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Supply reliability assessment of a gas pipeline network under stochastic demands

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Listed:
  • Chen, Qian
  • Zuo, Lili
  • Wu, Changchun
  • Cao, Yankai
  • Bu, Yaran
  • Chen, Feng
  • Sadiq, Rehan

Abstract

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.

Suggested Citation

  • Chen, Qian & Zuo, Lili & Wu, Changchun & Cao, Yankai & Bu, Yaran & Chen, Feng & Sadiq, Rehan, 2021. "Supply reliability assessment of a gas pipeline network under stochastic demands," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    • Handle: RePEc:eee:reensy:v:209:y:2021:i:c:s095183202100048x
    DOI: 10.1016/j.ress.2021.107482
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    Cited by:

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    5. Lu, Cheng & Teng, Da & Chen, Jun-Yu & Fei, Cheng-Wei & Keshtegar, Behrooz, 2023. "Adaptive vectorial surrogate modeling framework for multi-objective reliability estimation," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    6. Xiao, Jun & Qu, Yuqing & She, Buxin & Song, Chenhui, 2023. "Operational boundary of flow network," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    7. Ding, Yueting & Chen, Sai & Zheng, Yilei & Chai, Shanglei & Nie, Rui, 2022. "Resilience assessment of China's natural gas system under supply shortages: A system dynamics approach," Energy, Elsevier, vol. 247(C).
    8. Cabrales, Sergio & Valencia, Carlos & Ramírez, Carlos & Ramírez, Andrés & Herrera, Juan & Cadena, Angela, 2022. "Stochastic cost-benefit analysis to assess new infrastructure to improve the reliability of the natural gas supply," Energy, Elsevier, vol. 246(C).
    9. Wang, WuChang & Zhang, Yi & Li, YuXing & Hu, Qihui & Liu, Chengsong & Liu, Cuiwei, 2022. "Vulnerability analysis method based on risk assessment for gas transmission capabilities of natural gas pipeline networks," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).

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