A Combined Repair Crew Dispatch Problem for Resilient Electric and Natural Gas System Considering Reconfiguration and DG Islanding
Abstract
Resilience is an overarching concept that requires combined efforts from interdependent critical infrastructures to achieve. As the interdependence between the power system and the natural gas system grows, the roles of coordination in post-disaster repair will be unneglectable to improve the resilience of the two systems. In this paper, a combined repair crew dispatch problem for the interdependent power and natural gas systems is proposed. The repair schedule of the two systems is coordinated and co-optimized. Both power system topology reconfiguration and intentional DG islanding are modeled as operational measures to further improve the resilience of the interdependent systems. Case studies validate the effectiveness of the proposed method in reducing load shedding and repair duration, and prove that the interdependence has a significant impact on the repair sequence and crew coordination.
- Authors:
-
- Xi'an Jiaotong Univ. (China)
- Argonne National Lab. (ANL), Argonne, IL (United States)
- Southern Methodist Univ., Dallas, TX (United States)
- Publication Date:
- Research Org.:
- Argonne National Lab. (ANL), Argonne, IL (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE); National Natural Science Foundation of China (NSFC)
- OSTI Identifier:
- 1737394
- Alternate Identifier(s):
- OSTI ID: 1737393
- Grant/Contract Number:
- AC02-06CH11357
- Resource Type:
- Accepted Manuscript
- Journal Name:
- IEEE Transactions on Power Systems
- Additional Journal Information:
- Journal Volume: 34; Journal Issue: 4; Journal ID: ISSN 0885-8950
- Publisher:
- IEEE
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 24 POWER TRANSMISSION AND DISTRIBUTION; Critical infrastructure; extreme event; natural gas system; power system; resilience
Citation Formats
Lin, Yanling, Chen, Bo, Wang, Jianhui, and Bie, Zhaohong. A Combined Repair Crew Dispatch Problem for Resilient Electric and Natural Gas System Considering Reconfiguration and DG Islanding. United States: N. p., 2019.
Web. doi:10.1109/tpwrs.2019.2895198.
Lin, Yanling, Chen, Bo, Wang, Jianhui, & Bie, Zhaohong. A Combined Repair Crew Dispatch Problem for Resilient Electric and Natural Gas System Considering Reconfiguration and DG Islanding. United States. https://doi.org/10.1109/tpwrs.2019.2895198
Lin, Yanling, Chen, Bo, Wang, Jianhui, and Bie, Zhaohong. Thu .
"A Combined Repair Crew Dispatch Problem for Resilient Electric and Natural Gas System Considering Reconfiguration and DG Islanding". United States. https://doi.org/10.1109/tpwrs.2019.2895198. https://www.osti.gov/servlets/purl/1737394.
@article{osti_1737394,
title = {A Combined Repair Crew Dispatch Problem for Resilient Electric and Natural Gas System Considering Reconfiguration and DG Islanding},
author = {Lin, Yanling and Chen, Bo and Wang, Jianhui and Bie, Zhaohong},
abstractNote = {Resilience is an overarching concept that requires combined efforts from interdependent critical infrastructures to achieve. As the interdependence between the power system and the natural gas system grows, the roles of coordination in post-disaster repair will be unneglectable to improve the resilience of the two systems. In this paper, a combined repair crew dispatch problem for the interdependent power and natural gas systems is proposed. The repair schedule of the two systems is coordinated and co-optimized. Both power system topology reconfiguration and intentional DG islanding are modeled as operational measures to further improve the resilience of the interdependent systems. Case studies validate the effectiveness of the proposed method in reducing load shedding and repair duration, and prove that the interdependence has a significant impact on the repair sequence and crew coordination.},
doi = {10.1109/tpwrs.2019.2895198},
journal = {IEEE Transactions on Power Systems},
number = 4,
volume = 34,
place = {United States},
year = {Thu Jan 24 00:00:00 EST 2019},
month = {Thu Jan 24 00:00:00 EST 2019}
}