Alice Callanan, Lund University, is defending her doctoral thesis Quantifying the Grid Impact of Electric Vehicles: A Probabilistic Case Study of Southern Sweden

Date: 13 May, 2026
Time: 09:00
Location: Lecture hall M:B, M-building, LTH campus, Klas Anshelms väg 4, Lund.
Entrance from the parking is Ole Römers väg 1F.
Online via Microsoft Teams
Lund University calendar: https://www.lth.se/english/research/profile-areas/calendar/?evenemang=disputation-quantifying-grid-impact-electric-vehicles

Faculty opponent: Professor Lina Bertling Tjernberg, KTH

Abstract: The electrification of the transportation sector is a central strategy for decarbonization, yet it raises concerns about the capacity of existing electric power grids to meet increasing demand. This thesis investigates the interaction between large-scale electrified vehicle fleets and the electric power system under the assumption of full transport electrification. The focus is on assessing the readiness of the existing sub-transmission grid to accommodate increased power demand, in contrast with previous research that has focused mainly on lower voltage levels. A probabilistic load-flow simulation framework is developed and applied to a full-scale grid model of Skåne in southern Sweden. The framework quantifies the aggregated energy and power requirements of fully electrified fleets of passenger cars, long-haul trucks, and heavy construction equipment. These loads are then integrated into a full-scale grid model covering sub-transmission and transmission levels. The results indicate that the sub-transmission grid is largely capable of accommodating the aggregated charging demand under normal operating conditions, although localized bottlenecks require reinforcement. While smart charging strategies successfully reduce peak power demand from vehicle fleets, the thesis reveals that this benefit does not always translate into a proportional reduction in grid congestion. Importantly, the impact of charging loads is often “dampened” by existing background loads and local grid conditions. This finding challenges the assumption that high charging peaks inevitably lead to grid congestion and underscores the need to couple transport models with realistic grid simulations to assess the impact of new loads on grid capacity accurately.