Article
Can an influence graph driven by outage data determine transmission line upgrades that mitigate cascading blackouts?
Electrical and Computer Engineering Conference Papers, Posters and Presentations
Document Type
Conference Proceeding
Disciplines
Conference
IEEE International Conference Probabilistic Methods Applied to Power Systems (PMAPS)
Publication Version
Submitted Manuscript
Publication Date
1-1-2018
Conference Date
June 24-28, 2018
Geolocation
(43.6187102, -116.21460680000001)
Abstract
We transform historically observed line outages in a power transmission network into an influence graph that statistically describes how cascades propagate in the power grid. The influence graph can predict the critical lines that are historically most involved in cascading propagation. After upgrading these critical lines, simulating the influence graph suggests that these upgrades could mitigate large blackouts by reducing the probability of large cascades.
Rights
Copyright 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Copyright Owner
IEEE
Copyright Date
2018
Language
en
File Format
application/pdf
Citation Information
Kai Zhou, Ian Dobson, Paul D.H. Hines and Zhaoyu Wang. "Can an influence graph driven by outage data determine transmission line upgrades that mitigate cascading blackouts?" Boise, ID(2018) Available at: http://works.bepress.com/ian-dobson/26/
This is a manuscript of the proceeding Zhou, Kai, Ian Dobson, Paul D.H. Hines, and Zhaoyu Wang, "Can an influence graph driven by outage data determine transmission line upgrades that mitigate cascading blackouts?" that will appear at IEEE International Conference Probabilistic Methods Applied to Power Systems (PMAPS), Boise, ID. June 24-28, 2018.