Trustworthy V2G scheduling and energy trading: A blockchain-based framework

• DOI: 10.1016/j.etran.2024.100376
• Publication Date: 2024-10-28T17:24:54Z
• Authors: Yunwang Chen; Xiang Lei; Songyan Niu; Linni Jian
• Keywords: Optimization and Control (math.OC); FOS: Electrical engineering, electronic engineering, information engineering; FOS: Mathematics; 0211 other engineering and technologies; Systems and Control (eess.SY); 02 engineering and technology; Electrical Engineering and Systems Science - Systems and Control; Mathematics - Optimization and Control

The rapid growth of electric vehicles (EVs) and the deployment of vehicle-to-grid (V2G) technology pose significant challenges for distributed power grids, particularly in fostering trust and ensuring effective coordination among stakeholders. Establishing a trustworthy V2G operation environment is crucial for enabling large-scale EV user participation and realizing V2G potential in real-world applications. In this paper, an integrated scheduling and trading framework is developed to conduct transparent and efficacious coordination in V2G operations. In blockchain implementation, a cyber-physical blockchain architecture is proposed to enhance transaction efficiency and scalability by leveraging smart charging points (SCPs) for rapid transaction validation through a fast-path practical byzantine fault tolerance (fast-path PBFT) consensus mechanism. From the energy dispatching perspective, a game-theoretical pricing strategy is employed and smart contracts are utilized for autonomous decision-making between EVs and operators, aiming to optimize the trading process and maximize economic benefits. Numerical evaluation of blockchain consensus shows the effect of the fast-path PBFT consensus in improving systems scalability with a balanced trade-off in robustness. A case study, utilizing real-world data from the Southern University of Science and Technology (SUSTech), demonstrates significant reductions in EV charging costs and the framework potential to support auxiliary grid services.