We present a framework to support decarbonization of energy intensive transportation systems offering periodic service on expansive networks (e.g., freight rail, trucking, and intercity bus services). The framework consists of two optimization problems that respectivelyaddress (i) flow selection and facility location, and (ii) energy sourcing/procurement at the service facilities to enable the selected flows. The framework generalizes mixed integer linear programming formulations for and models appearing in the literature to situations where it is of interest to account for repositioning of assets along cyclical trajectories to allow for periodic service, and to account for intermediate flow capture (i.e., trip chaining). The framework also consists of a minimum cost network flow model to determine optimal energy sourcing and distribution strategies, which dictate capacity requirements at the service facilities. The energy demands are obtained from the solution to the flow selection and facility location model. To illustrate the framework, we analyze the deployment of charging stations to support battery-electric locomotive service on a subset of the US freight rail network (i.e., an aggregate network of 3 Class I Railroads). The results show that the deployment of 30 charging stations can support battery-electric locomotives (with 1600-km ranges) to serve 86% of distance-weighted flows (ton-km) and reduce emissions by approximately 50%.

中文翻译：

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优化服务网络以支持货运铁路脱碳：流程选择、设施选址和能源采购

我们提出了一个框架来支持能源密集型运输系统的脱碳，在广泛的网络上提供定期服务（例如货运铁路、卡车运输和城际巴士服务）。该框架由两个优化问题组成，分别解决（i）流量选择和设施位置，以及（ii）服务设施的能源采购/采购以启用所选流量。该框架将文献中出现的混合整数线性规划公式和模型推广到需要考虑沿循环轨迹重新定位资产以允许定期服务并考虑中间流捕获（即行程链）的情况。 。该框架还包括一个最小成本网络流模型，用于确定最佳能源采购和分配策略，这决定了服务设施的容量要求。能源需求是从流量选择和设施选址模型的解中获得的。为了说明该框架，我们分析了美国货运铁路网络子集（即 3 条一级铁路的聚合网络）上支持电动机车服务的充电站的部署。结果显示，部署30个充电站可支持纯电动机车（续航里程1600公里）服务86%的距离加权流量（吨公里），并减少约50%的排放。