IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i14p4961-d857305.html
   My bibliography  Save this article

Improved Adaptive Time Step Method for Natural Gas Pipeline Transient Simulation

Author

Listed:
  • Qiao Guo

    (College of Petroleum Engineering, Xi’an Shiyou University, Xi’an 710312, China)

  • Yuan Liu

    (College of Petroleum Engineering, Xi’an Shiyou University, Xi’an 710312, China)

  • Yunbo Yang

    (Petrochina Changqing Oilfield Changbei Operation Company, Xi’an 710018, China)

  • Tao Song

    (Changqing Oilfield Second Oil Transportation Office, Xianyang 712000, China)

  • Shouxi Wang

    (College of Petroleum Engineering, Xi’an Shiyou University, Xi’an 710312, China)

Abstract

As the natural gas pipeline network becomes larger and more complicated, a stricter requirement of computation efficiency for the large and complicated network transient simulation should be proposed. The adaptive time step method has been widely used in the transient simulation of natural gas pipeline networks as a significant way to improve computation efficiency. However, the trial calculation process, which is the most time-consuming process in time step adjustment, was used to adjust the time step in these methods, reducing the efficiency of time step adjustment. In order to reduce the number of trial calculations, and improve the calculation efficiency, an improved adaptive time step method is proposed, which proposes the concept of energy number and judges the energy number of the boundary conditions after judging whether the variation of the pipeline state is tolerable. A comparison between the adaptive time step method and the improved adaptive time step method in the restart process of natural gas pipelines and an actual operation of the XB section in China shows the accuracy, effect, and efficiency of the improved adaptive time step method. The results show that with the same accuracy, 27% fewer trial calculation processes and 24.95% fewer time levels are needed in the improved time step method.

Suggested Citation

  • Qiao Guo & Yuan Liu & Yunbo Yang & Tao Song & Shouxi Wang, 2022. "Improved Adaptive Time Step Method for Natural Gas Pipeline Transient Simulation," Energies, MDPI, vol. 15(14), pages 1-14, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:14:p:4961-:d:857305
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/14/4961/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/14/4961/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fan, Di & Gong, Jing & Zhang, Shengnan & Shi, Guoyun & Kang, Qi & Xiao, Yaqi & Wu, Changchun, 2021. "A transient composition tracking method for natural gas pipe networks," Energy, Elsevier, vol. 215(PA).
    2. Vasyl Zapukhliak & Lyubomyr Poberezhny & Pavlo Maruschak & Volodymyr Grudz Jr. & Roman Stasiuk & Janette Brezinová & Anna Guzanová, 2019. "Mathematical Modeling of Unsteady Gas Transmission System Operating Conditions under Insufficient Loading," Energies, MDPI, vol. 12(7), pages 1-14, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Vadim Fetisov & Aleksey V. Shalygin & Svetlana A. Modestova & Vladimir K. Tyan & Changjin Shao, 2022. "Development of a Numerical Method for Calculating a Gas Supply System during a Period of Change in Thermal Loads," Energies, MDPI, vol. 16(1), pages 1-16, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kai Wen & Hailong Xu & Wei Qi & Haichuan Li & Yichen Li & Bingyuan Hong, 2023. "Heat Transfer Model of Natural Gas Pipeline Based on Data Feature Extraction and First Principle Models," Energies, MDPI, vol. 16(3), pages 1-21, January.
    2. Jiawei Zhang & Lin Li & Qizhi Zhang & Yanbin Wu, 2022. "Optimization of Load Sharing in Compressor Station Based on Improved Salp Swarm Algorithm," Energies, MDPI, vol. 15(15), pages 1-18, August.
    3. Vadim Fetisov & Aleksey V. Shalygin & Svetlana A. Modestova & Vladimir K. Tyan & Changjin Shao, 2022. "Development of a Numerical Method for Calculating a Gas Supply System during a Period of Change in Thermal Loads," Energies, MDPI, vol. 16(1), pages 1-16, December.
    4. Wen, Kai & Jiao, Jianfeng & Zhao, Kang & Yin, Xiong & Liu, Yuan & Gong, Jing & Li, Cuicui & Hong, Bingyuan, 2023. "Rapid transient operation control method of natural gas pipeline networks based on user demand prediction," Energy, Elsevier, vol. 264(C).
    5. Li, Xiaoping & Yang, Qi & Xie, Xugang & Chen, Sihang & Pan, Chen & He, Zhouying & Gong, Jing & Hong, Bingyuan, 2023. "Spatiotemporal simulation of gas-liquid transport in the production process of continuous undulating pipelines," Energy, Elsevier, vol. 278(PA).
    6. Zhou, Dengji & Jia, Xingyun & Ma, Shixi & Shao, Tiemin & Huang, Dawen & Hao, Jiarui & Li, Taotao, 2022. "Dynamic simulation of natural gas pipeline network based on interpretable machine learning model," Energy, Elsevier, vol. 253(C).
    7. Dancker, Jonte & Wolter, Martin, 2022. "A coupled transient gas flow calculation with a simultaneous calorific-value-gradient improved hydrogen tracking," Applied Energy, Elsevier, vol. 316(C).
    8. Mehrdad Massoudi, 2020. "Mathematical Modeling of Fluid Flow and Heat Transfer in Petroleum Industries and Geothermal Applications," Energies, MDPI, vol. 13(6), pages 1-4, March.
    9. Koo, Bonchan & Chang, Seungjoon & Kwon, Hweeung, 2023. "Digital twin for natural gas infrastructure operation and management via streaming dynamic mode decomposition with control," Energy, Elsevier, vol. 274(C).
    10. Hong, Bingyuan & Li, Xiaoping & Li, Yu & Chen, Shilin & Tan, Yao & Fan, Di & Song, Shangfei & Zhu, Baikang & Gong, Jing, 2022. "An improved hydraulic model of gathering pipeline network integrating pressure-exchange ejector," Energy, Elsevier, vol. 260(C).
    11. Bermúdez, Alfredo & Shabani, Mohsen, 2022. "Numerical simulation of gas composition tracking in a gas transportation network," Energy, Elsevier, vol. 247(C).
    12. Yin, Xiong & Wen, Kai & Huang, Weihe & Luo, Yinwei & Ding, Yi & Gong, Jing & Gao, Jianfeng & Hong, Bingyuan, 2023. "A high-accuracy online transient simulation framework of natural gas pipeline network by integrating physics-based and data-driven methods," Applied Energy, Elsevier, vol. 333(C).
    13. Weichao Yu & Xianbin Zheng & Weihe Huang & Qingwen Cai & Jie Guo & Jili Xu & Yang Liu & Jing Gong & Hong Yang, 2022. "A Data-Driven Methodology for the Reliability Analysis of the Natural Gas Compressor Unit Considering Multiple Failure Modes," Energies, MDPI, vol. 15(10), pages 1-18, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:14:p:4961-:d:857305. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.