  The rise of renewables coincides with the shift towards Electrical Vehicles
(EVs) posing technical and operational challenges for the energy balance of the
local grid. Nowadays, the energy grid cannot deal with a spike in EVs usage
leading to a need for more coordinated and grid aware EVs charging and
discharging strategies. However, coordinating power flow from multiple EVs into
the grid requires sophisticated algorithms and load-balancing strategies as the
complexity increases with more control variables and EVs, necessitating large
optimization and decision search spaces. In this paper, we propose an EVs fleet
coordination model for the day ahead aiming to ensure a reliable energy supply
and maintain a stable local grid, by utilizing EVs to store surplus energy and
discharge it during periods of energy deficit. The optimization problem is
addressed using Harris Hawks Optimization (HHO) considering criteria related to
energy grid balancing, time usage preference, and the location of EV drivers.
The EVs schedules, associated with the position of individuals from the
population, are adjusted through exploration and exploitation operations, and
their technical and operational feasibility is ensured, while the rabbit
individual is updated with a non-dominated EV schedule selected per iteration
using a roulette wheel algorithm. The solution is evaluated within the
framework of an e-mobility service in Terni city. The results indicate that
coordinated charging and discharging of EVs not only meet balancing service
requirements but also align with user preferences with minimal deviations.
