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Poster Année : 2023

Probabilistic simulation model of resilience assessment of natural gas pipeline systems

Zhaoming Yang
  • Fonction : Auteur
Qi Xiang
  • Fonction : Auteur
Qian He
  • Fonction : Auteur
Michael Havbro Faber
  • Fonction : Auteur
Huai Su
  • Fonction : Auteur
Jinjun Zhang
  • Fonction : Auteur

Résumé

Abstract The study for the natural gas pipeline system (NGPS), particularly about the resilience evaluation, is still in its early stages. Resilience is a hot point in the most important aspects of system security assessment. An integrated simulation model is presented for assessing the gas supply of NGPS, incorporating the topological and operational circumstances. This model takes different forms of disruptions into consideration. Analysis is done on the properties of probabilistic disturbances. The novel ideas include the global resilience and temporal resilience as the indicators for evaluating resilience. By integrating the maximum flow algorithm and the shortest path algorithm with operational and structural parameters, the gas supply volume and routes were determined before and after system disturbances. Based on the theories of complex network and graph theory, researchers have moved the traditional viewpoint from the entire system to the affected regions. The use of simulation models in research can facilitate the development of pre-warning for natural gas supply systems (NGPS), including optimization of gas supply amount and supply routes arrangement, as well as formulation of pipeline maintenance strategies. In addition, simulation models can also support the rapid analysis of disturbance results, thus improving the accuracy of resilience evaluation for NGPS.

Dates et versions

hal-04409057 , version 1 (22-01-2024)

Identifiants

Citer

Zhaoming Yang, Qi Xiang, Qian He, Enrico Zio, Michael Havbro Faber, et al.. Probabilistic simulation model of resilience assessment of natural gas pipeline systems. International Conference on Computer Technology and Information Science (CTIS 2023), Jun 2023, Wuhan, China. 2595 (1), pp.012014, 2023, ⟨10.1088/1742-6596/2595/1/012014⟩. ⟨hal-04409057⟩
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