Reducing Electricity Grid Congestion by Scheduling Electric Vehicle Charging in Medium- and Low-Voltage Grids.

Abstract

Electricity grid congestion occurs at both the low- and medium-voltage levels, driven partly by the increasing adoption of electric vehicles (EVs). Upgrading low- and medium-voltage grid infrastructure is expected to take several years. As an interim solution, this work presents an algorithmic approach to alleviate grid congestion through optimizing the charging schedules of EVs. A linear programming model is developed to schedule vehicle charging across multiple connected low- and medium-voltage grids, encompassing residential neighborhoods and electric bus charging depots. The approach aims to satisfy all vehicle charging demands while avoiding overloading grid components. Compared to a conventional greedy approach, the proposed linear programming method results in lower grid congestion. Furthermore, inter-grid scheduling which spans both the low- and medium-voltage levels is likely more effective in reducing grid congestion compared to intra-grid limited scheduling. These findings suggest that linear programming is a promising technique for mitigating grid congestion by scheduling EV charging across multi voltage level grid networks.