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2428. A Matheuristic for the Optimal Placement of EV Charging Stations in an Urban Environment

Invited abstract in session TC-26: Sustainability in Distribution and Transportation, stream Combinatorial Optimization.

Tuesday, 12:30-14:00
Room: 012 (building: 208)

Authors (first author is the speaker)

1. Bryan Coulier
Computer Science, KU Leuven
2. Hatice Calik
Department of Electrical Engineering, KU Leuven
3. Thijs Becker
VITO
4. Greet Vanden Berghe
Computer Science, KU Leuven

Abstract

In response to global environmental concerns and policy initiatives, the automotive industry is currently undergoing a significant transformation towards sustainable transportation. As EVs become a major component of the transition to a greener, more electrified future, governments are investing heavily in charging infrastructure. The rapid rise of EV adoption poses significant challenges to conventional power grids. Intelligent solutions are necessary in order to ensure reliable and efficient charging infrastructure.

Current studies concerning EV charging infrastructure often overlook the underlying power distribution network and the accessibility of charging stations for EV users. The majority of these studies are small in scale, employing metaheuristics without validating their results using exact solutions. Moreover, researchers have predominantly focused on fast chargers, while slow chargers play an equally crucial role in urban settings.

In an effort to address these significant gaps, our research focuses on the placement of slow charging stations in urban areas while taking into account (i) the distribution network, (ii) customer demand, and (iii) accessibility. We propose a novel Mixed-Integer Linear Programming (MILP) model to determine the optimal placement, quantity, and type of charging stations. To enhance scalability and computational speed, we also introduce a multi-stage matheuristic for solving large-scale instances by decomposing the grid network.

Keywords

Status: accepted

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