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Supply reliability assessment of a gas pipeline network under stochastic demands.
- Source :
-
Reliability Engineering & System Safety . May2021, Vol. 209, pN.PAG-N.PAG. 1p. - Publication Year :
- 2021
-
Abstract
- • LHS-CD method is adopted to assess supply adequacy under demand uncertainty. • Typical scenarios are selected based on the Markov stochastic process. • The assessment results of gas supply reliability are demonstrated in four aspects. • The reasons for gas supply shortages are analyzed in detail. An integrated methodology to assess the gas supply reliability of a gas pipeline network considering stochastic demands is proposed in this study. Typical scenarios are selected based on the structural reliability calculated by probability theory and stochastic process, including the normal scenario and some failure scenarios with a high probability. For each specific scenario, the gas supply condition is assessed based on the Latin hypercube sampling with the Cholesky decomposition method under stochastic demands. The maximum flow method based on the Dijkstra algorithm is adopted to determine whether the gas demand of customers can be fully covered and optimize the supply scheme under shortages. Finally, the assessment results are demonstrated from the following four aspects: the probability distribution of gas shortages under the normal scenario, identification of units with a high failure probability and vulnerable units, the reasons of gas supply shortages and corresponding probabilities, and the probability distribution of supply reliability for a gas pipeline network and each customer. The methodology is applied to a large-scale gas pipeline network in China. The results of the supply reliability assessment are analyzed in detail, and the sensitivity analysis of the gas demand uncertainty level on gas supply reliability is conducted. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09518320
- Volume :
- 209
- Database :
- Academic Search Index
- Journal :
- Reliability Engineering & System Safety
- Publication Type :
- Academic Journal
- Accession number :
- 148987958
- Full Text :
- https://doi.org/10.1016/j.ress.2021.107482