Power system cascading risk assessment based on complex network theory

Zhuoyang Wang, David J. Hill, Guo Chen and Zhao Yang Dong

Physica A: Statistical Mechanics and its Applications, 2017, vol. 482, issue C, 532-543

Abstract: When a single failure occurs in a vulnerable part of a power system, this may cause a large area cascading event. Therefore, an advanced method that can assess the risks during cascading events is needed. In this paper, an improved complex network model for power system risk assessment is proposed. Risk is defined by consequence and probability of the failures in this model, which are affected by both power factors and network structure. Compared with existing risk assessment models, the proposed one can evaluate the risk of the system comprehensively during a cascading event by combining the topological and electrical information. A new cascading event simulation module is adopted to identify the power grid cascading chain from a system-level view. In addition, simulations are investigated on the IEEE 14 bus system and IEEE 39 bus system respectively to illustrate the performance of the proposed module. The simulation results demonstrate that the proposed method is effective in a power grid risk assessment during cascading event.

Keywords: Risk assessment; Cascading event; Complex network; Cascading chain (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437117303345
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

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:eee:phsmap:v:482:y:2017:i:c:p:532-543

DOI: 10.1016/j.physa.2017.04.031

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().