Robust Optimal Charging Guidance Strategy for Electric Logistics Vehicles under EVs-Traffic-Distribution Collaborative Model

The growing trend of electric logistic vehicle (ELV) is bringing the coupling relationship between the traffic network (TN) and the power distribution network (PDN) to a new level, while the unordered charging of electric vehicles poses a significant impact on the security of the power grid. To address this issue, this paper introduces the concept of coordinated optimization for electric logistics vehicle charging guidance con-sidering the uncertainty of renewable energy generation and load. A traffic-distribution coupled network model based on graph theory is established and then transformed into a two-stage robust optimization problem. The upper stage focuses on electric vehicle charging guidance, while the lower stage is dedicated to optimizing power allocation in the distribution network under the worst-case scenarios. The proposed model is then solved iteratively using the column-and-constraint generation (C&CG) algorithm after linearization. Finally, the efficacy of the proposed methodology is validated through a case study involving the coupling of traffic and power distribution networks, and a comprehensive comparison of different charging strategies is presented.