technology;Zhang;Int. J. Hydrogen Energy,2019

4. Thermodynamic investigation of an integrated near-zero CO2 emission power generation system with SOFC, MGT, SCO2BC, and CO2 capture;Wang;Process Saf. Environ. Protect.,2024

5. Current developments in reversible solid oxide fuel cells;Gómez;Renew. Sustain. Energy Rev.,2016

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