A data-driven multi-criteria optimization of a biogas-fed s-graz cycle combined with biogas steam reforming and Claude cycle for sustainable hydrogen liquefaction

• Biogas steam reforming and Claude cycle combined with biogas-based S-Graz power plant. • Data-driven multi-facet scenario to study a hydrogen production-liquefaction process. • Thermodynamic, exergoeconomic, and sustainability assessments of the proposed system. • Optimum exergy efficiency and liquefied hydrogen output equal 0.5154 and 2.23 lit/s. • Optimum sustainability index and specific cost of products equal 2.06 and 17.88 $/GJ. The purpose of this research is to develop and optimize an innovative trigeneration approach using biogas fuel, focusing on hydrogen production and liquefaction . This approach will increase the long-term sustainability associated with biogas utilization and lower corresponding irreversibility and environmental concerns. The proposed system employs a biogas-powered S-Graz plant enhanced with a carbon capture unit, a biogas steam reforming subsystem for hydrogen production , and a Claude cycle for hydrogen liquefaction. The configuration is modeled and analyzed to determine the system’s feasibility regarding thermodynamic, exergoeconomic, and sustainability factors. Following this, a data-driven optimization method is employed to reduce the optimization time and enhance its accuracy through MATLAB software, utilizing ANN models combined with NSGA-II and TOPSIS methods. The optimization procedure objective functions include total exergy efficiency, liquefied hydrogen production rate, and unit cost of products, yielding their optimal values of 0.5154, 2.23 lit/s, and 17.88 $/GJ, respectively. The optimization also indicates the total exergy destruction at a rate of 18.293 MW and the sustainability index of 2.06. Besides, the total investment cost rate, net present value, and exergoeconomic factor are found at 372.4 $/h, 33.99 M$, and 15.19 %, respectively. These results demonstrate the substantial economic and environmental benefits of integrating hydrogen production into biogas-based multi-generation systems, highlighting the potential for improved exergy efficiency and reduced environmental impact. This work exhibits the way for more sustainable energy solutions, contributing significantly to the development of cleaner technologies considering biogas utilization.

Authors

Institutions

Publication Details

Journal
Fuel
Published
2025-02-18
DOI
https://doi.org/10.1016/j.fuel.2025.134700
Citations
21
Primary Topic
Hybrid Renewable Energy Systems
Type
article
Field-Weighted Citation Impact
11.17
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A data-driven multi-criteria optimization of a biogas-fed s-graz cycle combined with biogas steam reforming and Claude cycle for sustainable hydrogen liquefaction

Hassan Athari, Milad Feili, Hadi Ghaebi, Maghsoud Abdollahi Haghghi
21 citations
Fuel
Hybrid Renewable Energy Systems
11.17
article

A data-driven multi-criteria optimization of a biogas-fed s-graz cycle combined with biogas steam reforming and Claude cycle for sustainable hydrogen liquefaction

Hassan Athari, Milad Feili, Hadi Ghaebi, Maghsoud Abdollahi Haghghi
article en
21 citations

Abstract

• Biogas steam reforming and Claude cycle combined with biogas-based S-Graz power plant. • Data-driven multi-facet scenario to study a hydrogen production-liquefaction process. • Thermodynamic, exergoeconomic, and sustainability assessments of the proposed system. • Optimum exergy efficiency and liquefied hydrogen output equal 0.5154 and 2.23 lit/s. • Optimum sustainability index and specific cost of products equal 2.06 and 17.88 $/GJ. The purpose of this research is to develop and optimize an innovative trigeneration approach using biogas fuel, focusing on hydrogen production and liquefaction . This approach will increase the long-term sustainability associated with biogas utilization and lower corresponding irreversibility and environmental concerns. The proposed system employs a biogas-powered S-Graz plant enhanced with a carbon capture unit, a biogas steam reforming subsystem for hydrogen production , and a Claude cycle for hydrogen liquefaction. The configuration is modeled and analyzed to determine the system’s feasibility regarding thermodynamic, exergoeconomic, and sustainability factors. Following this, a data-driven optimization method is employed to reduce the optimization time and enhance its accuracy through MATLAB software, utilizing ANN models combined with NSGA-II and TOPSIS methods. The optimization procedure objective functions include total exergy efficiency, liquefied hydrogen production rate, and unit cost of products, yielding their optimal values of 0.5154, 2.23 lit/s, and 17.88 $/GJ, respectively. The optimization also indicates the total exergy destruction at a rate of 18.293 MW and the sustainability index of 2.06. Besides, the total investment cost rate, net present value, and exergoeconomic factor are found at 372.4 $/h, 33.99 M$, and 15.19 %, respectively. These results demonstrate the substantial economic and environmental benefits of integrating hydrogen production into biogas-based multi-generation systems, highlighting the potential for improved exergy efficiency and reduced environmental impact. This work exhibits the way for more sustainable energy solutions, contributing significantly to the development of cleaner technologies considering biogas utilization.

FuelVol. 390
Urmia University (IR), University of Mohaghegh Ardabili (IR)
Responsible consumption and production
Openalex Percentile: Top 1%
Hybrid Renewable Energy Systems
11.17
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.