Research Information System
Results in Engineering, vol.30, 2026 (ESCI, Scopus)
The integration of hydrogen energy storage systems into modern power systems is increasingly essential to improve grid flexibility, stability, and decarbonization. Circular economy principles offer the potential to minimize material waste and reduce the overall environmental impact of energy systems. Despite its significance, the literature lacks comprehensive studies on the key factors influencing circular hydrogen storage integration. This study aims to develop a novel decision-support model that assists in the technical planning and integration of circular hydrogen energy storage systems within smart grids. The genetic algorithm provides optimization for complex datasets, outperforming conventional techniques. Similarly, ant colony optimization evaluates alternative investment scenarios, offering advantages over other weighting methods. By leveraging these advanced methodologies, this study provides a strategic roadmap for sustainable hydrogen storage investments, reducing uncertainties and enhancing decision accuracy. The findings indicate that use of recycling technologies and effectiveness of resource footprint are the most essential investment criteria for circular-oriented hydrogen storage systems. On the other side, it is also identified that cost efficiency with performance-oriented recovery rates and artificial intelligence-driven optimization of circularity process are the most appropriate investment strategy alternatives for these projects.