A graph neural network (GNN) method for assigning gas calorific values to natural gas pipeline networks

Yang, Zhuqiang; Li, Zhe; Zhou, Jing; Song, Chaofan; Qi, Xiang; Qian, He; Hu, Jinqiu; Faber, Michael Havbro; Zio, Enrico; Li, Zhenlin; Su, Huai; Zhang, Jinjun

doi:10.1016/j.energy.2023.127875

Cited by 10 publications

(2 citation statements)

References 55 publications

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“…These algorithms can effectively analyze function resilience even in cases where pipeline network scheduling data are incomplete. Furthermore, the integration of complex network theory with pipeline network resilience facilitates the combination of NGPS resilience with Bayesian networks and deep learning algorithms [74,75], particularly graph neural networks [76]. This integration of machine learning and engineering system analysis, especially graph theory, has become a significant trend in the field.…”

Section: Complex Network Methodsmentioning

confidence: 99%

Resilience of Natural Gas Pipeline System: A Review and Outlook

Yang,

Xiang,

et al. 2023

Energies

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A natural gas pipeline system (NGPS), as a crucial energy transportation network, exhibits intricate systemic characteristics. Both uncertain disturbances and complex characteristics result in higher requirement of supply safety. The investigation into NGPS resilience addresses the constraints of pipeline integrity and reliability, centering around the vulnerability, robustness, and recovery of an NGPS. Based on a literature review and practical engineering insights, the generalized concept of NGPS resilience is elucidated. The research methodologies of NGPS resilience are classified into three types: indicator construction method, process analysis method, and complex networks method. The practical applications of NGPS resilience research are analyzed, which are based on NGPS operation safety, information safety, and market safety. The ongoing applications and detailed measures are also concluded, which can guide the researchers and engineers from NGPS resilience.

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Section: Complex Network Methodsmentioning

confidence: 99%

Resilience of Natural Gas Pipeline System: A Review and Outlook

Yang,

Xiang,

et al. 2023

Energies

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“…Ulbig and Hoburg (2002) propose that the determination of the calorific value of natural gas is economically important in gas supply and describe different methods of calorific value determination. Yang et al, 2023 propose a graph neural network based calorific value metering method for natural gas. Motalo and Motalo (2021) propose an accuracy estimation method for measuring the gross and net specific calorific value of natural gas by calorimetry.…”

Section: Relevant Literaturementioning

confidence: 99%

A study of operational decisions of city gas operators under the energy metering and pricing model

Wan,

Sun,

Wen

et al. 2024

Front. Energy Res.

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This study examines the quantitative conditions under which an energy metering pricing model is proposed to increase both gas merchant profits and gas customer consumer surplus compared to a volumetric pricing model. The quantitative condition is found to be related to factors such as the standard unit calorific value of natural gas prescribed by the National Development and Reform Commission (NDRC) and other relevant government departments under the energy metering pricing model. This paper establishes a mathematical model based on optimization theory to explore the operational decisions of city gas suppliers in the volumetric and energy metering and pricing modes, respectively, under the condition of relatively stable natural gas sales price. The results of the study show that DAC and other authorities can regulate the standard unit calorific value of natural gas under the energy metering and pricing model by regulating the standard unit calorific value of natural gas. This affects the incentives of gas dealers to produce and operate, guides the preference of gas users for natural gas energy metering and pricing, and results in the derivation of formulas for a reasonable range of standard unit calorific values for natural gas. The findings of this paper provide theoretical support to promote the reform of natural gas energy measurement and pricing, and contribute to the development of the natural gas industry.

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