Presentation
Can the Markovian influence graph simulate cascading resilience from historical outage data?
Electrical and Computer Engineering Conference Papers, Posters and Presentations
Document Type
Conference Proceeding
Disciplines
Publication Version
Submitted Manuscript
Publication Date
1-1-2020
Abstract
It is challenging to simulate the cascading line outages that can follow initial damage to the electric power transmission system from extreme events. Instead of model-based simulation, we propose using a Markovian influence graph driven by historical utility data to sample the cascades. The sampling method encompasses the rare, large cascades that contribute greatly to the blackout risk. This suggested new approach contributes a high-level simulation of cascading line outages that is driven by standard utility data.
Rights
© 2020 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
2020
Language
en
File Format
application/pdf
Citation Information
Kai Zhou, Ian Dobson and Zhaoyu Wang. "Can the Markovian influence graph simulate cascading resilience from historical outage data?" (2020) Available at: http://works.bepress.com/ian-dobson/37/
This is a pre-print of the proceeding Zhou, Kai, Ian Dobson, and Zhaoyu Wang. "Can the Markovian influence graph simulate cascading resilience from historical outage data?" (2020). Posted with permission.