A team of researchers from the University of Central Florida, including Hamid Najafzad, Moddassir Khan Nayeem, Fuhad Ahmed Opu, Omar Abbaas, and Gabriel Nicolosi, have developed a new approach to optimize the deployment of electric vehicle (EV) charging stations. Their work, published in the journal Transportation Research Part E: Logistics and Transportation Review, aims to address one of the key barriers to widespread EV adoption: the lack of reliable and equitable charging infrastructure.
The researchers propose a two-stage stochastic optimization model to determine the optimal placement of both fixed and mobile charging stations. The model first identifies potential locations for fixed charging stations (FCSs) based on long-term traffic patterns, budget constraints, and socioeconomic factors. This ensures a stable baseline coverage that considers the needs of all communities, including underserved areas. The second stage dynamically assigns mobile charging stations (MCSs) in response to short-term demand fluctuations and uncertainties. The goal is to minimize relocation costs while maximizing coverage, using a scenario-based framework to capture demand variability.
To identify candidate locations for FCSs, the researchers modified an existing algorithm called the Edge Scanning Algorithm for a Single Refueling Station (ESS). This algorithm helps avoid redundant coverage by incorporating existing public charging stations into the planning process. The model’s effectiveness was demonstrated through numerical experiments on realistic networks, showing enhanced system resilience and reduced unmet demand.
The practical applications of this research are significant for the energy sector. By optimizing the deployment of charging stations, the model can help ensure that EV infrastructure is both reliable and equitable. This can accelerate EV adoption by addressing coverage gaps and providing a more responsive charging network. Planners and policymakers can use these insights to develop strategies that make EV charging more accessible and demand-responsive, ultimately supporting the transition to a more sustainable transportation system.
Source: Najafzad, H., Nayeem, M.K., Opu, F.A., Abbaas, O., & Nicolosi, G. (2023). A Two-Stage Stochastic Optimization Model for the Equitable Deployment of Fixed and Mobile Electric Vehicle Charging Stations. Transportation Research Part E: Logistics and Transportation Review.
This article is based on research available at arXiv.