Canada's transportation sector is rapidly transitioning to electrification, raising concerns about the strain on electricity grids during peak electric vehicle (EV) charging times. This increase in electricity demand has raised concerns about heightened peak demand, fluctuations in wattage and frequencies, increased transmission loss, compromised grid reliability, and the risk of power line overloads. Mitigating these concerns can be accomplished through demand management programs. As an initial exploration into understanding charging demand patterns this research aims to study the demand behavior patterns at electrical charging stations within the City of Ottawa. The research develops a multiple variable regression model using publicly available data from the City of Ottawa to model the gap times between charging events. The regression model aims to identify temporal/seasonality variations in EV charging behavior and the significance of the presence of rapid transit, and arterial roads. The regression model will also utilize data from the 2020 census to study the impact of site-specific dissemination area characteristics such as median income, median household sizes, and average travel times. The findings provide foundational knowledge to develop more resilient and efficient integration of EV charging infrastructure into urban grids.
