Optimization of low-carbon hydrogen supply chain networks in industrial clusters

This work presented an optimization-based model to aid in designing and planning a hydrogen supply chain network (HSCN) under different CO2 emission mitigation policies. The novelty of this approach lies in simultaneously, 1) tracking the resources available in HSCN and 2) designing the spatial interaction production, storage, and transportation. The model was formulated as a Mixed Integer Linear Program (MILP) to identify the minimum cost of HSCN. A case study was solved to assess the techno-economic performance of grey, blue and green hydrogen production while accounting for transport and the full energy system. A Pareto-curve was constructed to understand the trade-off between the Levelized cost of Hydrogen and emission reduction. The model also enabled the investigation of various long-distance hydrogen transport schemes; hydrogen transported as ammonia will cost 19% less than the other alternatives (liquid hydrogen, and liquid organic hydrogen carrier).