In this project, we explored the complex dynamics between the increasing adoption of electric vehicles (EVs) and the transition towards a cleaner energy grid in the United States. As the demand for EVs continues to rise, it is crucial to understand how this shift impacts electricity consumption and the environmental implications of coupling EVs with cleaner energy sources. Our objective was to create a spatially visualized Alternative Criteria Score (ACS) table, highlighting areas where discrepancies between EV adoption and the cleanliness of the energy grid are most prominent. To achieve this, we collected and processed data from various sources, including census data, EV registration counts, state electricity generation fuel shares, solar energy potential, and federal clean energy infrastructure project funding. We normalized the data to ensure comparability across diverse data points and selected evaluation criteria using linear regressions and Pearson's correlation tests. Each criterion was assigned a weight reflective of its significance, and scores were computed for each state based on the chosen criteria. The resulting ACS table employed a quintile distribution scoring system to categorize and compare states and grids based on their performance in each dimension. This analysis tool facilitated the identification of states with notable discrepancies between EV adoption and energy grid cleanliness, enabling policymakers to strategically direct efforts and allocate resources to regions in need of intervention.
