Dynamic resource allocation for parking lot electric vehicle recharging using heuristic fuzzy particle swarm optimization algorithm

Hao Wu, Grantham Kwok Hung Pang, King Lun Choy, Hoi Yan Lam

Research output: Journal article publicationJournal articleAcademic researchpeer-review

22 Citations (Scopus)


A parking lot (PL) dynamic resource allocation system for recharging electric vehicles (EVs) is introduced in this paper. For scheduling purposes, a day is divided into sequential timeslots. At the beginning of each timeslot, the dynamic system can determine an optimal charging schedule for that timeslot, as well as plan for subsequent timeslots. An EV may arrive at a PL with or without an appointment. Considering the variation in electricity prices during the day, the objective is to minimize the cost of electricity used to charge EVs by scheduling optimal electric quantities at the parking timeslots of each EV. The optimal solution satisfies the EV's charging rate limit and the PL's transformer limit. Based on particle swarm optimization (PSO), fuzzy systems and heuristics, this paper describes a heuristic fuzzy particle swarm optimization (PHFPSO) algorithm to solve the optimization problem. From the case studies, the results show the proposed dynamic resource allocation system has a significant improvement in satisfying charging requests and in reducing the electricity cost of the PL when compared with other scheduling mechanisms.

Original languageEnglish
Pages (from-to)538-552
Number of pages15
JournalApplied Soft Computing Journal
Publication statusPublished - Oct 2018


  • Dynamic resource allocation
  • Electric vehicle
  • Fuzzy system
  • Heuristics
  • Parking lot
  • Particle swarm optimization

ASJC Scopus subject areas

  • Software

Cite this