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Risk analysis of an underground gas storage facility using a physics-based system performance model and Monte Carlo simulation

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  • Syed, Zaki
  • Lawryshyn, Yuri

Abstract

This paper presents a quantitative risk analysis model to study operational reliability risk of an underground gas storage (UGS) facility. The model combines a thermo-hydraulic performance model for a gas storage facility consisting of a gathering system, compression system and transmission system with a Monte Carlo simulation of potential disruption events. The disruption events can impact the availability of one or more critical assets within the gas storage facility, which in turn affect the gas flow capability. The flow capability is compared against externally derived gas flow demand patterns to determine if shortfalls in supply can occur. The proposed model is highly configurable and can be used to quantitatively assess operational reliability risk in a UGS facility. A multitude of potential events that can affect a UGS facility can be analyzed. The integrated physics model means an analyst does not have to explicitly account for changes in system performance resulting from disruption events. As such, many combinations of asset configurations, system states and disruption events can be analyzed within a single modeling framework.

Suggested Citation

  • Syed, Zaki & Lawryshyn, Yuri, 2020. "Risk analysis of an underground gas storage facility using a physics-based system performance model and Monte Carlo simulation," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    • Handle: RePEc:eee:reensy:v:199:y:2020:i:c:s0951832019304557
    DOI: 10.1016/j.ress.2020.106792
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    1. Praks, Pavel & Kopustinskas, Vytis & Masera, Marcelo, 2015. "Probabilistic modelling of security of supply in gas networks and evaluation of new infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 254-264.
    2. Fodstad, Marte & Midthun, Kjetil T. & Tomasgard, Asgeir, 2015. "Adding flexibility in a natural gas transportation network using interruptible transportation services," European Journal of Operational Research, Elsevier, vol. 243(2), pages 647-657.
    3. von Lanzenauer, Christoph Haehling & James, William G. & Wright, Don D., 1992. "Insufficient supply in a natural gas distribution system: A risk analysis," European Journal of Operational Research, Elsevier, vol. 56(1), pages 41-53, January.
    4. von Lanzenauer, Christoph Haehling & James, William G. & Wright, Don D., 1995. "Service level risk in a pipeline system: A stochastic analysis," European Journal of Operational Research, Elsevier, vol. 81(3), pages 489-499, March.
    5. Louit, D.M. & Pascual, R. & Jardine, A.K.S., 2009. "A practical procedure for the selection of time-to-failure models based on the assessment of trends in maintenance data," Reliability Engineering and System Safety, Elsevier, vol. 94(10), pages 1618-1628.
    6. Aouam, Tarik & Rardin, Ronald & Abrache, Jawad, 2010. "Robust strategies for natural gas procurement," European Journal of Operational Research, Elsevier, vol. 205(1), pages 151-158, August.
    7. Yang, Chunhe & Jing, Wenjun & Daemen, J.J.K. & Zhang, Guimin & Du, Chao, 2013. "Analysis of major risks associated with hydrocarbon storage caverns in bedded salt rock," Reliability Engineering and System Safety, Elsevier, vol. 113(C), pages 94-111.
    8. Wang, Jing & Zuo, Wangda & Rhode-Barbarigos, Landolf & Lu, Xing & Wang, Jianhui & Lin, Yanling, 2019. "Literature review on modeling and simulation of energy infrastructures from a resilience perspective," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 360-373.
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