Document Type
Article
Language
eng
Publication Date
7-2014
Publisher
Institute of Electrical and Electronic Engineers (IEEE)
Source Publication
IEEE Transactions on Power Systems
Source ISSN
0885-8950
Abstract
A scalable and analytically tractable probabilistic model for the cascading failure dynamics in power grids is constructed while retaining key physical attributes and operating characteristics of the power grid. The approach is based upon extracting a reduced abstraction of large-scale power grids using a small number of aggregate state variables while modeling the system dynamics using a continuous-time Markov chain. The aggregate state variables represent critical power-grid attributes, which have been shown, from prior simulation-based and historical-data-based analysis, to strongly influence the cascading behavior. The transition rates among states are formulated in terms of certain parameters that capture grid's operating characteristics comprising loading level, error in transmission-capacity estimation, and constraints in performing load shedding. The model allows the prediction of the evolution of blackout probability in time. Moreover, the asymptotic analysis of the blackout probability enables the calculation of the probability mass function of the blackout size. A key benefit of the model is that it enables the characterization of the severity of cascading failures in terms of the operating characteristics of the power grid..
Recommended Citation
Rahnamay-Naeini, Mahshid; Wang, Zhuoyao; Ghani, Nasir; Mammoli, Andrea; and Hayat, Majeed M., "Stochastic Analysis of Cascading-Failure Dynamics in Power Grids" (2014). Electrical and Computer Engineering Faculty Research and Publications. 562.
https://epublications.marquette.edu/electric_fac/562
ADA Accessible Version
Comments
Accepted version. IEEE Transactions on Power Systems, Vol. 29, No. 4 (July 2014): 1767-1779. DOI. © 2014 Institute of Electrical and Electronic Engineers (IEEE). Used with permission.
Majeed M. Hayat was affiliated with University of New Mexico, Albuquerque at the time of publication.