A scheduling and control system for electric vehicle charging at parking lot

This paper proposes a new electric vehicle (EV) charging scheduling and control system for a parking lot (PL), which would minimize the PL's electricity cost of recharging all the EVs. This system is to determine an optimal charging schedule for each incoming EV by allocating the electric quantities to the parking time slots of each EV considering the varied electricity price during the day. The schedule would satisfy the EV's charging rate limit and the PL's transformer limit. This paper proposes a heuristics & proportion-based assignment (HPBA) method to generate the initial population, and adapts the particle swarm optimization (PSO) algorithm to solve the optimization problem. The performance of the proposed system is compared with random search (RS), first-in-first-serve (FIFS) and earliest-deadline-first (EDF) mechanisms, and the results show that the new scheduling system would achieve the goal on minimizing the electricity cost and satisfying the charging demands and constraints.

I. Introduction

The rapid growth of electric vehicle (EV) population in the past decade [1] has attract attention from the electric power sectors and transportation departments because of the limited public EV parking lots (PLs) and the high electric requirement of charging infrastructure. The main limitations of EV parking lot scheduling include long charging time, uncertain parking periods, varied charging demands and limit of transformer limit. Currently, most of the parking lots deal with the EVs' charging requests using the first come-first-serve (FIFS) or earliest-deadline-first (EDF) charging strategies.