Coordinated Routing and Charging–Discharging Optimization for Autonomous Electric Vehicles in Logistics Delivery Scenarios

Abstract

With the electrification of urban logistics and the development of autonomous driving technology, autonomous electric vehicles (AEVs) are becoming flexible resources linking transportation systems and power grids. Considering their programmable mobile energy storage capability and task-driven operation characteristics, this paper proposes a coordinated routing and charging-discharging optimization model for logistics delivery scenarios with distribution network constraints. The model jointly considers vehicle operating economy, distribution network operation quality, and renewable energy accommodation, and optimizes the daily routing and charging-discharging schedules of an AEV fleet under practical constraints such as customer service time windows and network power flow limits. To improve computational efficiency, model reduction and linear outer approximation are adopted to reformulate the original problem as a mixed-integer linear programming model. Case studies based on a logistics transportation network and the IEEE 33-bus distribution system show that the proposed method ensures delivery task fulfillment while shifting AEV energy replenishment from passive range-driven charging to active system-oriented response. The results demonstrate reductions in fleet delivery costs and improvements in grid operating conditions.