«Automation and Informatization of the fuel and energy complex»

Practical implementation of using neural network models for modeling complex large-scale gas transportation systems

UDC: 681.5:622.279
DOI: -

Authors:

¹ Gazprom, St. Petersburg, Russia
² NIIgazekonomika, Moscow, Russia

Keywords: systems analysis, gas transportation systems, neural network models

Annotation:

The authors of the article propose a developed and tested approach to modeling non-stationary modes of operation of complex gas transportation systems (GTS) using a combination of physical neural network models of gas transportation. The implementation of this methodology is based on three interconnected modules: a balance-coordinating module for calculating flow dynamics to ensure target balance indicators and gas reserves of large fragments; neural network module for calculating the operating parameters of a "large fragment"; hybrid module for operating modes of complex fragments based on a combination of traditional physical models and machine learning methods. The possibility of using these modules in the iterative process of modeling a gas transportation system is shown, taking into account the transfer of calculation results between individual software blocks.

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