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 - Publication in refereed journal › peer-review
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Detail(s)
Original language | English |
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Article number | 7944561 |
Pages (from-to) | 10846-10857 |
Journal / Publication | IEEE Access |
Volume | 5 |
Online published | 8 Jun 2017 |
Publication status | Published - 2017 |
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DOI | DOI |
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Attachment(s) | Documents
Publisher's Copyright Statement
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Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-85028383491&origin=recordpage |
Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(734ed314-18d5-41e2-b237-61a7d22c9290).html |
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 et al.
In: IEEE Access, Vol. 5, 7944561, 2017, p. 10846-10857.
In: IEEE Access, Vol. 5, 7944561, 2017, p. 10846-10857.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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