Robustness Maps for Hydrogen Delivery Mode Selection Under Construction Cost Uncertainty: Application to Korean Hydrogen Corridors

Whether hydrogen should be delivered by pipeline or by truck is a large and largely irreversible investment decision. The cost information needed for this decision varies by a factor of several across the literature, and conventional single-value comparisons can reverse their conclusions depending on which value is selected. This study introduces a risk classification framework from construction management to define cost uncertainty as probability distributions grounded in the literature and in Korean empirical records. Four delivery modes were compared, specifically new pipelines, repurposed pipelines, high-pressure tube trailers, and liquefied hydrogen tanker trucks. Their twenty-year total costs were computed by Monte Carlo simulation with 20,000 draws for each combination of transport distance (10–500 km) and annual demand (1000–1,000,000 t/yr). The results are summarized as robustness maps that display only the mode with the lowest cost in at least 80% of the 20,000 cost scenarios. The synthesized cost distributions are consistent with the Korean cost records available for comparison, one of which was reserved from the model inputs. Where a repurposable pipeline exists, repurposing is effectively the only robust choice. In new corridors, new pipelines become robustly justified from 19,191 t/yr at the reference distance of 150 km, below which lies a gray band where assumptions decide the outcome. The viability of liquefied hydrogen delivery is determined not by technology but by who bears the liquefaction plant cost, and this boundary alone raises the share of the map on which liquefied hydrogen delivery is robust from 1% to 72.4%. The effective levers that advance the transition to pipelines are the operation and maintenance (O&M) rate (45.8%), the planning horizon (38.3%), and demand commitment (23.2%) rather than the carbon price (2.2%). Four announced Korean plans are located on the map in positions consistent with their project stages, which indicates that the framework can serve as a planning-stage diagnostic tool.