TY - GEN
T1 - A scheduling and control system for electric vehicle charging at parking lot
AU - Wu, Hao
AU - Pang, Grantham Kwok Hung
AU - Choy, King Lun Tommy
AU - Lam, Hoi Yan
PY - 2018/2/7
Y1 - 2018/2/7
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85047555290&partnerID=8YFLogxK
U2 - 10.1109/ASCC.2017.8287095
DO - 10.1109/ASCC.2017.8287095
M3 - Conference article published in proceeding or book
VL - 2018-January
T3 - 2017 Asian Control Conference, ASCC 2017
SP - 13
EP - 18
BT - 2017 Asian Control Conference, ASCC 2017
PB - IEEE
T2 - 2017 11th Asian Control Conference, ASCC 2017
Y2 - 17 December 2017 through 20 December 2017
ER -