• An integrated multi-agent digital twin simulation framework is proposed. • The Sardine optimization algorithm adjusts service prices to balance charging demand. • An improved A-star algorithm cuts travel time and provides precise distance and time. • The strategy reduces spatial charging imbalance and narrows peak-valley gaps. • The guidance significantly lowers operator revenue inequality (Gini coefficient). With the large-scale deployment of electric vehicles and fast-charging stations, transportation–power systems face critical conflicts: stochastic fast-charging loads aggravate grid instability, spatiotemporal mismatches cause station congestion, and market imbalances undermine operator profitability. To address the high cost and delayed responsiveness of conventional infrastructure solutions, this paper proposes a coordinated optimization strategy for electric vehicles, fast-charging stations, and the distribution grid. An improved A-star algorithm, incorporating road impedance and intersection turning costs, enables dynamic route guidance. A sardine optimization algorithm is employed to establish a dynamic pricing model that captures competitive market dynamics through swarm intelligence. These components are embedded within a digital twin framework that supports real-time coupling among traffic flows, charging demands, and grid conditions, forming the basis of a vehicle-load migration mechanism. By combining dynamic price signals with routing guidance, the proposed strategy steers user decisions across both spatial and temporal dimensions. Simulation results demonstrate that, subject to user satisfaction constraints, compared to unguided baselines, the strategy reduces the Gini coefficient of station revenue by 70.20% and spatial imbalance by 34.51%. Notably, compared to the baseline with no electric vehicles, it reduces the average peak-valley difference by 10.30% and increases the average daily load factor by 21.22%, effectively reversing grid degradation caused by electric vehicle integration. Ultimately, this study shows that coordinated routing and pricing offer a scalable solution for managing charging demand and enhancing distribution grid stability under high electrification.
Wang et al. (Sun,) studied this question.