An empirically-validated methodology to simulate electricity demand for electric vehicle charging

With recent changes in the availability and diversity of plug-in electric vehicles (PEVs) in the United States, there is increasing research interest in the interaction between PEVs and the electric grid. Extensive work in the literature examines these interactions with the assumption that the timing of PEV charging will be scheduled, and that charging loads can be adjusted dynamically at the behest of the utility and the system operator. While it might be technically feasible to aggregate the data on driver schedules and historical PEV use and charging decisions, it is unclear whether PEV owners will readily share these data and accept partial third-party control of their vehicle’s charging. Given the uncertainty in the future relationships between electric utilities and PEV owners, this study examines the region-level effects of PEV charging in the absence of the additional data utilities would need to realize these idealized charging scenarios. In particular, this study focuses on temporally-resolved prediction of electricity demand needed to serve PEV charging loads if charge scheduling or control is not widespread.