A Schedule-Control Aided Strategy for Charging Large Number of EVs under Normal and Line Failure Scenarios

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

4 Scopus Citations
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Detail(s)

Original languageEnglish
Article number7944561
Pages (from-to)10846-10857
Journal / PublicationIEEE Access
Volume5
Online published8 Jun 2017
Publication statusOnline published - 8 Jun 2017

Abstract

Electric vehicle (EV) becomes a popular choice for its zero air pollutant and high energy efficiency. Nevertheless, the massive penetration of EVs can cause problems, including voltage drop and peak amplification. The charging pattern of EVs also poses a challenge to the reconfiguration work of the power system when failure occurs. Therefore, an EV schedule-control-based strategy is designed to address these issues in order to achieve voltage regulation and load shifting under both normal operation and failure scenarios. The framework involves two agents: 1) a two-stage voltage control agent schedules EVs to perform load shifting and voltage regulation under normal condition and 2) a fault control agent deals with line failure scenarios to recover the power supply of out-of-service basic and EV loads. A three-level queue table mechanism is designed to collaboratively perform EV scheduling. The influence of EV charging locations on the voltage variations of other nodes is considered and alleviated through a voltage sensitivity analysis method. Moreover, graph theory is employed to perform the network reconfiguration process to deal with line failure situations. The effectiveness of the scheme to restore the power supply while maintaining reliable system voltage level has been verified with the simulation results based on a modified IEEE 30 nodes test feeder.

Research Area(s)

  • Charging, distribution network, electric vehicle, line failure, load shifting, voltage control

Citation Format(s)

A Schedule-Control Aided Strategy for Charging Large Number of EVs under Normal and Line Failure Scenarios. / MAO, TIAN; LAU, WING-HONG; SHUM, CHONG; CHUNG, HENRY SHU-HUNG; TSANG, KIM-FUNG; TSE, NORMAN CHUNG-FAI.

In: IEEE Access, Vol. 5, 7944561, 08.06.2017, p. 10846-10857.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal