Analysis of Blockchain Electricity Trading System Based on the Bayesian Game

The power industry is undergoing a rapid shift towards decarbonization, driven by the decreasing costs of low-carbon technologies and reduced competitive risks. While various power trading methodologies are emerging, current studies predominantly analyze transactions within a static game framework, lacking a comprehensive competitive analysis involving multiple participants. In real-world scenarios, trading parties engage in multiple rounds of negotiations to determine prices. To bridge this gap, we propose an innovative blockchain-based secure trading mechanism tailored for electricity quotas. This mechanism employs a bidding strategy designed for trading under conditions of incomplete information. Furthermore, we introduce a two-stage bargaining game model that utilizes the Bayesian game framework to calculate optimal bidding strategies for both buyers and sellers. This approach maximizes their revenues while ensuring the sustainability of the trading structure. Our analysis yields a Nash equilibrium solution that also satisfies Pareto optimality criteria, showcasing the theoretical and practical strengths of our proposed trading mechanism and model.