Electronic Thesis/Dissertation
 

Electric Vehicle Charge Station Expansion Analysis for EV Owners in Maryland

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Stochastic Model utilizing Monte Carlo Simulation Methodology to Determine Arrival Rates, Utilization and Wait Times of Electric Vehicles at Charge Station InfrastructureIn recent years, the rapid growth of Electric Vehicle sales has heightened demand for public Charge Station infrastructure, particularly in urban areas. The pace of Charge Station infrastructure development often fails to match the local and passing EV traffic demand, creating frustration from queuing EV drivers. This praxis conducts a comprehensive examination of the Electric Vehicle charging station queuing problem in the urban area of Bethesda, Maryland. Employing a quantitative methodology, we develop and assesses predictive Monte Carlo simulation models using distribution functions to represent key aspects of EV charging processes, such as state of charge, station utilization, and waiting times. This approach yields favorably validated results demonstrating simulated Charge Station utilization reflects empirical data from Charge Station operators. Notably the findings reveal supply and demand of Charge Station resources are misaligned with EV charging growth demands and needs during periods of extended extreme air temperature. This research provides valuable insights into the operation of EV charging stations and how they are influenced by factors to include weather and rapid EV registration growth. Recommendations are offered for further elaboration of the approach for the engineering manager to gain a broader understanding across urban and intra-urban EV user communities.

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