Mobility-Aware Electric Vehicle Fast Charging Load Models With Geographical Price Variations

We study the traffic patterns as well charging of a population cost-minimizing EV owners traveling and within transportation network equipped with fast stations (FCSs). Specifically, we how operator (CNO) can influence where users charge in order to optimize utilization FCSs. These decisions private affect aggregate congestion at (i.e., waiting time) load across network. In this work, capture resulting equilibrium wait times electricity through so-called assignment problem (TCAP) an FCS Our formulation allows us to: 1) expected station probability distribution EVs mobility-aware fashion (an aspect unique our work) while accounting for heterogeneities users' travel patterns, energy demands, geographically variant prices; 2) analytically characterize special threshold-based structure that determines choose their vehicle equilibrium, response FCS's price structure, mobility patterns; 3) provide convex optimization identify network's equilibrium. Furthermore, illustrate induce socially optimal behavior by deriving plug-in fees prices stations.