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

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.