Inducing Human Behavior to Alleviate Overstay at PEV Charging Station

This paper proposes a mathematical framework to optimally operate a plug-in electric vehicle (PEV) charging station, using differentiated charging services. The mathematical framework specifically exploits human behavioral modeling to alleviate "overstay" - when a PEV remains plugged-in after charging service is complete. Discrete Choice Modeling is utilized to capture human decision-making behavior among multiple charging service options that differ in both price and quality-of-service. We reformulate an associated non-convex problem to a multi-convex problem via the Young-Fenchel transform. We then apply Block Coordinate Descent algorithm to efficiently solve the multi-convex problem. Simulation results show a strong potential of the proposed method in realizing benefits in three ways: (i) net profits gains, (ii) overstay reduction, and (iii) increased quality-of-service.