Enhancing Adequacy of Isolated Systems with Electric Vehicle-Based Emergency Strategy

Ning Zhou Xu, Ka Wing Chan, Chi Yung Chung, Ming Niu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

Abstract

Extreme events can extensively damage power systems, causing customers to experience long-lasting outages. During such events, an electric vehicle (EV) can be used to directly power a house, i.e., vehicle-to-home (V2H). Specifically, the EV serves as a mobile energy storage system - running errands to 'transport' energy from other places. Vehicle-to-grid (V2G) further allows cooperation among houses. It enables EV fleets to take turns running the errands so that sustained power supply is possible. Moreover, autonomous driving technology can also benefit system adequacy because the charging errands of EVs can be scheduled flexibly without being bonded to human activities. An emergency power supply strategy featuring scheduled EV charging errands as introduced above is proposed. It answers the questions whether and to what extent a system can survive an extended period of outage with the use of EVs only. An optimization problem is formulated with the purpose of maximizing the supply adequacy of the isolated system during the outage period. Both V2H and V2G scenarios are considered in the problem formulation, as well as self-driving capability. The complex optimization problems are solved with genetic algorithm. It is significant to find from the case study that the proposed strategy is able to fully restoring an islanded system when V2G and self-driving EVs are implemented.

Original languageEnglish
Article number8798760
Pages (from-to)3469-3475
Number of pages7
JournalIEEE Transactions on Intelligent Transportation Systems
Volume21
Issue number8
DOIs
Publication statusPublished - Aug 2020

Keywords

  • Adequacy assessment
  • autonomous driving
  • electric vehicle (EV)
  • isolated system
  • vehicle-to-grid (V2G)
  • vehicle-to-home (V2H)

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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