Optimizing hydrogen supply chains for energy-intensive industries: A cost-efficient framework

Abstract

This study develops an optimization workflow that connects hydrogen supply chain design, hourly operation, screening of parameters, and two-stage stochastic planning. Five supply configurations and three demand profiles for a synthetic steel hub in Asturias (Spain) are compared. Reference delivered costs range from 4.402 to 5.191 €/kg without SMR, and are 3.076 €/kg with SMR and CCS under the stated economic assumptions. The dominant cost drivers shift from electrolysis and wind to hydrogen procurement or SMR as supply options change. Joint screening and conditional sensitivity analysis also reveal different roles for technologies unused in reference design. Across ten historical scenarios, cases B, D and E yield values of the stochastic solution (VSS) of 0.323, 0.273 and 0.006 €/kg. Stochastic planning increases storage in some configurations and reduces it in others. The combined workflow identifies cost drivers, investment substitutions, and feasibility losses that a single deterministic cost comparison would leave unresolved.