Distributed Noncooperative MPC for Energy Scheduling of Charging and Trading Electric Vehicles in Energy Communities

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