Optimisation of an emergency plan in gas distribution network operations with Bayesian networks
by Abdelaziz Lakehal; Zine Ghemari
International Journal of Reliability and Safety (IJRS), Vol. 10, No. 3, 2016

Abstract: The focus of this paper is on the development of a predictive emergency plan for operating gas networks in crisis situations (major incident or disaster). The first contribution of this paper is summarised in the first part, which defines the essential elements of an emergency plan and the centre position of reliability in such plan. A Bayesian model is implemented; it allows the estimation of probabilities of valve closure based on system-level performance for isolating gas distribution network. Also it allows the prioritisation of revamp work and capacity-upgrade actions related to existing gas pipe networks for the sake of safe operations. Finally a case study of a distribution network supplying a city is presented. The paper demonstrates that Bayesian networks allow for the management and the predictive control of gas networks and the simulation of effect of maintenance and investment actions on the performance of isolating system.

Online publication date: Tue, 17-Jan-2017

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Reliability and Safety (IJRS):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com