Queue Modelling for EV Charging Station Design: Minimizing Rejection Rates and Maximizing Efficiency

In recent times, the Passenger Vehicle market has been rapidly evolcing. Conventional Internal Combustion Vehicles (ICVs) are rapidly being replaced by Electric Vehicles (EVs). The widespread adoption of Electric Vehicles (EVs) requires the establishment of a comprehensive charging infrastructure to adequately handle the current and anticipated demand. This research paper addresses this critical need by proposing a Python implementation of queuing models to optimize the minimum required EV charging infrastructure. The queuing models are used to analyze charging station performance. These models consider variables like arrival rates, service times, and station capacity to evaluate key performance indicators (KPIs) such as average waiting time, charger utilization, queue length, and blocking probability of the system. This Python-based tool allows customizable simulations, enabling researchers and decision-makers to optimize the operations and facilitate further development of EV charging infrastructure.