Optimal sizing of PEV fast charging stations with Markovian demand characterization

Fast charging stations are critical infrastructures to enable high penetration of plug-in electric vehicles (PEVs) into future distribution networks. They need to be carefully planned to ensure meeting charging demand as well as economic benefits. Accurate estimation of PEV charging demand is the prerequisite of such planning, but a non-trivial task. This paper addresses the sizing (number of chargers and waiting spaces) problem of fast charging stations and presents an optimal planning solution based on an explicit temporal-SoC characterization of PEV fast charging demand. The characteristics of PEV charging demand are derived through the vehicle travel behavior analysis using available statistics. The PEV dynamics in charging stations is modelled with a Markov chain and queuing theory. As a result, the optimal number of chargers and waiting spaces in fast charging stations can be jointly determined so as to maximize the expected operator profits, considering profit of charging service, penalty of waiting and rejection, as well as maintenance cost of idle facilities. The proposed solution is validated through a case study with mathematical justifications and numerical results from simulation.