Decarbonising urban transport infrastructure requires moving beyond traction-focused strategies to address the persistent gap in non-traction energy management at railway stations. Despite accounting for up to 10% of total railway sector electricity consumption, station building stock remains largely absent from renewable energy investment frameworks, with demand characterisation and supply-side planning treated in isolation across the existing literature. This study bridges that gap by proposing a novel soft-linked modelling architecture that integrates stochastic bottom-up demand simulation — via the open-source RAMP model — with mixed-integer linear programming optimisation through Hypatia, enabling simultaneous techno-economic and environmental assessment of PV-based mini-grids. The framework is applied across a structured 20-configuration matrix of four Italian station archetypes defined by Rete Ferroviaria Italiana — Bronze, Silver, Gold, and Platinum — distributed across five national macro-regions, with Milan Central Station serving as the primary validation case. Results demonstrate that cost-optimal PV deployment generates IRRs consistently above 17% across all archetypes, with southern Platinum stations exceeding 25%, payback periods of 6–8 years, and LCOEs of €80–99/MWh against a self-consumption avoided cost of €130–150/MWh. Emission-minimisation scenarios unlock two-to-three-fold increases in avoided CO₂, reaching up to 812 tonCO₂ annually per Platinum station, while remaining economically competitive — establishing a shared viability zone where environmental ambition and financial returns are simultaneously achievable. These findings reposition large urban railway stations as strategic, bankable anchors for national renewable energy portfolios, and provide a transferable planning tool directly applicable to railway electrification strategies and sustainable transport investment frameworks.
Railway stations as bankable renewable energy enablers: Stochastic demand modelling and mini-grid optimisation across Italian station archetypes / Sayed Gad, K., Tonini, F., Agati, G., Agostino, M., Borello, D., Colombo, E.. - In: RESULTS IN ENGINEERING. - ISSN 2590-1230. - 32:(2026). [10.1016/j.rineng.2026.112931]
Railway stations as bankable renewable energy enablers: Stochastic demand modelling and mini-grid optimisation across Italian station archetypes
Giuliano Agati;Domenico Borello;
2026
Abstract
Decarbonising urban transport infrastructure requires moving beyond traction-focused strategies to address the persistent gap in non-traction energy management at railway stations. Despite accounting for up to 10% of total railway sector electricity consumption, station building stock remains largely absent from renewable energy investment frameworks, with demand characterisation and supply-side planning treated in isolation across the existing literature. This study bridges that gap by proposing a novel soft-linked modelling architecture that integrates stochastic bottom-up demand simulation — via the open-source RAMP model — with mixed-integer linear programming optimisation through Hypatia, enabling simultaneous techno-economic and environmental assessment of PV-based mini-grids. The framework is applied across a structured 20-configuration matrix of four Italian station archetypes defined by Rete Ferroviaria Italiana — Bronze, Silver, Gold, and Platinum — distributed across five national macro-regions, with Milan Central Station serving as the primary validation case. Results demonstrate that cost-optimal PV deployment generates IRRs consistently above 17% across all archetypes, with southern Platinum stations exceeding 25%, payback periods of 6–8 years, and LCOEs of €80–99/MWh against a self-consumption avoided cost of €130–150/MWh. Emission-minimisation scenarios unlock two-to-three-fold increases in avoided CO₂, reaching up to 812 tonCO₂ annually per Platinum station, while remaining economically competitive — establishing a shared viability zone where environmental ambition and financial returns are simultaneously achievable. These findings reposition large urban railway stations as strategic, bankable anchors for national renewable energy portfolios, and provide a transferable planning tool directly applicable to railway electrification strategies and sustainable transport investment frameworks.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
