Abstract
Hydrogen is increasingly recognized as a key player in future energy systems. However, its production technologies—Steam Methane Reforming (SMR) and electrolysis—present trade-offs. SMR, the dominant method, is cost-effective but has a significant carbon footprint, emitting substantial greenhouse gases (GHGs). In contrast, electrolysis, powered by renewable energy sources, offers a cleaner alternative, albeit at a higher cost. While current hydrogen system optimizations primarily focus on cost reduction and GHG mitigation, they often neglect broader environmental impacts. This paper addresses the challenge of modeling a hydrogen supply chain (HSC) that achieves strong environmental performance at a relatively affordable cost. To this end, a supply chain design optimization is coupled with Life Cycle Assessment (LCA). The novelty of this work lies in the integration of multiple LCA indicators in the supply chain design optimization, rather than focusing solely on costs and Global Warming Potential. The model employs a multi-period (2025–2050) mixed-integer linear programming (MILP) formulation, implemented in the General Algebraic Modeling System (GAMS) environment, using CPLEX as the solver. The Bourgogne-Franche-Comté region is used as a case study to illustrate the framework. Initial optimization results highlight how varying the focus on different parameters can lead to distinct solutions and provide insights into the interactions between indicators. Future research will aim to reduce the dimensionality in multi-objective optimization to improve efficiency while maintaining environmental sustainability in the development of hydrogen networks.