Online Sharing via Energy-Carbon Storage Equivalence and Potential Evolution of EVs: A Decoupling Approach

The stochastic nature of electric vehicles (EVs) and renewable energy generation necessitates online management of both energy and carbon emissions at the distribution level in line with the low-carbon transition vision. However, existing adjustable potential models fail to account for the anti-herding behavior of EV users, resulting in extreme and unrealistic outcomes. Additionally, the multiple coupled characteristics and behavioral randomness of EVs hinder real-time optimization management. To address these challenges, a unified storage equivalence model is proposed, complemented by an evolutionary game framework on social networks that integrates Anti-Herding Mechanisms (AHM) to realistically quantify the flexibility of charging stations (CSs) while preventing irrational congregation. An offline energy-carbon emission joint sharing model is established within the energy community. To handle the temporal and energy-carbon coupling in EVs, virtual queues based on Lyapunov optimization are introduced, effectively decoupling the multi-timeslot problem into a tractable single-timeslot sharing formulation while ensuring asymptotic optimality. Case studies validate the rationality of the potential evolution results and the effectiveness of the proposed real-time sharing framework. The proposed online sharing method effectively limits peak carbon intensity and reduces costs by 6.50%.