Performance evaluation and cost optimization for electric vehicle charging stations

Electric vehicles (EVs) are experiencing widespread adoption driven by environmental concerns and the diminishing fossil fuel availability. However, range anxiety remains a major barrier to further EV adoption. The rising demand for charging stations has led to extensive research on the development of charging infrastructure. This study investigates the design and management of an EV charging station by modeling a finite-capacity queueing system with unreliable servers and impatient customers. “Finite capacity” represents limited parking spaces, while “unreliable servers” accounts for the possibility of charger breakdowns and the need for repairs. Furthermore, “impatient customers” reflects the tendency of EV owners to abandon their wait if delays become excessive. To assess the transient performance of the queueing system, the fourth-order Runge–Kutta method is utilized, and steady-state results are analyzed using the matrix-geometric method. Based on the performance analysis, the expected total cost function is constructed, and a numerical optimization problem is formulated to minimize expected total cost. This study provides a framework for evaluating both transient and steady-state performance of EV charging stations, offering practical insights for designers and managers. Finally, the empirical analysis further enhances the model’s robustness by validating its assumptions and providing real-world data to refine its predictions.