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Evaluation of sustainable hydrogen production technologies on an industrial scale using comparative analysis of decision-making methods

  • Role of Hydrogen in Decarbonization: Energy Policies and Strategies for Transition
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Abstract

Due to its various advantages in different industrial fields, hydrogen can provide energy based on sustainability goals and recreates a critical function in the economy of countries. In this regard, evaluating hydrogen production technologies on an industrial scale is necessary for industrial development and economic growth. Therefore, this study proposes a comprehensive, integrated framework of hybrid fuzzy decision-making for assessing hydrogen production technologies in Iran. In addition to considering sustainability factors, political, technical, and reliability indicators are also assessed in this research to make a comprehensive assessment. The Fuzzy Step-wise Weight Assessment Ratio Analysis (F-SWARA) technique determines the importance of indicators, and the Fuzzy Weighted Aggregates Sum-Product Assessment (F-WASPAS) approach ranks technologies. The weighing findings indicated that the sub-indices of investment cost, technical infrastructure development, and implementation costs were introduced as the most significant sub-indices with weights of 0.226, 0.151, and 0.126, respectively. The evaluation findings with the F-WASPAS method and comparative analysis with various decision-making methods revealed that electrolysis based on solar energy and electrolysis based on wind energy technologies had the highest preference. In this regard, the infrastructure and costs of hydrogen production can be improved by presenting various incentives, such as improving financial conditions while attracting investment and increasing cooperation with top companies. So, sustainable development, economic growth, and industrial development are provided.

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Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

F-ARAS:

Fuzzy Additive Ratio Assessment

F-CoCoSo:

Fuzzy Combined Compromise Solution

F-SWARA:

Fuzzy Step-wise Weight Assessment Ratio Analysis

F-TOPSIS:

Fuzzy Technique for Order Preference by Similarity to Ideal Solution

F-WASPAS:

Fuzzy Weighted Aggregates Sum-Product Assessment

MCDM:

Multi-criteria decision-making

\({P}_{i}\) :

The crisp relative importance of option i based on the WPM model

\({\widetilde{P}}_{i}\) :

The fuzzy relative importance of option i based on the WPM model

\({Q}_{i}\) :

The crisp relative importance of option i based on the WSM model

\({\widetilde{Q}}_{i}\) :

The fuzzy relative importance of option i based on the WSM model

\(\widetilde{{q}_{j}}\) :

The fuzzy value of the initial significance of the factor j

\({\tilde{w}}_{j}\) :

The fuzzy value of the final significances of the factor j

\({WPS}_{i}\) :

The crisp score of option i

\({\widetilde{x}}_{ij}\) :

The fuzzy value for alternative i in factor j

\({\widetilde{\overline{x}} }_{ij}\) :

The normalized fuzzy value for alternative i in factor j

\({\widetilde{\widehat{X}}}_{q}\) :

The matrix of the WSM model

\({\widetilde{\widehat{X}}}_{p}\) :

The matrix of the WPM model

\(\theta\) :

Interactive variable for exchange between WSM and WPM models

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Contributions

Conceptualization, supervision, methodology, investigation, formal analysis, and writing—the original draft was done by Seyyed Jalaladdin Hosseini Dehshiri. Supervision, software, and resources were done by Ali Mostafaeipour. Validation and writing—review and editing were performed by Ttu Le and Ali Rezaeian Sabagh. The first draft of the manuscript was written by Seyyed Jalaladdin Hosseini Dehshiri and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Ali Mostafaeipour.

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The authors declare no competing interests.

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Hosseini Dehshiri, S.J., Mostafaeipour, A., Le, T. et al. Evaluation of sustainable hydrogen production technologies on an industrial scale using comparative analysis of decision-making methods. Environ Sci Pollut Res (2024). https://doi.org/10.1007/s11356-024-33535-z

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  • DOI: https://doi.org/10.1007/s11356-024-33535-z

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