Beyond black-box rail transport: how aggregated energy system optimisation models can hide infeasible planning pathways and underestimate decarbonisation costs — evidence from Italy to 2050

The railway sector is a cross-cutting sector between the transport and power sectors due to its dual role as the most electrified transport mode and a major industrial electricity load. Consequently, rail expansion can simultaneously reshape mobility demand and power system loading, underlining its potential as a key contributor to decarbonisation pathways. However, Energy System Optimisation Models (ESOMs) commonly represent transport demand in aggregated form, omitting or inadequately representing the infrastructure, fleet composition, and operational constraints that determine the feasibility and cost of railway-led decarbonisation. This study develops a modelling framework that explicitly disaggregates the railway sector within a national ESOM, linking rolling stock technologies, infrastructure capacity, and transport service demand to the power system. The framework extends the Hypatia model through a dual-input transformation in which rail service production requires both traction energy and track-capacity utilisation as co-mandatory inputs, embedding hard infrastructure constraints directly into the cost-minimisation problem. The approach is applied to Italy through a scenario analysis for 2020–2050, combining two energy pathways (reference and policy decarbonisation scenarios) with alternative railway supply options, by varying infrastructure investment regimes, and demand-side management strategies. Overall, the results show that a disaggregated representation of the railway sector enables a more detailed and consistent assessment of the costs and benefits of rail-led decarbonisation, revealing that an aggregated model can underestimate system costs by 79% (240–406 B€, discounted). In this setting, rail emerges as both a significant mitigation lever and an infrastructure challenge, with substantial emissions reduction potential and meaningful demand-side management benefits.