STraM: A strategic network design model for national freight transport decarbonization
提出一个名为STraM的两阶段随机规划模型，用于国家货运脱碳的战略网络设计，考虑燃料技术发展、车队惯性和长期不确定性，通过挪威案例展示其有效性。
National freight transport models are valuable tools for assessing the impact of various policies and investments on achieving decarbonization targets under different future scenarios. However, these models struggle to address several critical elements necessary for strategic planning, such as the development and adoption of new fuel technologies over time, inertia in transport fleets, and uncertainty surrounding future transport costs. In this paper, we develop a strategic network design model, named STraM, that explicitly incorporates these key factors. STraM, being a two-stage stochastic program, effectively handles long-term uncertainty by considering different future scenarios in its decision-making process.It provides a network design plan that includes infrastructure investments and fuel technology decisions, aiming to achieve cost-effective decarbonization of the freight transport system. The model output can be used as input for higher-resolution national freight transport models to yield results with greater operational detail. We demonstrate the application of STraM through a case study of Norway, offering valuable insights into the strategic planning of decarbonizing freight transport. • STraM models multi-period freight decarbonization with long-term uncertainty. • Identifies cost-effective pathways for fuel adoption and infrastructure investments. • Explicit uncertainty modeling improves results by 13.6% over deterministic methods. • Carbon pricing is effective for emissions reduction but requires high price levels. • Results show the need for dynamic models over traditional static ''what-if'' approaches.