چكيده به لاتين
Abstract:
Today, energy is one of the most important pillars of the economic cycle of different countries and natural gas as one of the most important energy carriers occupies 70% of the country's energy supply basket.
The transfer of natural gas from the place of production to the places of consumption is done by transmission and distribution networks. The city gas distribution networks, as one of the important urban infrastructures, are responsible for distributing gas to domestic, commercial and industrial consumers. The level of consumers, especially in the cold seasons, is essential and vital and plays an important role in economic growth and social welfare of society, so increasing the resilience of these networks in order to minimize the impact of disruptive factors is very important.
In the present study, after an in-depth review of the literature and determining the appropriate conditions and methods for simulating this network and appropriate metrics to determine the resilience of the gas distribution network in graph theory, information about network topology, node consumption and number of consuming units (node weight) Was collected, and extracted by simulation with Gp Net software, network topology structure and critical points, by adding the number of consumer units (as weight), a list of proximity was prepared and then with Python software and Network X library. The values of the metrics were calculated from the simulated reports.
According to the results of simulation and metrics calculations, the state of network resilience is determined, Network sensitivity analysis to add links is one of the things that is done after determining the network structure and in different stages. In the next step, the vulnerability of the network to the failure of each node or link, taking into account the hydraulic analysis, topological structure and cascading properties in the failures, is investigated simultaneously reviewed and by an algorithm ranking nodes and links.In other words, at each stage, the removal of a node or link, determines the network status based on re-hydraulic analysis and pressure control obtained with standard pressure, and based on the new network status, the effect of removing each node or link on the network services calculated.
Finally, by predicting the consumption of nodes in the five-year horizon by ARIMA time series models and Eviews Softwar, the status of critical points and network resilience in the next five years is determined and the solution to improve its status in this time horizon is presented
