Integrating Electrified Logistics Systems Into Power Distribution Network: A Joint-Optimization Planning Approach

Abstract

Integrating electrified logistics systems with power distribution networks (PDNs) poses challenges for jointly optimizing charging infrastructure deployment and vehicle routing. Conventional methods often fail to jointly address the interdependencies between these two systems, leading to suboptimal planning and increased operational costs. To address this issue, a two-stage joint-optimization framework is proposed to simultaneously optimize EV charging station siting and electric logistics vehicle (ELV) routing within PDNs. In the first stage, a multi-objective optimization model is employed to determine optimal charging station locations, balancing infrastructure costs and traffic flow capture efficiency. In the second stage, an adaptive routing model integrates charging constraints to optimize ELV operational costs. A hybrid optimization algorithm, combining self-adaptive MOEA/D and genetic algorithm with best-first search (GABFS), is developed to enhance computational efficiency and solution robustness. The proposed approach is validated on a benchmark distribution network with logistics scenarios, demonstrating significant reductions in both capital investment for charging infrastructure and logistics operational costs. The findings underscore the importance of coordinated charging and logistics planning in accelerating the transition towards sustainable electrified logistics networks.