中国电机工程学报2025，Vol.45Issue(z1)：31-45,15.DOI:10.13334/j.0258-8013.pcsee.242934
P2P交易随机博弈决策与复杂网络协同演化分析
The Analysis of P2P Trading Stochastic Game Decision-making and Co-evolution of Complex Networks
摘要
Abstract
The rise of peer-to-peer(P2P)trading has provided an important way to promote the efficient utilization of renewable energy by end-user prosumers.However,the high uncertainty in prosumer trading behaviors and the complexity of their competitive-cooperative relationships severely hinder the further development of P2P trading.Moreover,the lack of attention to the long-term evolution of trading networks in existing research significantly limits the scientific formulation of relevant policies.To address these issues,this paper proposes a stochastic game-based decision-making and complex network co-evolution analysis method for P2P trading,aiming to systematically optimize trading strategies and uncover the long-term evolution characteristics of trading networks.Firstly,to address the uncertainty in trading behaviors,stochastic game theory is applied to P2P trading,constructing a dynamic trading model that maximizes the economic benefits of prosumers and determines the optimal trading price using a demand-supply ratio-based pricing mechanism.Secondly,by employing stochastic game theory,the multi-period trading behavior of prosumers is modeled as a Markov decision process,thereby enabling multi-stage dynamic strategy adjustment and effectively addressing the limitations of conventional trading models that neglect the inherent uncertainty in prosumer trading behavior..Subsequently,based on rigorous mathematical theories,the existence of Nash equilibrium in stochastic game for P2P trading is proved,laying a theoretical foundation for the practical application of stochastic game.Furthermore,a P2P trading network is constructed using the optimal threshold method and complex network theory,with community division achieved through the Fast Newman algorithm.The competitive-cooperative relationships among prosumers are analyzed using Pearson coefficients to reveal the dynamic structural evolution of the trading network.Finally,numerical simulations verify the proposed method's effectiveness and feasibility in optimizing prosumer trading strategies,improving economic benefits,and analyzing the long-term evolution of trading networks.关键词
点对点交易/随机博弈/复杂网络/协同演化/皮尔逊系数/最佳阈值法/竞合关系Key words
peer-to-peer(P2P)trading/stochastic game theory/complex network/co-evolution/Pearson correlation coefficient/optimal threshold method/competitive and collaborative relationships分类
动力与电气工程引用本文复制引用
张帅,裴玮,蒲天骄,马腾飞,肖浩,王晓辉..P2P交易随机博弈决策与复杂网络协同演化分析[J].中国电机工程学报,2025,45(z1):31-45,15.基金项目
国家自然科学基金项目(U2066211,52177124,52107134). Project Supported by National Natural Science Foundation of China(U2066211,52177124,52107134). （U2066211,52177124,52107134）
