The adoption of Electric Vehicles (EVs) represents a transformative change in the automotive industry. As more households make the transition to EVs, the traditional dependence on fossil fuels for transportation is being replaced by electricity as the primary energy source. This transition has the potential to increase the electricity consumption within households as well as the demand on the power grids. To maximize the environmental and economic benefits of EV adoption, strategies regarding efficient energy management, integration of renewable energy source, and grid capacity are becoming essential considerations. The current dissertation research is motivated toward evaluating the adoption of EV and its impact on the US household's energy demand. In pursuit of these goals, this research has made several contributions. First, we proposed an econometric framework to estimate the factors influencing customers' vehicle purchase decisions. Second, a comparative analysis is conducted between two econometric frameworks -panel mixed random utility maximization MNL model and panel mixed random regret minimization MNL model to estimate the evolving landscape of EV adoption over time. Third, we employed an advanced econometric framework- Multiple Discrete Continuous Extreme value model- to evaluate the factors that influence the energy consumption profile of various household end-uses along with their alternating trends over time. Finally, by predicting household EV ownership, projections of total household energy demand for the city of Atlanta for the years 2030, 2040 and 2050 are performed. To make the prediction, population synthesis data for the corresponding future years are employed from the Atlanta Regional Commission. A set of independent variables including vehicle attributes, socio-economic attributes, charging infrastructure attributes, dwelling attributes, appliance-use related attributes, and climate-related attributes from various data sources are employed in this study. The research concludes with an analysis of different policy implications.
Naveen Eluru, Committee Chair.
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