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Hydrogen has attracted considerable attention as a clean and renewable energy carrier to potentially solve the increasingly serious problems of energy security and environmental pollution. As it can be produced from diverse feedstocks by using a variety of technologies, this study aims to develop a novel multi-criteria decision making (MCDM) mathematical framework for the sustainability assessment of multiple hydrogen production technologies (HPTs). In the proposed method, the criteria weights were determined by combining the grey relational analysis (GRA) and DEMATEL method, which can realize a relatively objective weighting process by considering the causal relationships among criteria. Moreover, the alternatives are also ranked by using the GRA approach to attain the grey correlation coefficients as indicators, which measures the closeness of the corresponding alternative with the ideal scheme. Finally, the developed MCDM method was illustrated by the sustainability prioritization of 9 HPTs. • A MCDM method was established for more objective sustainability assessment of HPTs. • An GRA-incorporated DEMATEL method was developed for determining the criteria weight. • The GRA approach was adopted for ranking the sustainability of HPTs. [ABSTRACT FROM AUTHOR]

A novel two-stage multi-criteria decision making (MCDM) method is proposed with the aim to select the most sustainable hydrogen production technology (HPT) by considering the preference information on both attributes and alternatives. In the first stage of the method, the initial sustainability ranking of the alternative HPTs was achieved by using the FBWM (Fuzzy Best-Worst Method) to determine the weights of the criteria and the fuzzy TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) method to prioritize the sustainability of alternative HPTs. While, in the second stage, a novel Preference Ranking Linear Programming Method (PRLPM) was used to acquire the final sustainability ranking according to the alternative preference information by following the principle of the outranking method. The proposed method was illustrated by a case study with 8 HTPs, demonstrating that the developed two-stage MCDM method can reflect the alternative preference of the decision-maker more accurately for selecting the most preferred alternative among various HTPs. • The MCDM framework divides the sustainability decision-making into two stages. • Fuzzy best-worst method and fuzzy TOPSIS were used in the first stage. • A novel method based on preference information on alternatives is proposed. • The framework combines preference information on attributes and alternatives. [ABSTRACT FROM AUTHOR]

Hydrogen has emerged as one of the most promising players in the future energy system for a better life due to multiple advantages, it is important to identify the most sustainable technology for producing hydrogen among several alternatives. This study aims to propose a novel multi-criteria decision making (MCDM) framework for prioritizing hydrogen production technologies under data uncertainties by combining the methods of interval best-worst method (IBWM), interval entropy technique (IET), and interval best-worst projection (IBWP). In the framework, the IBWM and the IET methods were integrated to offer a comprehensive weighting result by capturing both the uncertain subjective judgments and uncertain objective information regarding the importance of multiple criteria; the IBWP approach was introduced to offer a rigorous ranking result by aggregating both the absolute performance and relative balance of the alternatives regarding the multi-criteria system in uncertain conditions. An illustrative case considering five hydrogen production technologies was studied to verify the feasibility of the proposed framework, while results comparisons and sensitivity analysis were implemented to indicate the necessities and advantages of the developed MCDM methods. • A novel framework was proposed for selecting hydrogen production technology. • Uncertainties were incorporated into the sustainability assessment framework. • The interval BWM and the interval entropy were combined for weighting the criteria. • A novel IBWP method was developed for ranking technology alternatives. [ABSTRACT FROM AUTHOR]