Abstract
Cascading phenomena have been studied extensively in various networks. Particularly, it has been shown that the community structures in networks impact their cascade processes. However, the role of community structures in cascading failures in power grids have not been studied heretofore. In this paper, cascading failures in power grids are studied using interaction graphs. Key evidence has been provided that the community structures in interaction graphs bear critical information about the cascade process and the role of system components in cascading failures in power grids. Furthermore, a centrality measure based on the community structures is proposed to identify critical components of the system, which their protection can help in containing failures within a community and prevent the propagation of failures to large sections of the power grid. Various criticality evaluation techniques, including data driven, epidemic simulation based, power system simulation based, and graph based, have been used to verify the importance of the identified critical components in the cascade process and compare them with those identified by traditional centrality measures. Moreover, it has been shown that the loading level of the power grid impacts the interaction graph and consequently, the community structure and criticality of the components in the cascade process.
| Original language | English |
|---|---|
| Article number | 8663432 |
| Pages (from-to) | 1079-1093 |
| Number of pages | 15 |
| Journal | IEEE Transactions on Network Science and Engineering |
| Volume | 7 |
| Issue number | 3 |
| DOIs | |
| State | Published - Jul 1 2020 |
Bibliographical note
Publisher Copyright:© 2013 IEEE.
Funding
Manuscript received July 23, 2018; revised February 28, 2019; accepted March 1, 2019. Date of publication March 8, 2019; date of current version September 2, 2020. This work was supported in part by the National Science Foundation under Grant 1761471, and in part by the Defense Threat Reduction Agency’s Basic Research Program under Grant HDTRA1-13-1-0020. Recommended for acceptance by M. Porter. (Corresponding author: Mah-shid Rahnamay-Naeini.) U. Nakarmi and M. Rahnamay-Naeini are with the Department of Electrical Engineering, University of South Florida, Tampa, FL 33620, USA. (e-mail: [email protected]; [email protected]). This material is based upon work supported by the National Science Foundation under Grant No. 1761471. Also, this work is partially supported by the Defense Threat Reduction Agency’s Basic Research Program under grant No. HDTRA1-13-1-0020.
| Funders | Funder number |
|---|---|
| National Science Foundation Arctic Social Science Program | |
| Directorate for Computer and Information Science and Engineering | 1761471 |
| Defense Threat Reduction Agency | HDTRA1-13-1-0020 |
Keywords
- Power grids
- cascading failures
- community structure
- critical component
- influence model
- interaction graph
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Computer Networks and Communications