Queueing Network Analysis for Electric Vehicle Management Systems using G-Queues

This study introduces an advanced queueing model for electric vehicle (EV) charging stations that incorporates negative and positive arrivals, representing various system disruptions and service interruptions. The research addresses the growing complexity of EV charging infrastructure by developing a comprehensive mathematical framework using G-queue networks and modified Chapman-Kolmogorov differential-difference equations. We analyze system performance through multiple system performance metrics, including expected waiting times, queue lengths, and server utilization patterns under the influence of negative arrivals. The model incorporates key operational parameters such as positive and negative arrival rates, service completion rates, and the probability of negative customer impacts on the system state. Through numerical analysis, we demonstrate the significant impact of these parameters on system stability and resource utilization. Results reveal that managing the balance between regular service provision and handling negative customer disruptions can substantially improve overall system reliability. The findings provide valuable insights for EV charging station operators, enabling them to implement robust operational strategies that account for various forms of service interruptions and system perturbations.