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Short-term supply reliability assessment of a gas pipeline system under demand variations

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  • Chen, Qian
  • Zuo, Lili
  • Wu, Changchun
  • Bu, Yaran
  • Lu, Yifei
  • Huang, Yanfei
  • Chen, Feng

Abstract

It is the basic responsibility for pipeline companies to satisfy the gas demand of customers. A methodology is proposed to assess the short-term supply reliability of a gas pipeline system under demand variations in this paper. Based on the failure rate and repair rate of the pipe segments and compressor units obtained through historical operational data, the probability under different structural failure scenarios of a gas pipeline system is computed through the stochastic process and probability theory. Indices from aspects of adequacy, availability, and shortage rate are developed to reflect the supply reliability. To reflect the assessment results intuitively, the cumulative probability function is adopted to reflect the supply adequacy and availability, and the probability distribution is adopted to reflect the supply shortage rate during the assessment period. For all scenarios, supply reliability is calculated through batch transient hydraulic and thermal simulations of a gas pipeline system by Stoner Pipeline Simulator considering practical operational processes and legal constraints. The proposed methodology is performed based on the Trans-Asian gas pipeline A-B system, and the functions of cross-over valves on supply reliability of the Trans-Asian gas pipeline A-B system is studied.

Suggested Citation

  • Chen, Qian & Zuo, Lili & Wu, Changchun & Bu, Yaran & Lu, Yifei & Huang, Yanfei & Chen, Feng, 2020. "Short-term supply reliability assessment of a gas pipeline system under demand variations," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
  • Handle: RePEc:eee:reensy:v:202:y:2020:i:c:s0951832020305056
    DOI: 10.1016/j.ress.2020.107004
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    5. Yu, Weichao & Huang, Weihe & Wen, Yunhao & Li, Yichen & Liu, Hongfei & Wen, Kai & Gong, Jing & Lu, Yanan, 2021. "An integrated gas supply reliability evaluation method of the large-scale and complex natural gas pipeline network based on demand-side analysis," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    6. Su, Yue & Li, Jingfa & Yu, Bo & Zhao, Yanlin & Yao, Jun, 2021. "Fast and accurate prediction of failure pressure of oil and gas defective pipelines using the deep learning model," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
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    8. 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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