Modelling the Transient Evolution of Queues in Plugged-in Electric Vehicles(PEV) Fast Charging Stations

TytułModelling the Transient Evolution of Queues in Plugged-in Electric Vehicles(PEV) Fast Charging Stations
Publication TypeConference Paper
Rok publikacjiIn Press
AutorzyKuaban GSuila, Nycz T, Nycz M, Czachórski T, Czekalski P
Conference Name25th International Conference on Computational Science
PublisherSpringer, Cham
Conference LocationSingapore
Abstract

The transportation sector is responsible for approximately 23% of global greenhouse gas (GHG) emissions, with road transportation contributing nearly 70% of these emissions. The widespread adoption of electric vehicles (EVs) is transforming this sector by reducing emissions and decreasing reliance on fossil fuels. However, the growing number of EVs presents significant challenges for charging infrastructure, particularly in managing long queues, extended wait times, and limited station capacity. Most existing studies on the performance of electric vehicle charging stations assume Poisson arrivals and exponential charging times, simplifications that often overlook real-world variability. This paper introduces a generalized queueing model that leverages empirical interarrival and charging duration data for more accurate performance evaluation. A transient analysis is conducted, examining two operational optimization strategies aimed at minimizing queue sizes during peak demand: (1) a queue management policy that encourages charging only up to a predefined state-of-charge (SoC) threshold instead of the typical 80–100%, and (2) dynamic control of the number of active charging ports based on demand. The results show that these operational optimization policies improve the efficiency of the charging station and significantly improve the customer experience.

Historia zmian

Data aktualizacji: 08/05/2025 - 02:37; autor zmian: Godlove Kuaban (gskuaban@iitis.pl)