Article (Scientific journals)
Bayesian estimates of transmission line outage rates that consider line dependencies
Zhou, Kai; Cruise, James R; Dent, Chris J et al.
2021In IEEE Transactions on Power Systems, 36 (2), p. 1095-1106
Peer Reviewed verified by ORBi
 

Files


Full Text
ZhouBayesPS20.pdf
Author preprint (1.92 MB)
Download

All documents in ORBi are protected by a user license.

Send to



Details



Keywords :
Bayesian methods; hierarchical model; outage rates; transmission lines; transmission system reliability
Abstract :
[en] Transmission line outage rates are fundamental to power system reliability analysis. Line outages are infrequent, occurring only about once a year, so outage data are limited. We propose a Bayesian hierarchical model that leverages line dependencies to better estimate outage rates of individual transmission lines from limited outage data. The Bayesian estimates have a lower standard deviation than estimating the outage rates simply by dividing the number of outages by the number of years of data, especially when the number of outages is small. The Bayesian model produces more accurate individual line outage rates, as well as estimates of the uncertainty of these rates. Better estimates of line outage rates can improve system risk assessment, outage prediction, and maintenance scheduling.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Zhou, Kai;  Iowa State University
Cruise, James R
Dent, Chris J
Dobson, Ian;  Iowa State University
Wehenkel, Louis  ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Méthodes stochastiques
Wang, Zhaoyu
Wilson, Amy L
Language :
English
Title :
Bayesian estimates of transmission line outage rates that consider line dependencies
Publication date :
March 2021
Journal title :
IEEE Transactions on Power Systems
ISSN :
0885-8950
Publisher :
Institute of Electrical and Electronics Engineers, United States - New Jersey
Volume :
36
Issue :
2
Pages :
1095-1106
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 03 August 2020

Statistics


Number of views
63 (7 by ULiège)
Number of downloads
44 (2 by ULiège)

Scopus citations®
 
7
Scopus citations®
without self-citations
4
OpenCitations
 
3

Bibliography


Similar publications



Contact ORBi