TY - JOUR
T1 - Enhancing Adequacy of Isolated Systems with Electric Vehicle-Based Emergency Strategy
AU - Xu, Ning Zhou
AU - Chan, Ka Wing
AU - Chung, Chi Yung
AU - Niu, Ming
N1 - Funding Information:
Manuscript received March 13, 2018; revised November 26, 2018 and May 15, 2019; accepted July 12, 2019. Date of publication August 14, 2019; date of current version July 29, 2020. This work was supported in part by Hong Kong Innovation and Technology Fund Internship Program (IP-ITF) under Grant Number InP/035/17, and in part by Experimental Power Grid Centre, Energy Research Institute@NTU, Nanyang Technological University, Singapore. The Associate Editor for this article was E. Kosmatopoulos. (Corresponding author: Ning Zhou Xu.) N. Z. Xu is with the Experimental Power Grid Centre, Energy Research Institute@NTU, Nanyang Technological University, Singapore 627590 (e-mail: [email protected]).
Publisher Copyright:
© 2000-2011 IEEE.
PY - 2020/8
Y1 - 2020/8
N2 - 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.
AB - 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.
KW - Adequacy assessment
KW - autonomous driving
KW - electric vehicle (EV)
KW - isolated system
KW - vehicle-to-grid (V2G)
KW - vehicle-to-home (V2H)
UR - http://www.scopus.com/inward/record.url?scp=85089874306&partnerID=8YFLogxK
U2 - 10.1109/TITS.2019.2929767
DO - 10.1109/TITS.2019.2929767
M3 - Journal article
AN - SCOPUS:85089874306
SN - 1524-9050
VL - 21
SP - 3469
EP - 3475
JO - IEEE Transactions on Intelligent Transportation Systems
JF - IEEE Transactions on Intelligent Transportation Systems
IS - 8
M1 - 8798760
ER -