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

Troffaes, Matthias C.M.; Blake, Simon

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

Troffaes, Matthias C.M.; Blake, Simon

Authors

Professor Matthias Troffaes matthias.troffaes@durham.ac.uk
Professor

Simon Blake

Contributors

Fabio Cozman
Editor

Thierry Denoeux
Editor

Sebastien Destercke
Editor

Teddy Seidenfeld
Editor

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). A Robust Data Driven Approach to Quantifying Common-Cause Failure in Power Networks. In F. Cozman, T. Denoeux, S. Destercke, & T. Seidenfeld (Eds.), ISIPTA ’13 : proceedings of the eighth international symposium on imprecise probability : theories and applications July 2-5 2013, Compiègne, France (311-317)

Conference Name	ISIPTA'13: Proceedings of the Eighth International Symposium on Imprecise Probability: Theories and Applications
Conference Location	Compiegne, France
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