Selection of underground hydrogen storage systems using a novel fuzzy model


Görçün Ö. F., DEMİR G., PAMUCAR D., Simic V.

Energy Conversion and Management, cilt.352, 2026 (SCI-Expanded, Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 352
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1016/j.enconman.2026.121082
  • Dergi Adı: Energy Conversion and Management
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, Environment Index, INSPEC
  • Anahtar Kelimeler: ARTASI, Dombi-Bonferroni Mean Aggregation, Fuzzy set, Storage system selection, Underground Hydrogen storage, WENSLO
  • Sivas Cumhuriyet Üniversitesi Adresli: Evet

Özet

Storing hydrogen resources underground can accelerate the transition to renewable energy, facilitate energy supply security, and the adoption and expansion of hydrogen energy, a clean energy source. The selection of sustainable underground hydrogen storage systems is a critical research topic for addressing environmental issues caused using fossil fuels. However, decision-makers still lack a consensus-based and sustainability-oriented framework that can comparatively evaluate alternative underground hydrogen storage geological formations under economic, environmental, social, and technical uncertainties, which constitutes a critical barrier to large-scale hydrogen deployment. This issue has become more prominent as fossil-based fuel reserves are gradually decreasing worldwide. In contrast, researchers and practitioners lack a consensus on which underground storage method is most suitable for economical, safe, and efficient hydrogen storage. If this problem is not addressed correctly and reasonable solutions are not obtained, continued dependence on fossil fuels may persist. Alternatively, other renewable energy sources with relatively lower efficiency and performance may be adopted. In both cases, significant delays in achieving the global sustainability goal are likely to occur. We propose an integrated fuzzy decision-making framework (F-WENSLO & Dombi-Bonferroni & F-ARTASI) to address this selection problem under uncertainty. The proposed framework integrates fuzzy WENSLO (Weights by ENvelope and SLOpe) for robust sustainability-based criteria weighting, the Dombi–Bonferroni aggregation operator to model interdependencies among criteria explicitly, and the fuzzy ARTASI (Alternative Ranking Technique based on Adaptive Standardized Intervals) method to provide flexible and stable ranking of geological alternatives beyond rigid distance-based approaches. Key advantages of the proposed model include producing reliable and consistent solutions that accurately reflect real-world conditions for selecting sustainable underground hydrogen storage systems. The results revealed that C14 (job creation and employment opportunities) (0.0603) is the most influential criterion in selecting the most suitable storage system. In addition, salt caverns with an Ωi of 10,5167 have achieved the highest score, placing them in the first position, and it is the most suitable and advantageous underground hydrogen storage option. The suggested decision-making tool can yield reliable and robust solutions in real-world conditions, enabling the planning of infrastructure design for hydrogen energy systems that incorporate sustainability dimensions. In that regard, the developed model possesses the characteristics of an efficient and practical roadmap that can guide policymakers and decision-makers in transitioning from fossil-based energy sources to renewable energy sources. It has been implemented to evaluate underground geological formations that could facilitate the storage of hydrogen energy underground, serving as a case study. The reliability and robustness of this tool have been verified through extensive validation tests.