The transportation sector, contributing to 23% of European greenhouse gas emissions, plays a pivotal role in achieving the zero net emissions target by 2050 outlined in the EU Green Deal. The Italian railway system emerges as a strategic solution for green and cost-effective passenger and freight transport on a national scale. Anticipated impacts on the energy sector and other transport modes, including air, road, water, and light mobility, arise from increased railway capacity, correction of interregional infrastructure gaps, high-speed network improvements, system digitization, and freight transport enhancements. Quantitative analysis is crucial for identifying effective decarbonization and energy efficiency strategies aligned with national and European objectives, serving as a reference for policy formulation. Robust, open, and integrated modeling tools are employed for this analysis, accounting for energy consumption along archetypal railway lines and supporting evidence-based policy-making. The model is based on a bottom-up stochastic modeling approach to quantify and predict the Energy Demand of the Railway sector. The results are expected to guide strategic decisions within the sector, maximizing renewable energy utilization and incorporating emerging energy recovery technologies, thereby advancing the sector towards carbon neutrality. Additionally, the aim is to position the railway sector as a decarbonization hub within intersecting local contexts.

Bottom-Up Stochastic Model to Asses Energy Consumption of Typical Railway Routes in Italy

Tonini, Francesco;Gad, Khaled Sayed;Colombo, Emanuela
2024-01-01

Abstract

The transportation sector, contributing to 23% of European greenhouse gas emissions, plays a pivotal role in achieving the zero net emissions target by 2050 outlined in the EU Green Deal. The Italian railway system emerges as a strategic solution for green and cost-effective passenger and freight transport on a national scale. Anticipated impacts on the energy sector and other transport modes, including air, road, water, and light mobility, arise from increased railway capacity, correction of interregional infrastructure gaps, high-speed network improvements, system digitization, and freight transport enhancements. Quantitative analysis is crucial for identifying effective decarbonization and energy efficiency strategies aligned with national and European objectives, serving as a reference for policy formulation. Robust, open, and integrated modeling tools are employed for this analysis, accounting for energy consumption along archetypal railway lines and supporting evidence-based policy-making. The model is based on a bottom-up stochastic modeling approach to quantify and predict the Energy Demand of the Railway sector. The results are expected to guide strategic decisions within the sector, maximizing renewable energy utilization and incorporating emerging energy recovery technologies, thereby advancing the sector towards carbon neutrality. Additionally, the aim is to position the railway sector as a decarbonization hub within intersecting local contexts.
2024
2024 IEEE International Conference on Environment and Electrical Engineering and 2024 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1310553
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