Enhancing predictive models for steam gasification: A comparative study of stoichiometric, equilibrium, data-driven, and hybrid approaches

Juan Moreno, Martha Cobo, Felipe Buendia and Nestor Sánchez

Renewable and Sustainable Energy Reviews, 2025, vol. 210, issue C

Abstract: Steam gasification offers a pathway to generate synthesis gas (syngas) rich in hydrogen (H2), a crucial element in efforts to decarbonize and mitigate greenhouse gas emissions. However, the intricate web of reactions involved in the process demands predictive tools to enable its large-scale application. While models based on stoichiometry, chemical equilibrium, and data algorithms have made strides, previous works lack comprehensive comparative studies on their efficacy and adaptability. This study addresses this gap by developing and juxtaposing four models: stoichiometric, equilibrium-based, data-driven, and a hybrid approach to forecast steam gasification products against experimental data gleaned from a systematic literature review. Among these models, the hybrid variant emerges as the most accurate in predicting syngas composition, boasting an average root mean square error (RMSE) of 5.63 and an average R2 of 0.59. Moreover, it yields predictions for tar, char, and gas with respective RMSEs of 42.79 g/Nm3 syngas, 72.99 g/kg biomass, and 0.33 Nm3 syngas/kg biomass. Notably, the robust validation process of this model enhances its versatility while maintaining commendable prediction accuracy compared to the existing literature. Future enhancements could entail integrating advanced kinetic and equilibrium expressions and incorporating fresh experimental data into the training phases of data-driven models.

Keywords: Char; Tar; Hydrogen; Hybrid model; Syngas (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1364032124008773
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:rensus:v:210:y:2025:i:c:s1364032124008773

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/bibliographic
http://www.elsevier. ... 600126/bibliographic

DOI: 10.1016/j.rser.2024.115151

Access Statistics for this article

Renewable and Sustainable Energy Reviews is currently edited by L. Kazmerski

More articles in Renewable and Sustainable Energy Reviews from Elsevier
Bibliographic data for series maintained by Catherine Liu ().