Abstract
Electrifying port horizontal transportation is constrained by downtime and deadheading from fixed charging/swapping systems, large battery sizes, and the lack of integrated decision tools for life-cycle emissions. This study develops a carbon-efficiency-centered bi-objective optimization framework benchmarking Mobile Charging Stations (MCSs) against Fixed Charging Stations (FCSs) and Battery Swapping Stations (BSWSs). The framework integrates operational parameters such as charging power, range, dispatch, and non-operational mileage, along with grid carbon intensity, battery embodied emissions, and carbon-market factors. It generates Pareto fronts using the NSGA-II algorithm with real port data. Port horizontal transportation refers to the movement of goods within the port area, typically involving the use of specialized vehicles to transport containers short distances across the terminal. Results show that MCSs can reuse idle windows to reduce deadheading and infrastructure demand, yielding significant economic improvements. The trade-off between emissions and profitability is context-dependent: at low-to-moderate reuse levels, low-carbon and profitable solutions coexist; beyond a threshold of approximately 0.5–0.75, the Pareto fronts shift to high emissions and high profits, highlighting the context-specific advantages of MCSs for port-infrastructure planning. MCSs thus provide context-dependent advantages over FCSs and BSWSs, offering practical guidance for port infrastructure planning and carbon-informed policy design.