Analyses and Applications of Plug-in Electric Vehicle Charging Stations' User Behavior in a Large University Campus Community

Abstract

Efficient utilization and fast deployment of Plug-in Electric Vehicle (PEV) Charging Stations (CS) are required to accommodate the rapid growth of PEV adoption. This paper investigates the behavioral pattern of public PEV charging stations situated in a university campus community. A year-long data of 16 PEV charging stations are analyzed to find out the correlation between station occupancy, energy usage, and charging activities. The analyses are followed by a generalized probabilistic load model to estimate the hourly aggregated PEV power consumption on a given day. The expected load estimation is validated and compared with an existing public charging network of another university campus. Case studies are done to show the power consumption for different PEV penetration scenarios and the charging impacts on the duck curve. Cost analysis is also provided to estimate the revenues for CS owners. Charging rates based on the duration of hours exhibit to be more beneficial for EV station owners compared to energy based rates. The in-depth load demand and charging cost analysis will assist the policy makers in planning future CS integration.