Abstract:
In this thesis work a control problem is formulated to handle the charging
of Electric Vehicles (EVs) in a power distribution system which is prone to
network overloading. Such overloading results due to the lack of capacity of
the distribution system to deliver power to its consumers, and it is prevalent
in the developing countries, where the addition of EVs load is expected to
further aggravate it. Furthermore, the addition of EVs in a distribution
network introduces multiple uncertainties, e.g. uncertainties in the arrival
times of the EVs to Charging Stations (CSs), their initial battery State Of
Charges (SOCs) and their charging time requirements, which adds to the
load fluctuation and results in the instability of the grid. To address these
issues, we formulate the problem of charging EVs in a stochastic framework
where a Stochastic Model Predictive Control (S-MPC) based approach is
proposed. The approach is designed to simultaneously achieve the desired
SOCs of the batteries of the EVs, standing at the CSs, and minimize network
overloading and load fluctuation in the grid. The simulated results show that
the approach successfully achieves the desired objectives in the presence of
the said uncertainties.
