Mathematical modelling of the process of natural gas transportation through pipeline networks to minimize fuel costs.

2023

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.22541/au.168087246.65008375/v1
Data confidence 70 medium
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Abstract

This research is one of the most relevant research carried out to solve the problems of natural gas transportation through pipeline networks. The increased demand for natural gas in Kazakhstan is associated with a greater level of environmental friendliness, as a result of which many power-generating stations use natural gas as the main source of energy. Modernization of existing thermal power plants is necessary to improve the environmental situation in the country. There are three main groups of gas pipeline systems in the literature, namely collection, transmission and distribution systems. In this article, we aim to present a detailed study and research of this process undertaken to optimize natural gas transmission lines and build new approaches to address such challenges. Of course, over the past few years, a huge amount of research has been conducted on many problems of decision-making in the gas industry and, in particular, on optimizing the pipeline network. In this paper we consider dynamical optimization models, highlighting aspects of modelling and the most relevant approaches to solving known as of the current date. Consequently, this research can serve as a useful tool for understanding the evolution of many real-world applications and the most recent advances in solution methodologies emerging in this exciting and complex field of research-decision problems. Gas pipelines are often operated in transient modes due to the time-varying needs of consumers for natural gas and gas supplies. For a certain period of operation of the gas pipeline with the specified gas parameters, depending on time, at the input and output points, pipeline dispatchers are faced with the task of optimizing the transition process in order to minimize fuel consumption at compressor stations in real-time. The results of the research can be used to develop technologies for automating calculations, planning and optimizing natural gas transportation.