Saudi Cultural Missions Theses & Dissertations
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Item Restricted DATA-DRIVEN EV CHARGING INFRASTRUCTURE PLANNING: ADAPTIVE SIMULATION AND STRATEGIC DEPLOYMENT IN VIRGINIA(Geroge Mason University, 2024-04-29) Zaylaee, Mohammed; Ji, WenyingAbstract The rapid adoption of electric vehicles (EVs) necessitates innovative approaches to manage and optimize the deployment of EV charging infrastructure. This scholarly paper integrates two complementary studies focusing on the dynamic modeling of EV charging behaviors and the strategic evaluation of charging station coverage in Virginia. The first part of the thesis employs advanced spatial analysis techniques to assess the current network of public EV charging stations in Virginia. Using a comprehensive dataset from Virginia Clean Cities, this analysis identifies regions with insufficient charging facilities, particularly in areas exhibiting high growth potential in the EV market. Techniques such as buffer and coverage analysis are utilized to map and visualize the distribution and capacity of existing infrastructure, thereby pinpointing areas where expansion is most needed. This spatial investigation highlights underserved areas by comparing infrastructure against critical benchmarks, facilitating targeted policy actions to bridge infrastructure gaps. The second part introduces a novel adaptive simulation framework that enhances traditional models by incorporating Bayesian inference with (MCMC). Together, these studies provide a comprehensive approach to understanding and improving the EV charging infrastructure. By combining detailed spatial analysis with adaptive simulation techniques, this scholarly paper offers actionable insights that can drive the sustainable growth of the EV market through more informed decision-making and strategic deployment of resources.188 0