Design and Analysis of Small-Scale Hydrogen Valleys Success Factors: A Stratified Network-Based Hybrid Fuzzy Approach

Abstract

Hydrogen energy, one of the renewable energy sources, plays a crucial role in combating climate change, since its usage aims to reduce carbon emissions and enhance energy security. As the global energy trend moves toward cleaner alternatives, countries start to adapt their energy strategies. In this transition, hydrogen is one of the energy sources with the potential to increase long-term energy security. Developing countries face challenges, such as high energy import dependency, rising industrial demand, and the need for infrastructure modernization, making hydrogen valleys one of the viable solutions, since they integrate hydrogen production, storage, distribution, and utilization at one facility. However, establishing small-scale hydrogen valleys requires a comprehensive decision-making strategy consisting of technical, financial, environmental, social, and political factors while addressing uncertainties in the system. To systematically manage the process, this study proposes a Z-number-based fuzzy cognitive mapping approach, which models the interdependencies among success factors, supported by Z-number Decision-Making Trial and Evaluation Laboratory for structured prioritization with a multi-expert perspective. The results indicate that Financial Factors emerged as the most critical category, with Government Incentives, Infrastructure Investment Cost, and Land Acquisition Cost ranking as the top three sub-success factors. Availability of Skilled Workforce and Regional Energy Supply followed in importance, which demonstrates the importance of social and technical dimensions in the hydrogen valley development. These findings demonstrate the critical role of policy support, infrastructure readiness, and workforce availability in the design process. Sensitivity analyses are also conducted to present robustness of the given decisions for the analysis of the results. Based on the results and analyses, possible implications based on the policy and practical dimensions are also discussed. By integrating fuzzy logic and Z-numbers, the study aims to minimize loss of information, enhances the analytical background for decision-making, and provides a strategic roadmap for hydrogen valley development.