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.
|Name||2017 Asian Control Conference, ASCC 2017|
|Conference||2017 11th Asian Control Conference, ASCC 2017|
|Period||17/12/17 → 20/12/17|