DocumentCode :
182039
Title :
Monte-Carlo Based Reliability Modelling of a Gas Network Using Graph Theory Approach
Author :
Praks, Pavel ; Kopustinskas, Vytis
Author_Institution :
Energy Security, Syst. & Market, Joint Res. Centre, Ispra, Italy
fYear :
2014
fDate :
8-12 Sept. 2014
Firstpage :
380
Lastpage :
386
Abstract :
The aim of the study is to develop a European gas transmission system probabilistic model to analyse in a single computer model, the reliability and capacity constraints of a gas transmission network. We describe our approach to modelling the reliability and capacity constraints of networks elements, for example gas storages and compressor stations by a multi-state system. The paper presents our experience with the computer implementation of a gas transmission network probabilistic prototype model based on generalization of the maximum flow problem for a stochastic-flow network in which elements can randomly fail with known failure probabilities. The paper includes a test-case benchmark study, which is based on a real gas transmission network. Monte-Carlo simulations are used for estimating the probability that less than the demanded volume of the commodity (for example, gas) is available in the selected network nodes. Simulated results are presented and analysed in depth by statistical methods.
Keywords :
Monte Carlo methods; compressors; gas industry; graph theory; probability; reliability; stochastic processes; European gas transmission system probabilistic model; Monte-Carlo based reliability modelling; Monte-Carlo simulations; capacity constraints; compressor stations; computer model; gas network; gas storages; gas transmission network probabilistic prototype model; graph theory approach; known failure probabilities; maximum flow problem; multistate system; network elements; network nodes; probability estimation; reliability constraints; statistical methods; stochastic-flow network; test-case benchmark study; Computational modeling; Computer network reliability; Liquefied natural gas; Monte Carlo methods; Pipelines; Probabilistic logic; Reliability; Monte-Carlo methods; gas transmission network modelling; network reliability; network resilience;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Availability, Reliability and Security (ARES), 2014 Ninth International Conference on
Conference_Location :
Fribourg
Type :
conf
DOI :
10.1109/ARES.2014.57
Filename :
6980306
Link To Document :
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