Coordinated charging of electric vehicle fleets

Transport electrification is driving rapid growth in charging demand on distribution grids designed long before the mass arrival of electric vehicles. Uncoordinated charging, concentrated at the end of the day, coincides with the residential peak and can cause transformer overloads, voltage drops and costly reinforcement — a risk heightened in Quebec by the winter peak.

This doctoral project develops a charging coordination strategy that exploits the temporal flexibility of EVs to reduce grid impact while respecting users' mobility needs: modeling charging demand and its uncertainty from real data, then applying optimization methods able to handle uncertainty in charging behaviour and grid conditions.

Main objective

Develop and validate an EV charging optimization method that minimizes distribution-grid impact while guaranteeing users' mobility needs, under uncertainty.

Methodology

Five stages: collection and characterization of charging profiles; multi-period stochastic optimization formulation; a decomposed, privacy-preserving solution method; a transactive mechanism encouraging vehicles to provide flexibility; validation via Monte-Carlo simulations (peak reduction, transformer life, cost, satisfaction).