Balancing Charging Station Utilization and Throughput in Electric Vehicle Charging Stations with Queuing Theory

Conference · Fri Nov 01 00:00:00 EDT 2024

DOI:https://doi.org/10.1109/IECON55916.2024.10905639· OSTI ID:2538272

Kumar, Praveen ^[1]; Ozpineci, Burak ^[1]; Ribeiro, Pedro ^[1]; Galigekere, Veda Prakash ^[1]

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1. ORNL

The rapid increase in electric vehicle (EV) adoption demands enhancements in the efficiency and adaptability of EV supply equipment (EVSE). Traditional EVSE systems often fail to optimize power delivery to meet the variable acceptance rates of EV batteries, resulting in significant energy wastage and reduced operational efficiency. This research addresses these challenges by integrating queuing theory with modular EVSE architectures, offering a dual strategy to optimize the operation of EV charging stations. A simulation model was developed to assess various configurations of charger capacities and outlet numbers. This model aimed to identify the optimal setup that maximizes station utilization while minimizing charging times and maximizing throughput. The model focused on charger capacities ranging from 50 to 250 kW and analyzed the different capacities’ effects on charging times and the number of vehicles served. The results indicate that a charger capacity of 125 kW is optimal, striking a balance between the charging time and the number of EVs served per hour, thus achieving the highest station utilization rate. This capacity allows for servicing a significant number of EVs with moderate increases in charging times. Lower capacities, although capable of serving more vehicles, lead to longer charging times and decreased throughput efficiency. The study underscores the effectiveness of combining queuing theory with flexible, modular charging systems that can dynamically adjust to EV charging demands.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE); USDOE
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 2538272
• Resource Type: Conference paper/presentation
• Conference Information: 50th Annual Conference of the IEEE Industrial Electronics Society (IECON 2024) - Chicago, Illinois, United States of America - 11/3/2024-11/6/2024
• Country of Publication: United States
• Language: English