A Robust Data Driven Approach to Quantifying Common-Cause Failure in Power Networks

Troffaes, Matthias C.M.; Blake, Simon

Abstract

The standard alpha-factor model for common cause failure assumes symmetry, in that all components must have identical failure rates. In this paper, we generalise the alpha-factor model to deal with asymmetry, in order to apply the model to power networks, which are typically asymmetric. For parameter estimation, we propose a set of conjugate Dirichlet-Gamma priors, and we discuss how posterior bounds can be obtained. Finally, we demonstrate our methodology on a simple yet realistic example.

Citation

Troffaes, M. C., & Blake, S. (2013, July). A Robust Data Driven Approach to Quantifying Common-Cause Failure in Power Networks. Presented at ISIPTA'13: Proceedings of the Eighth International Symposium on Imprecise Probability: Theories and Applications, Compiegne, France

• Presentation Conference Type: Conference Paper (published)
• Conference Name: ISIPTA'13: Proceedings of the Eighth International Symposium on Imprecise Probability: Theories and Applications
• Publication Date: Jul 5, 2013
• Deposit Date: May 29, 2013
• Publicly Available Date: Oct 22, 2014
• Pages: 311-317
• Book Title: ISIPTA ’13 : proceedings of the eighth international symposium on imprecise probability : theories and applications July 2-5 2013, Compiègne, France.
• Keywords: Robust, Alpha-factor, Failure, Reliability, Gamma, Dirichlet.
• Public URL: https://durham-repository.worktribe.com/output/1156384
• Publisher URL: http://www.sipta.org/isipta13/index.php?id=paper&paper=031.html