A Review of Multi-Agent Intelligent Interaction Technologies for Renewable Energy Vehicles Under a Vehicle-Station-Traffic-Grid Coupling System

The rapid development of renewable energy vehicles (REVs) has deepened the coupling between transportation and power systems, leading to the formation of the vehicle–station–traffic–grid (VSTG) coupled system. This paper provides a systematic review of multi-agent intelligent interaction technologies for REVs under the VSTG framework, covering the evolutionary process of VSTG systems, the composition and coupling mechanisms of vehicle–station–traffic–grid subsystems, the objectives and constraints of heterogeneous agents, representative V2X interaction modes, deployment-related standards, and collaborative optimization methods. First, the development trajectory of VSTG systems is traced, from independent planning and uncoordinated charging to V2G integration and V2X multi-network interaction. Second, a multi-agent interaction framework is established to characterize vehicle agents, charging station agents, grid agents, traffic management agents, user/operator agents, aggregator/platform agents, and roadside infrastructure agents. In addition, representative vehicle-to-everything (V2X) modes, including V2L, V2H, V2B, V2mG, and V2G, are compared in terms of their operating principles, application scenarios, and technical characteristics. Moreover, various optimization methods for the coupled system are reviewed. Finally, key challenges, including cross-domain coupling complexity, operational uncertainty, interoperability, battery degradation, and engineering deployment, are discussed, and future research directions are proposed. This review provides a structured reference for the modeling, optimization, and practical deployment of intelligent VSTG systems.

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Publication Details

Journal
Processes
Published
2026-06-25
DOI
https://doi.org/10.3390/pr14132068
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00

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article

A Review of Multi-Agent Intelligent Interaction Technologies for Renewable Energy Vehicles Under a Vehicle-Station-Traffic-Grid Coupling System

Lei Zhou, Ying Liu, Yuanweiji Hu, Bo Yang et al.
Processes
Electric Vehicles and Infrastructure
article

A Review of Multi-Agent Intelligent Interaction Technologies for Renewable Energy Vehicles Under a Vehicle-Station-Traffic-Grid Coupling System

Lei Zhou, Ying Liu, Yuanweiji Hu, Bo Yang, Chuanyun Tang, Zhe Jiang
article en

Abstract

The rapid development of renewable energy vehicles (REVs) has deepened the coupling between transportation and power systems, leading to the formation of the vehicle–station–traffic–grid (VSTG) coupled system. This paper provides a systematic review of multi-agent intelligent interaction technologies for REVs under the VSTG framework, covering the evolutionary process of VSTG systems, the composition and coupling mechanisms of vehicle–station–traffic–grid subsystems, the objectives and constraints of heterogeneous agents, representative V2X interaction modes, deployment-related standards, and collaborative optimization methods. First, the development trajectory of VSTG systems is traced, from independent planning and uncoordinated charging to V2G integration and V2X multi-network interaction. Second, a multi-agent interaction framework is established to characterize vehicle agents, charging station agents, grid agents, traffic management agents, user/operator agents, aggregator/platform agents, and roadside infrastructure agents. In addition, representative vehicle-to-everything (V2X) modes, including V2L, V2H, V2B, V2mG, and V2G, are compared in terms of their operating principles, application scenarios, and technical characteristics. Moreover, various optimization methods for the coupled system are reviewed. Finally, key challenges, including cross-domain coupling complexity, operational uncertainty, interoperability, battery degradation, and engineering deployment, are discussed, and future research directions are proposed. This review provides a structured reference for the modeling, optimization, and practical deployment of intelligent VSTG systems.

ProcessesVol. 14(13)
Kunming University of Science and Technology (CN)
National Natural Science Foundation of China
Industry, innovation and infrastructure
Openalex Percentile: Top 11%
Electric Vehicles and Infrastructure
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