A Noncooperative Stochastic Rolling Horizon Control Framework for V1G and V2B Scheduling in Energy Communities

In this paper, we propose a novel control strategy for the optimal scheduling of an energy community constituted by prosumers and equipped with unidirectional vehicle-to-grid (V1G) and vehicle-to-building (V2B) capabilities. In particular, V2B services are provided by long-term parked electric vehicles (EVs) thus acting as temporary storage systems by prosumers, which in turn offer the V1G service to EVs provisionally plugged into charging stations. To tackle the stochastic nature of the framework, we assume that EVs communicate their parking and recharging time distribution to prosumers, allowing them to improve their energy allocation. Prosumers and EVs interact in a rolling horizon control framework with the aim of achieving an agreement on their operating strategies. The resulting control problem is formulated as a generalized Nash equilibrium problem, addressed through the variational inequality theory, and solved in a distributed fashion leveraging on the accelerated distributed augmented Lagrangian method (ADALM). The convergence and effectiveness of the proposed approach are validated through numerical simulations under realistic scenarios.