面向电动卡车的充电站位置规划：考虑需求与电网不确定性
摘要
实现长途货运的脱碳化需要大规模部署高功率充电设施。本文研究了一个多期充电站位置问题，确定在不确定的未来需求和本地电网容量可用性条件下，为电动重型货车部署充电容量的空间和时间。该问题 formulated as a two-stage stochastic mixed-integer program that maximizes covered electric freight flow. Feasible truck routes are generated a priori using a resource-constrained label-setting algorithm that enforces range limitations and driving-break regulations. To solve large-scale instances, an integer L-shaped decomposition method embedded in a branch-and-cut framework and accelerated by a deterministic warm start is implemented. Computational experiments are conducted on a nationwide Norwegian case study based on real candidate locations provided by a charging station operator. The approach solves instances intractable for a monolithic formulation and achieves near-optimal solutions within practical runtimes. For larger networks, the value of the stochastic solution is substantial, highlighting the importance of explicitly modeling uncertainty in long-term infrastructure planning. Optimal investments prioritize major freight corridors in early periods and subsequently reinforce and expand the network. Grid capacity constraints discourage large, concentrated stations and shift deployments toward more distributed layouts. Covered demand increases rapidly at low budget levels but exhibits diminishing returns as the network approaches saturation.
引用
@article{arxiv.2603.01782,
title = {Charging station location planning for electric trucks under demand and grid uncertainty},
author = {Céline Pagnier and Tord Gunnar Holen and Thomas Haugen de Lange and Patrick Levin and Steffen J. S. Bakker and Peter Schütz},
journal= {arXiv preprint arXiv:2603.01782},
year = {2026}
}