Quantitative Resilience Assessment under a Tri-Stage Framework for Power Systems

Han Zhang, Hanjie Yuan, Gengfeng Li and Yanling Lin
Additional contact information
Han Zhang: The State Key Laboratory of Electrical Insulation and Power Equipment, the Shaanxi Key Laboratory of Smart Grid, Xi’an Jiaotong University, Xi’an 710049, China
Hanjie Yuan: The State Key Laboratory of Electrical Insulation and Power Equipment, the Shaanxi Key Laboratory of Smart Grid, Xi’an Jiaotong University, Xi’an 710049, China
Gengfeng Li: The State Key Laboratory of Electrical Insulation and Power Equipment, the Shaanxi Key Laboratory of Smart Grid, Xi’an Jiaotong University, Xi’an 710049, China
Yanling Lin: The State Key Laboratory of Electrical Insulation and Power Equipment, the Shaanxi Key Laboratory of Smart Grid, Xi’an Jiaotong University, Xi’an 710049, China

Energies, 2018, vol. 11, issue 6, 1-23

Abstract: The frequent occurrence of natural disasters and malicious attacks has exerted unprecedented disturbances on power systems, accounting for the extensive attention paid to power system resilience. Combined with the evolving nature of general disasters, this paper proposes resilience assessment approaches for power systems under a tri-stage framework. The pre-disaster toughness is proposed to quantify the robustness of power systems against potential disasters, where the thinking of area division and partitioned multi-objective risk method (PMRM) is introduced. In the case of information deficiency caused by disasters, the during-disaster resistance to disturbance is calculated to reflect the real-time system running state by state estimation (SE). The post-disaster restoration ability consists of response ability, restoration efficiency and restoration economy, which is evaluated by Sequential Monte-Carlo Simulation to simulate the system restoration process. Further, a synthetic metric system is presented to quantify the resilience performance of power systems from the above three aspects. The proposed approaches and framework are validated on the IEEE RTS 79 system, and helpful conclusions are drawn from extensive case studies.

Keywords: power system; resilience assessment; Monte-Carlo Simulation; extreme weather (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://www.mdpi.com/1996-1073/11/6/1427/pdf (application/pdf)
https://www.mdpi.com/1996-1073/11/6/1427/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:11:y:2018:i:6:p:1427-:d:150361

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().