Blockchain-based game theoretical framework for V2V and V2G energy trading in carbon-intelligent internet of vehicles

Abstract

Electric vehicles (EVs) are becoming more popular as people try to live more eco-friendly ways. A major challenge slowing down their widespread adoption is limited driving range and inadequate charging infrastructure, particularly in rural and highway areas where charging station deployment remains uneven. This paper proposed a blockchain-based framework for Vehicle-to-Vehicle (V2V) and Vehicle-to-Grid (V2G) energy trading to address these challenges, enabling efficient decentralized energy exchanges. The framework integrates three-game theory models, contract theory, Bayesian game theory, and evolutionary game theory to optimize trading strategies, ensure fairness, and enhance grid stability. By utilizing a lightweight blockchain architecture on Hyperledger Fabric, the proposed system ensures secure, transparent, and efficient transactions while reducing operational costs. The performance evaluations show that the proposed framework surpasses existing methods, reaching a transaction throughput of 49.8 transactions per second (TPS) for payment settlements and 44.7 TPS for energy trade proposals, with an average latency ranging from 0.09 to 0.18 seconds. Resource utilization analysis shows that peer nodes experience an average CPU usage of 23.76% and memory consumption of 169.5 MB during trade proposals. These results highlight the robustness and scalability of the framework in enabling decentralized, carbon-intelligent energy trading, offering a promising solution for advancing sustainable and intelligent EV energy ecosystems.