I. Introduction
PEVs provide a compelling opportunity for supplying demand-side management services in the smart grid. Namely, a vehicle-to-grid (V2G) capable PEV communicates with the grid, stores energy, and can return energy to the electric grid. If properly managed, PEVs can enhance energy infrastructure resilience, enable renewable integration, and reduce economic costs for consumers and energy providers [1]. In addition to these societal-level infrastructure and environmental benefits, V2G strategies may provide additional revenue streams to PEV owners [2]. Underscoring this opportunity, U.S. personal vehicles are parked and un-used 96% of time [3]. A single PEV typically charges or discharges at 5-20 kW, which is insufficient to participate in power grid markets. However, populations of PEVs can be aggregated to collectively provide grid services [4]. The main challenge, however, is monitoring and managing a large population of distributed PEV resources without sacrificing their primary function of personal mobility. As such, this paper examines modeling and control of grid integrated PEV populations.