EURO 2024 Copenhagen
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1804. Strategic Locations of EV Charging Stations: Catering to Various Charging Types and Diverse Driver Profiles

Invited abstract in session MB-61: Location of Alternative Fuel and Charging Stations, stream Locational Analysis.

Monday, 10:30-12:00
Room: S10 (building: 101)

Authors (first author is the speaker)

1. Jingyu Xiang
Smurfit Business School, University College Dublin
2. Paula Carroll
Management Information Systems, UCD
3. Annunziata Esposito Amideo
Quinn School of Business, University College Dublin

Abstract

As a promising sustainable transportation solution, Electric Vehicles (EVs) require efficient strategies for their refueling to complete their journey. This study aims to address the charging station location problem (CSLP), considering multiple charging options and varied driver behaviours. We first integrate the Multi-Path Refueling Location Model (MPRLM) with various charging types, including slow, fast, and battery-swapping charging stations. This model considers different charging rates of multiple charging stations, assuming a linear recharging rate over time. To balance the investment cost of charging stations and the service level for EV users, our objective involves minimizing the total cost for operators and the overall charging time for EV users. Experimental tests on a 25-node network indicate the extended MPRLM outperforms the original model by better balancing system costs, charging time, and station utilization. Then, the Integrated Behavioral Multipath Refueling Location Model (IB-MPRLM) is introduced to incorporate varied charging profiles of EV users. We categorize private EV drivers based on their sensitivity levels to range anxiety, charging costs, and charging time. For each EV driver category, the satisfaction function and satisfaction threshold are established. In this IB-MPRLM, the charging station located at a certain node can only refuel an EV when the user's satisfaction is higher than the threshold of the EV user.

Keywords

Status: accepted

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