A stochastic receding horizon approach to manage an EV charging
station participating in DR programs for RECs has been proposed.Additional developments may regard the adaptation of the procedure to
dynamic traffic conditions, the integration of renewable resources, and
the experimental validation of the approach in real-world RECsThe
developed procedure implements a stochastic approach that is (i) able
to exploit online information to schedule the EV charging such that the
aggregated power consumption lies within prescribed energy bounds
during DR windows, and is (ii) computationally feasible to be deployed
in real-world applications.Moreover, the computation time
remains feasible even for scenarios involving a high EV penetration.