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

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

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)

Abstract

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.
Original languageEnglish
Title of host publication2017 Asian Control Conference, ASCC 2017
PublisherIEEE
Pages13-18
Number of pages6
Volume2018-January
ISBN (Electronic)9781509015733
DOIs
Publication statusPublished - 7 Feb 2018
Event2017 11th Asian Control Conference, ASCC 2017 - Gold Coast Convention and Exhibition Centre, Gold Coast, Australia
Duration: 17 Dec 201720 Dec 2017

Publication series

Name2017 Asian Control Conference, ASCC 2017
Volume2018-January

Conference

Conference2017 11th Asian Control Conference, ASCC 2017
Country/TerritoryAustralia
CityGold Coast
Period17/12/1720/12/17

ASJC Scopus subject areas

  • Control and Optimization

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