Abstract: This paper presents a methodology for finding scalable implementation paths for distributed green hydrogen systems in urban residential communities, based on a pre-2024-2025 study. Specifically, a multi-objective optimization approach is applied using the MOPSO (Multi- Objective Particle Swarm Optimization) algorithm, which efficiently addresses the many factors that influence the adoption of these systems. Furthermore, the research is extended to two other optimization methods: AGEII (Approximation-guided Evolutionary Multi-Objective Algorithm II) and FDV (Fuzzy Decision Variables Framework). These methods are compared in terms of their performance and effectiveness in generating optimal solutions. The results show that the AGE-II method significantly outperforms the other two methods, achieving more efficient and suitable solutions for the implementation of green hydrogen systems in urban environments. In this way, this study contributes to the discussion on the development of sustainable technologies and the transition to renewable energy.

Keywords: Green hydrogen, residential communities, multi-objective optimization, algorithm, MOPSO, AGE-II, FDV, Pareto front

Pages: 7-17

WSEAS Transactions on