Integrated Planning of Residential and Commercial Electric Vehicle Charging Infrastructure: A Strategic Bi-Level Optimization and Queuing Framework Approach

Abstract

Electric vehicles (EVs) have gained significant popularity, becoming an attractive option for cleaner transportation systems. The market adoption of different types of EVs in the USA has grown significantly over the years. A critical challenge for this expanding market is the limited charging infrastructure available in both residential and commercial spaces. This research aims to study the optimal number, placement, and management of charging stations required to accommodate EVs at both residential and commercial locations, considering varying market penetration rates, household adoption of charging infrastructure, and the constraints posed by power network capacities.The developed model is applied to the Baltimore Metropolitan Statistical Area (MSA) to determine the optimal number and distribution of charging stations. This study integrates real-world Origin-Destination (OD) trip data with census data to investigate the relationship between residential and commercial EV charging infrastructures. Furthermore, advanced queuing theory models are employed to analyze and manage congestion at commercial charging stations, evaluating system performance indicators such as waiting times, blocking probabilities, and station utilization under realistic, stochastic demand conditions. Scenario analysis illustrates the shifting landscape of charging infrastructure demands for both current (0.09%, 0.75%, and 1.61%) and future market penetration rates (5%, 7.5%, and 10%), reflecting Maryland's current adoption levels and future growth projections driven by policy initiatives and technological advancements in EV infrastructure. The findings reveal a clear inverse relationship between the availability of residential charging facilities and the necessity for commercial chargers. Utilizing a bi-level optimization model, this research balances investor interests with EV user satisfaction by maximizing profits and minimizing user charging costs. Additionally, the queuing simulation highlights critical operational insights, illustrating how variations in arrival rates, service times, and charger availability impact overall system efficiency and user experience. These combined insights emphasize the importance of integrating residential and commercial charging infrastructure planning with congestion management strategies. Policymakers, utility providers, and infrastructure investors can utilize these findings to formulate sustainable EV charging strategies, considering market penetration rates, household charger adoption, optimal State of Charge (SoC) management, and operational efficiency through queuing management. This comprehensive framework provides robust guidance for stakeholders aiming to develop resilient, sustainable, and efficient EV charging networks, promoting greater EV adoption and contributing to environmental sustainability.