Bayesian Estimates of Transmission Line Outage Rates That Consider Line Dependencies

被引:9
作者
Zhou, Kai [1 ]
Cruise, James R. [2 ]
Dent, Chris J. [3 ]
Dobson, Ian [1 ]
Wehenkel, Louis [4 ]
Wang, Zhaoyu [1 ]
Wilson, Amy L. [3 ]
机构
[1] Iowa State Univ, Ames, IA 50011 USA
[2] Riverlane Res, Cambridge CB2 3BZ, England
[3] Univ Edinburgh, Edinburgh EH9 3FD, Midlothian, Scotland
[4] Univ Liege, B-4000 Liege, Belgium
基金
英国工程与自然科学研究理事会;
关键词
Bayes methods; Power transmission lines; Biological system modeling; Data models; Uncertainty; Meteorology; Power system reliability; Bayesian methods; hierarchical model; outage rates; transmission lines; transmission system reliability;
D O I
10.1109/TPWRS.2020.3012840
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页码:1095 / 1106
页数:12
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