  This paper offers a strategic approach to Electric Vehicles (EVs) charging
network planning, emphasizing the integration of demand and supply dynamics via
continuous-time fluid queue models and discrete flow refueling location
modeling, all in the context of innovation diffusion principles. We employ a
continuous-time approximation based on Ordinary Differential Equations (ODEs)
to design multi-year supply curves, a method that stands in contrast to
conventional practices which often overlook inter-year transitions and ongoing
processes. For medium-term charging station location planning (CSLP), we apply
a flow refueling location model (FRLM) within grid-based multi-level networks,
considering both multiple-path networks and capacity constraints. The
grid-based network planning strategy uses a three-tier (Macro-Meso-Micro)
approach for thorough EV charging station placement, with the macro-level
covering entire cities, the meso-level assessing detailed EV routes and
bridging the macro to micro levels, and the micro-level focusing on precise
station placement for accessibility and efficiency. Our investigation into
overutilization and underutilization scenarios delivers valuable insights for
policymaking and cost-benefit analyses. Illustrating our approach with the
example of the Chicago sketch network, we introduce an integrated demand-supply
model suitable for a single region and extendable to multiple regions, thereby
addressing a gap in the existing literature. Our proposed methodology focuses
on EV station placement, taking into account future needs, geographical
capacities, and the importance of scenario analysis, which empowers strategic
resource planning for EV charging networks over extended timeframes, thus
aiding the transition towards a more sustainable and efficient transportation
system.
