A possibilistic-stochastic programming approach to resilient natural gas transmission network design problem under disruption: A case study

Document Type : Research Paper


1 School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

2 Research Institute of Petroleum Industry, Tehran, Iran


Resilient natural gas production and transmission pipeline for minimum cost and minimum the maximum cumulative fraction of unsupplied demand related to the met demand before disruption) are two essential goals of natural gas transmission network design. This paper develops a multi-objective multi-period mixed possibilistic-stochastic programming model to form a trade-off between resiliency and cost. In the presented model, the uncertainty of natural gas consumptions is considered as an operational risk while disruption risks are accounted for the failure of refinery production capacity and pipeline transmission capacity. The proposed model utilizes mitigation strategy such as extra capacities in the refinery, backup and fortified pipelines before disruption event and recovery strategy for restoring lost capacities of facilities to reach normal performance after disruption event. Finally, the performance of the proposed model is validated by executing a computational analysis using the data of a real case study. Our analysis shows that the efficiency of the natural gas transmission network is highly vulnerable to failure of pipeline and refinery capacity as well as demand fluctuations. Also, results indicate that utilizing extra refinery production capacity, fortified pipeline and backup pipeline options have numerous influences in raising the resiliency of the NG network.


Main Subjects

Azadeh, A., Shabanpour, N., Gharibdousti, M.S. and Nasirian, B., (2016). Optimization of supply chain based on macro ergonomics criteria: A case study in gas transmission unit. Journal of Loss Prevention in the Process Industries, 43, pp.332-351.
Babazadeh, R., Ghaderi, H. and Pishvaee, M.S., (2019). A benders-local branching algorithm for second-generation biodiesel supply chain network design under epistemic uncertainty. Computers & Chemical Engineering, 124, pp.364-380.
Biringer, B., Vugrin, E. and Warren, D., (2013). Critical infrastructure system security and resiliency. CRC press.
California. Seismic Safety Commission and ASCE-25 Task Committee on Earthquake Safety Issues for Gas Systems, (2002). Improving Natural Gas Safety in Earthquakes (No. 2). Seismic Safety Commission.
Cimellaro, G.P., Villa, O. and Bruneau, M., 2014. Resilience-based design of natural gas distribution networks. Journal of Infrastructure systems, 21(1), p.05014005.
da Silva Alves, F., de Souza, J.N.M. and Costa, A.L.H., (2016). Multi-objective design optimization of natural gas transmission networks. Computers & Chemical Engineering, 93, pp.212-220.
Emenike, S.N. and Falcone, G., (2020). A review on energy supply chain resilience through optimization. Renewable and Sustainable Energy Reviews, 134, p.110088.
Fan, M.W., Gong, J., Wu, Y. and Kong, W.H., (2017). The gas supply reliability analysis of natural gas pipeline network based on simplified topological structure. Journal of Renewable and Sustainable Energy, 9(4), p.045503.
Fasihizadeh, M., Sefti, M.V. and Torbati, H.M., (2014). Improving gas transmission networks operation using simulation algorithms: Case study of the National Iranian Gas Network. Journal of Natural Gas Science and Engineering, 20, pp.319-327.
Ghavamifar, A., Sabouhi, F. and Makui, A., (2018). An integrated model for designing a distribution network of products under facility and transportation link disruptions. Journal of Industrial and Systems Engineering, 11(1), pp.113-126.
Hamedi, M., Farahani, R.Z., Husseini, M.M. and Esmaeilian, G.R., (2009). A distribution-planning model for natural gas supply chain: A case study. Energy Policy, 37(3), pp.799-812.
Honegger, et al., “Improving Natural Gas Safety in Earthquakes”, Prepared by ASCE-25 Task Committee On Earthquake Safety Issues For Gas Systems, California Seismic Safety Commission, (2002).
Hosseini, S., Barker, K. and Ramirez-Marquez, J.E., (2016). A review of definitions and measures of system resilience. Reliability Engineering & System Safety, 145, pp.47-61.
Jo, Y.D. and Crowl, D.A., (2008). Individual risk analysis of high-pressure natural gas pipelines. Journal of Loss Prevention in the Process Industries, 21(6), pp.589-595.
Kashani, A.H.A. and Molaei, R., (2014). Techno-economical and environmental optimization of natural gas network operation. Chemical Engineering Research and Design, 92(11), pp.2106-2122.
Karmon, E., (2002). The risk of terrorism against oil and gas pipelines in Central Asia. The Oil and Gas Routed from Caspian-Caucasus Region: Geopolitics of Pipelines, Stability and International Security.
Li, X., Armagan, E., Tomasgard, A. and Barton, P.I., (2011). Stochastic pooling problem for natural gas production network design and operation under uncertainty. AIChE Journal, 57(8), pp.2120-2135.
Liang, Y., Zheng, J., Wang, B., Zheng, T. and Xu, N., (2020). Optimization Design of Natural Gas Pipeline Based on a Hybrid Intelligent Algorithm. In Recent Trends in Intelligent Computing, Communication and Devices (pp. 1015-1025). Springer, Singapore.
Liu, W., Li, Z., Song, Z. and Li, J., (2018). Seismic reliability evaluation of gas supply networks based on the probability density evolution method. Structural safety, 70, pp.21-34.
Liu, W. and Song, Z., (2020). Review of studies on the resilience of urban critical infrastructure networks. Reliability Engineering & System Safety, 193, p.106617.
Mavrotas, G., (2009). Effective implementation of the ε-constraint method in multi-objective mathematical programming problems. Applied mathematics and computation, 213(2), pp.455-465.
Misra, S., Fisher, M.W., Backhaus, S., Bent, R., Chertkov, M. and Pan, F., (2014). Optimal compression in natural gas networks: A geometric programming approach. IEEE transactions on control of network systems, 2(1), pp.47-56.
Omidvar, B. and Kivi, H.K., (2016). Multi-hazard failure probability analysis of gas pipelines for earthquake shaking, ground failure and fire following earthquake. Natural hazards, 82(1), pp.703-720.
Pishvaee, M.S. and Torabi, S.A., (2010). A possibilistic programming approach for closed-loop supply chain network design under uncertainty. Fuzzy sets and systems, 161(20), pp.2668-2683.
Pishvaee, M.S., Razmi, J. and Torabi, S.A., (2012). Robust possibilistic programming for socially responsible supply chain network design: A new approach. Fuzzy sets and systems, 206, pp.1-20.
Papageorgiou, L.G., (2009). Supply chain optimisation for the process industries: Advances and opportunities. Computers & Chemical Engineering, 33(12), pp.1931-1938.
Sabouhi, F. and Jabalameli, M.S., (2019). A stochastic bi-objective multi-product programming model to supply chain network design under disruption risks. Journal of Industrial and Systems Engineering, 12(3), pp.196-209.
Su, H., Zio, E., Zhang, J., Li, X., Chi, L., Fan, L. and Zhang, Z., (2019). A method for the multi-objective optimization of the operation of natural gas pipeline networks considering supply reliability and operation efficiency. Computers & Chemical Engineering, 131, p.106584.
Su, H., Zio, E., Zhang, J. and Li, X., (2018). A systematic framework of vulnerability analysis of a natural gas pipeline network. Reliability Engineering & System Safety, 175, pp.79-91.
Sesini, M., Giarola, S. and Hawkes, A.D., (2020). The impact of liquefied natural gas and storage on the EU natural gas infrastructure resilience. Energy, 209, p.118367.
Su, H., Zhang, J., Zio, E., Yang, N., Li, X. and Zhang, Z., (2018). An integrated systemic method for supply reliability assessment of natural gas pipeline networks. Applied Energy, 209, pp.489-501.
Tabatabaee, M., (2016). Resilience assessment of the natural gas supply system of the Country and Proposals to increase its Resiliency. The Center for Energy Technology Development, No. of research agreement: 193010.
Tsinidis, G., Di Sarno, L., Sextos, A. and Furtner, P., (2019). A critical review on the vulnerability assessment of natural gas pipelines subjected to seismic wave propagation. Part 1: Fragility relations and implemented seismic intensity measures. Tunnelling and Underground Space Technology, 86, pp.279-296.
Üster, H. and Dilavero─člu, ┼×., (2014). Optimization for design and operation of natural gas transmission networks. Applied Energy, 133, pp.56-69.
Yu, W., Gong, J., Song, S., Huang, W., Li, Y., Zhang, J., Hong, B., Zhang, Y., Wen, K. and Duan, X., (2019). Gas supply reliability analysis of a natural gas pipeline system considering the effects of underground gas storages. Applied Energy, 252, p.113418.
Zamanian, M.R., Sadeh, E., Sabegh, Z.A. and Rasi, R.E., (2020). A Multi-Objective Optimization Model for the Resilience and Sustainable Supply Chain: A Case Study. International Journal of Supply and Operations Management, 7(1), pp.51-75.
Zhang, H., Liang, Y., Liao, Q., Chen, J., Zhang, W., Long, Y. and Qian, C., (2019). Optimal design and operation for supply chain system of multi-state natural gas under uncertainties of demand and purchase price. Computers & Industrial Engineering, 131, pp.115-130.
Zhu, Y., Wang, P., Wang, Y., Tong, R., Yu, B. and Qu, Z., (2021). Assessment method for gas supply reliability of natural gas pipeline networks considering failure and repair. Journal of Natural Gas Science and Engineering, 88, p.103817.