IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v175y2018icp79-91.html
   My bibliography  Save this article

A systematic framework of vulnerability analysis of a natural gas pipeline network

Author

Listed:
  • Su, Huai
  • Zio, Enrico
  • Zhang, Jinjun
  • Li, Xueyi

Abstract

A systematic framework is developed to assess the vulnerability of natural gas pipeline networks. To measure the impact of accidents on gas supply service, a consequence model is developed based on a flow algorithm embedded into an optimization scheme, with the consideration of physical constraints. The vulnerability analysis is performed from three viewpoints: global vulnerability analysis, demand robustness and critical pipeline analysis. The global vulnerability analysis is performed considering hazards and threats in gas sources, demand and transmission system. The analysis of demand robustness evaluates the capacities of demand sites to withstand the strains imposed on the pipeline network system and further explains the differences in capacities, from a graph theory perspective. In the critical pipeline analysis, criticalities of pipelines are evaluated by considering direct attacks and using a physical flow-based method. The analyses are performed on a relatively complex gas pipeline network taken from literature.

Suggested Citation

  • Su, Huai & Zio, Enrico & Zhang, Jinjun & Li, Xueyi, 2018. "A systematic framework of vulnerability analysis of a natural gas pipeline network," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 79-91.
    • Handle: RePEc:eee:reensy:v:175:y:2018:i:c:p:79-91
    DOI: 10.1016/j.ress.2018.03.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832017311651
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2018.03.006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Johansson, Jonas & Hassel, Henrik & Zio, Enrico, 2013. "Reliability and vulnerability analyses of critical infrastructures: Comparing two approaches in the context of power systems," Reliability Engineering and System Safety, Elsevier, vol. 120(C), pages 27-38.
    2. Du, Y.F. & Jiang, L. & Li, Y.Z. & Counsell, J. & Smith, J.S., 2016. "Multi-objective demand side scheduling considering the operational safety of appliances," Applied Energy, Elsevier, vol. 179(C), pages 864-874.
    3. Shaffer, Brenda, 2013. "Natural gas supply stability and foreign policy," Energy Policy, Elsevier, vol. 56(C), pages 114-125.
    4. Sean Wilkinson & Sarah Dunn & Shu Ma, 2012. "The vulnerability of the European air traffic network to spatial hazards," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 60(3), pages 1027-1036, February.
    5. Wang, Zhuoyang & Chen, Guo & Hill, David J. & Dong, Zhao Yang, 2016. "A power flow based model for the analysis of vulnerability in power networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 105-115.
    6. Levitin, Gregory & Hausken, Kjell, 2009. "Meeting a demand vs. enhancing protections in homogeneous parallel systems," Reliability Engineering and System Safety, Elsevier, vol. 94(11), pages 1711-1717.
    7. Zeniewski, Peter & Bolado-Lavin, Ricardo, 2012. "A review of national gas emergency plans in the European Union," Energy Policy, Elsevier, vol. 49(C), pages 652-662.
    8. Siano, Pierluigi, 2014. "Demand response and smart grids—A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 461-478.
    9. Zio, Enrico & Piccinelli, Roberta, 2010. "Randomized flow model and centrality measure for electrical power transmission network analysis," Reliability Engineering and System Safety, Elsevier, vol. 95(4), pages 379-385.
    10. Ouyang, Min & Xu, Min & Zhang, Chi & Huang, Shitong, 2017. "Mitigating electric power system vulnerability to worst-case spatially localized attacks," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 144-154.
    11. Kjell Hausken & Jun Zhuang (ed.), 2015. "Game Theoretic Analysis of Congestion, Safety and Security," Springer Series in Reliability Engineering, Springer, edition 127, number 978-3-319-11674-7, February.
    12. Ferrario, E. & Pedroni, N. & Zio, E., 2016. "Evaluation of the robustness of critical infrastructures by Hierarchical Graph representation, clustering and Monte Carlo simulation," Reliability Engineering and System Safety, Elsevier, vol. 155(C), pages 78-96.
    13. 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.
    14. Kjell Hausken & Jun Zhuang (ed.), 2015. "Game Theoretic Analysis of Congestion, Safety and Security," Springer Series in Reliability Engineering, Springer, edition 127, number 978-3-319-13009-5, February.
    15. Nicholson, Charles D. & Barker, Kash & Ramirez-Marquez, Jose E., 2016. "Flow-based vulnerability measures for network component importance: Experimentation with preparedness planning," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 62-73.
    16. Prodan, Ionela & Zio, Enrico & Stoican, Florin, 2015. "Fault tolerant predictive control design for reliable microgrid energy management under uncertainties," Energy, Elsevier, vol. 91(C), pages 20-34.
    17. Cherp, Aleh & Jewell, Jessica, 2014. "The concept of energy security: Beyond the four As," Energy Policy, Elsevier, vol. 75(C), pages 415-421.
    18. Enrico Zio, 2013. "Monte Carlo Simulation: The Method," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 19-58, Springer.
    19. Enrico Zio, 2013. "The Monte Carlo Simulation Method for System Reliability and Risk Analysis," Springer Series in Reliability Engineering, Springer, edition 127, number 978-1-4471-4588-2, February.
    20. Faturechi, Reza & Miller-Hooks, Elise, 2014. "Travel time resilience of roadway networks under disaster," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 47-64.
    21. Enrico Zio, 2013. "System Reliability and Risk Analysis by Monte Carlo Simulation," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 59-81, Springer.
    22. Vivoda, Vlado, 2014. "Natural gas in Asia: Trade, markets and regional institutions," Energy Policy, Elsevier, vol. 74(C), pages 80-90.
    23. Zio, E. & Golea, L.R., 2012. "Analyzing the topological, electrical and reliability characteristics of a power transmission system for identifying its critical elements," Reliability Engineering and System Safety, Elsevier, vol. 101(C), pages 67-74.
    24. Aven, Terje, 2008. "A semi-quantitative approach to risk analysis, as an alternative to QRAs," Reliability Engineering and System Safety, Elsevier, vol. 93(6), pages 790-797.
    25. Alan Murray & Timothy Matisziw & Tony Grubesic, 2007. "Critical network infrastructure analysis: interdiction and system flow," Journal of Geographical Systems, Springer, vol. 9(2), pages 103-117, June.
    26. Mohammad Saied Dehghani & Hanif D. Sherali, 2016. "A resource allocation approach for managing critical network-based infrastructure systems," IISE Transactions, Taylor & Francis Journals, vol. 48(9), pages 826-837, September.
    27. Demirel, Hande & Kompil, Mert & Nemry, Françoise, 2015. "A framework to analyze the vulnerability of European road networks due to Sea-Level Rise (SLR) and sea storm surges," Transportation Research Part A: Policy and Practice, Elsevier, vol. 81(C), pages 62-76.
    28. Lo Prete, Chiara & Hobbs, Benjamin F., 2016. "A cooperative game theoretic analysis of incentives for microgrids in regulated electricity markets," Applied Energy, Elsevier, vol. 169(C), pages 524-541.
    29. Hausken, Kjell, 2010. "Defense and attack of complex and dependent systems," Reliability Engineering and System Safety, Elsevier, vol. 95(1), pages 29-42.
    30. Khakzad, Nima & Reniers, Genserik, 2015. "Using graph theory to analyze the vulnerability of process plants in the context of cascading effects," Reliability Engineering and System Safety, Elsevier, vol. 143(C), pages 63-73.
    31. Podofillini, L. & Zio, E. & Mercurio, D. & Dang, V.N., 2010. "Dynamic safety assessment: Scenario identification via a possibilistic clustering approach," Reliability Engineering and System Safety, Elsevier, vol. 95(5), pages 534-549.
    32. Enrico Zio, 2013. "System Reliability and Risk Analysis," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 7-17, Springer.
    33. Zio, Enrico, 2016. "Challenges in the vulnerability and risk analysis of critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 137-150.
    34. Kuznetsova, Elizaveta & Li, Yan-Fu & Ruiz, Carlos & Zio, Enrico, 2014. "An integrated framework of agent-based modelling and robust optimization for microgrid energy management," Applied Energy, Elsevier, vol. 129(C), pages 70-88.
    35. Mo, Hua-Dong & Li, Yan-Fu & Zio, Enrico, 2016. "A system-of-systems framework for the reliability analysis of distributed generation systems accounting for the impact of degraded communication networks," Applied Energy, Elsevier, vol. 183(C), pages 805-822.
    36. Dieckhöner, Caroline & Lochner, Stefan & Lindenberger, Dietmar, 2013. "European natural gas infrastructure: The impact of market developments on gas flows and physical market integration," Applied Energy, Elsevier, vol. 102(C), pages 994-1003.
    37. Cadini, Francesco & Agliardi, Gian Luca & Zio, Enrico, 2017. "Estimation of rare event probabilities in power transmission networks subject to cascading failures," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 9-20.
    38. Hausken, Kjell & Levitin, Gregory, 2009. "Minmax defense strategy for complex multi-state systems," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 577-587.
    39. Wang, Fei & Xu, Hanchen & Xu, Ti & Li, Kangping & Shafie-khah, Miadreza & Catalão, João. P.S., 2017. "The values of market-based demand response on improving power system reliability under extreme circumstances," Applied Energy, Elsevier, vol. 193(C), pages 220-231.
    40. Ouyang, Min & Pan, ZheZhe & Hong, Liu & He, Yue, 2015. "Vulnerability analysis of complementary transportation systems with applications to railway and airline systems in China," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 248-257.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Su, Huai & Zhang, Jinjun & Zio, Enrico & Yang, Nan & Li, Xueyi & Zhang, Zongjie, 2018. "An integrated systemic method for supply reliability assessment of natural gas pipeline networks," Applied Energy, Elsevier, vol. 209(C), pages 489-501.
    2. Abedi, Amin & Gaudard, Ludovic & Romerio, Franco, 2019. "Review of major approaches to analyze vulnerability in power system," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 153-172.
    3. 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).
    4. Yu, Weichao & Wen, Kai & Min, Yuan & He, Lei & Huang, Weihe & Gong, Jing, 2018. "A methodology to quantify the gas supply capacity of natural gas transmission pipeline system using reliability theory," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 128-141.
    5. Zhou, Xingyuan & van Gelder, P.H.A.J.M. & Liang, Yongtu & Zhang, Haoran, 2020. "An integrated methodology for the supply reliability analysis of multi-product pipeline systems under pumps failure," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    6. 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).
    7. Zheng, Xiaoyu & Tamaki, Hitoshi & Sugiyama, Tomoyuki & Maruyama, Yu, 2022. "Dynamic probabilistic risk assessment of nuclear power plants using multi-fidelity simulations," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    8. Michele Compare & Francesco Di Maio & Enrico Zio & Fausto Carlevaro & Sara Mattafirri, 2016. "Improving scheduled maintenance by missing data reconstruction: A double-loop Monte Carlo approach," Journal of Risk and Reliability, , vol. 230(5), pages 502-511, October.
    9. Di Maio, Francesco & Pettorossi, Chiara & Zio, Enrico, 2023. "Entropy-driven Monte Carlo simulation method for approximating the survival signature of complex infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    10. Senderov, Sergey M. & Smirnova, Elena M. & Vorobev, Sergey V., 2020. "Analysis of vulnerability of fuel supply systems in gas-consuming regions due to failure of critical gas industry facilities," Energy, Elsevier, vol. 212(C).
    11. Zio, Enrico, 2016. "Challenges in the vulnerability and risk analysis of critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 137-150.
    12. Wang, Fan & Li, Heng, 2018. "System reliability under prescribed marginals and correlations: Are we correct about the effect of correlations?," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 94-104.
    13. Tito G. Amaral & Vitor Fernão Pires & Armando Cordeiro & Daniel Foito & João F. Martins & Julia Yamnenko & Tetyana Tereschenko & Liudmyla Laikova & Ihor Fedin, 2023. "Incipient Fault Diagnosis of a Grid-Connected T-Type Multilevel Inverter Using Multilayer Perceptron and Walsh Transform," Energies, MDPI, vol. 16(6), pages 1-18, March.
    14. Penttinen, Jussi-Pekka & Niemi, Arto & Gutleber, Johannes & Koskinen, Kari T. & Coatanéa, Eric & Laitinen, Jouko, 2019. "An open modelling approach for availability and reliability of systems," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 387-399.
    15. Rocco, Claudio M. & Moronta, José & Ramirez-Marquez, José E. & Barker, Kash, 2017. "Effects of multi-state links in network community detection," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 46-56.
    16. Babykina, Génia & Brînzei, Nicolae & Aubry, Jean-François & Deleuze, Gilles, 2016. "Modeling and simulation of a controlled steam generator in the context of dynamic reliability using a Stochastic Hybrid Automaton," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 115-136.
    17. Compare, Michele & Bellani, Luca & Zio, Enrico, 2017. "Reliability model of a component equipped with PHM capabilities," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 4-11.
    18. Gascard, Eric & Simeu-Abazi, Zineb, 2018. "Quantitative Analysis of Dynamic Fault Trees by means of Monte Carlo Simulations: Event-Driven Simulation Approach," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 487-504.
    19. Shiyu Chen & Wei Wang & Enrico Zio, 2021. "A Simulation-Based Multi-Objective Optimization Framework for the Production Planning in Energy Supply Chains," Energies, MDPI, vol. 14(9), pages 1-27, May.
    20. Kim, Hyeonmin & Kim, Jung Taek & Heo, Gyunyoung, 2018. "Failure rate updates using condition-based prognostics in probabilistic safety assessments," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 225-233.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:175:y:2018:i:c:p:79-91. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.