Maksym'yuk S.O. Improvement of information and measuring systems of quality and transportation of energy resources on the basis of their energy value. – Qualification scientific work in the form of a manuscript.
Dissertation for the degree of Doctor of Philosophy in specialty 152 – metrology and information and measuring equipment. – Ivano-Frankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, 2024.
The object of research is the process of determining the energy value of natural gas in branched low-pressure gas networks.
The subject of research is methods for assessing the energy value of gas during transportation in the gas distribution system, based on modern information and measuring technologies, an express method for gas quality control, as well as the influence of hydrogen and biomethane impurities on the functional parameters of the network.
The dissertation solves a scientific and practical problem related to the improvement of information and measurement systems for determining the quality of energy resources in gas distribution networks with two sources of gas supply by developing new mathematical models taking into account the impact of injected biomethane and hydrogen into the gas pipeline.
The introduction substantiates the relevance of the research tasks, presents the scientific novelty and formulates the practical significance of the results obtained.
The first section provides a systematic analysis of modern approaches to quality control and transportation of natural gas, justifies the transition to energy units of accounting and the relevance of studying the relationship between the qualitative characteristics of gas and network parameters for the integration of new energy carriers.
The second section of the dissertation develops a methodology for assessing the higher calorific value of natural gas in branched networks with two inputs, which takes into account the volume fractions of flows and the physicochemical parameters of gas. A mathematical model based on multivariate regression analysis was proposed and its high accuracy with an error of 0.24% was confirmed. An algorithm for the functioning of an information and measuring system for gas quality control was developed, which includes integration with dispatching systems, and the use of artificial neural networks was also proposed to increase the accuracy of forecasts. The model was adapted to take into account the influence of hydrogen, which provided an average error of 0.31%, confirming its suitability for forecasting mixed gases.
In the third section, the influence of natural gas quality on the parameters of gas transmission networks was investigated. The modeling showed that a decrease in calorific value by 4.5% increases gas consumption and reduces reserves in storage facilities. The method for assessing the technical condition of low-pressure gas pipelines was improved, in which, unlike existing ones, a new informative parameter of the change in the calorific value of gas was applied, which allows predicting the formation of corrosion damage to the low-pressure pipeline.
In the fourth section, the energy value of biogas, the influence of its components on the characteristics of gas mixtures, and the model for estimating the heat of combustion for the integration of biomethane into gas pipelines were studied. Biogas purification technologies, biomethane quality requirements according to standards, and the influence of oxygen on the energy performance of gas were analyzed. A neural network was developed to predict the heat of combustion of natural gas in networks with two inputs, taking into account the presence of natural gas, hydrogen, and biomethane in the gas pipeline, which ensured high accuracy of the results (R ≥ 0.996). As part of the testing of the results, drafts of two national standards were created: DSTU EN 16723-1:2023 for the integration of biomethane into the gas transportation system and DSTU EN 12007-4:2019 for the modernization of gas networks up to 16 bar with an emphasis on safety and reliability. Keywords: natural gas, mathematical model, measurement error, measurement result, neural networks, diagnostic features, energy parameters, decarbonization, hydrogen, gas-hydrogen mixtures, solid household waste, component composition, biogas, statistical evaluations, hydrocarbon transportation.
