Gas transmission capability curve of natural gas pipeline system

被引：0
|
作者：
Song C. [1 ]
Xiao J. [1 ]
Chen Q. [2 ]
Qu Y. [1 ]
Qiu Z. [1 ]
Li H. [3 ]
机构：
[1] Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin
[2] School of Mechanical and Storage and Transportation Engineering, China University of Petroleum(Beijing), Beijing
[3] Suzhou Operation and Maintenance Station, Maintenance Branch of State Grid Jiangsu Electric Power Company Limited, Suzhou
来源：
Zhongguo Shiyou Daxue Xuebao (Ziran Kexue Ban)/Journal of China University of Petroleum (Edition of Natural Science) | 2022年 / 46卷 / 02期
关键词：
Gas transmission capability; Gas transmission capability curve; Gas transmission security; Natural gas pipeline network system; Transmission capability limit;
D O I：
10.3969/j.issn.1673-5005.2022.02.017
中图分类号：
学科分类号：
摘要：
The gas transmission capability (GTC) is a key index for the natural gas pipeline system, which is used to describe the transmission capability limit of the system. There exists the GTC curve in the natural gas pipeline system, which can describe the transmission capability limit of the system more completely. The operating point and the security of natural gas transmission were defined, and the mathematical model of GTC was presented meanwhile. Then, the definition, model, indices and plotting method of the GTC curve were proposed. A small-scale natural gas pipeline network and large-scale natural gas pipeline network (Belgium system) were used to verify the proposed methods. The method in this paper was compared with the traditional method, and the theoretical value and application prospect of GTC curve were discussed further. The results show that GTC is just the maximum point on the curve. The critically secure state of GTC may not be unique, and there exist many critically secure states whose gas transmission volumes are less than GTC. The GTC curve can reflect the gas transmission limit of the system under different load distributions, which is beneficial to better understand the range of transmission limit of natural gas pipeline system, and to guide the planning and operation. © 2022, Editorial Office of Journal of China University of Petroleum(Edition of Natural Science). All right reserved.
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页码：160 / 167
页数：7
相关论文
共 21 条
  • [1] LI Yang, LIAN Peiqing, XUE Zhaojie, Et al., Application status and prospect of big data and artificial intelligence in oil and gas field development, Journal of China University of Petroleum (Edition of Natural Science), 44, 4, pp. 1-11, (2020)
  • [2] ZHANG Jinjun, SU Huai, GAO Peng, Resilience-based supply assurance of natural gas pipeline networks and its research prospects [J], Acta Petrolei Sinica, 41, 12, pp. 1665-1678, (2020)
  • [3] HUANG Weihe, Reliability of large-scale natural gas pipeline network, Acta Petrolei Sinica, 34, 2, pp. 401-404, (2013)
  • [4] OLORUNNIWO O., PAUL A J., Optimal capacity expansion for natural gas transmission networks-a decomposition approach [J], Engineering Optimization, 6, 1, pp. 13-30, (1982)
  • [5] YANG Yi, LI Changjun, SHANG Shuya, Study on gas transmission and distribution optimization of pipeline system, Natural Gas Industry, 26, 1, pp. 123-125, (2006)
  • [6] YANG Yi, LI Changjun, Application of algorithms in optimal operation of natural gas pipeline network, Journal of Southwest Petroleum Institute, 28, 1, pp. 79-82, (2006)
  • [7] THORSTEN K, BENJAMIN H, MARC E, Et al., Evaluating gas network capacities, pp. 65-84, (2015)
  • [8] CLAUDEMIR D V, SERGIO R L, ANTONIO C G, Et al., Network flows modeling applied to the natural gas pipeline in Brazil [J], Journal of Natural Gas Science & Engineering, 14, 14, pp. 211-224, (2013)
  • [9] HUANG Yanfei, WU Changchun, CHEN Qian, Et al., A computation model for gas supply reliability analysis in a gas pipeline network based upon the uncertainty of gas consumption, Natural Gas Industry, 38, 8, pp. 126-133, (2018)
  • [10] BENJAMIN H, THORSTEN K, LARS S, Et al., A system to evaluate gas network capacities: concepts and implementation [J], European Journal of Operational Research, 270, pp. 797-808, (2018)
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