IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v215y2021ipas0360544220322386.html
   My bibliography  Save this article

A transient composition tracking method for natural gas pipe networks

Author

Listed:
  • Fan, Di
  • Gong, Jing
  • Zhang, Shengnan
  • Shi, Guoyun
  • Kang, Qi
  • Xiao, Yaqi
  • Wu, Changchun

Abstract

A transient composition tracking method is developed for natural gas pipe networks. It adopts the control volume method for hydraulic simulation and a one-dimensional unsteady heat transfer model for thermal simulation. In order to model the junction in the network, a special grid is proposed to connect all adjacent pipes together. Under this grid, the momentum equation could be discretized by the first-order upwind scheme while the mass equation could be discretized just like an ordinary pipe node. To track the composition, the advective concentration equation is given for each component. Therefore, the gas composition in the pipe network could be predicted in real time and its influence on the calculation of property parameters could be taken into consideration. Based on these models, a transient composition tracking algorithm is developed for natural gas pipe networks. It consists of three parts: transient flow simulation, composition tracking and parameters calculation. Case studies show that the proposed method can provide reliable results for transient flow simulation. Compared with the measured data, the composition outcomes given by this method are also very accurate. In addition, the impact of injecting LNG/H2 into the pipe network is quite complicated and should be treated with caution.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:energy:v:215:y:2021:i:pa:s0360544220322386
    DOI: 10.1016/j.energy.2020.119131
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544220322386
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2020.119131?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hong, Bingyuan & Li, Xiaoping & Song, Shangfei & Chen, Shilin & Zhao, Changlong & Gong, Jing, 2020. "Optimal planning and modular infrastructure dynamic allocation for shale gas production," Applied Energy, Elsevier, vol. 261(C).
    2. Yu, Weichao & Song, Shangfei & Li, Yichen & Min, Yuan & Huang, Weihe & Wen, Kai & Gong, Jing, 2018. "Gas supply reliability assessment of natural gas transmission pipeline systems," Energy, Elsevier, vol. 162(C), pages 853-870.
    3. Guandalini, Giulio & Colbertaldo, Paolo & Campanari, Stefano, 2017. "Dynamic modeling of natural gas quality within transport pipelines in presence of hydrogen injections," Applied Energy, Elsevier, vol. 185(P2), pages 1712-1723.
    4. Guandalini, Giulio & Campanari, Stefano & Romano, Matteo C., 2015. "Power-to-gas plants and gas turbines for improved wind energy dispatchability: Energy and economic assessment," Applied Energy, Elsevier, vol. 147(C), pages 117-130.
    5. Chaczykowski, Maciej & Zarodkiewicz, Paweł, 2017. "Simulation of natural gas quality distribution for pipeline systems," Energy, Elsevier, vol. 134(C), pages 681-698.
    6. Mikolajková, Markéta & Haikarainen, Carl & Saxén, Henrik & Pettersson, Frank, 2017. "Optimization of a natural gas distribution network with potential future extensions," Energy, Elsevier, vol. 125(C), pages 848-859.
    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. 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).
    2. 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).
    3. 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.
    4. 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).
    5. 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).
    6. 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).
    7. 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).
    8. Bermúdez, Alfredo & Shabani, Mohsen, 2022. "Numerical simulation of gas composition tracking in a gas transportation network," Energy, Elsevier, vol. 247(C).
    9. 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).
    10. 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.
    11. Qi, Shikun & Zhao, Wei & Qiu, Rui & Liu, Chunying & Li, Zhuochao & Lan, Hao & Liang, Yongtu, 2023. "Capacity allocation method of hydrogen-blending natural gas pipeline network based on bilevel optimization," Energy, Elsevier, vol. 285(C).
    12. 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.

    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. Szoplik, Jolanta & Stelmasińska, Paulina, 2019. "Analysis of gas network storage capacity for alternative fuels in Poland," Energy, Elsevier, vol. 172(C), pages 343-353.
    2. Danieli, Piero & Lazzaretto, Andrea & Al-Zaili, Jafar & Sayma, Abdulnaser & Masi, Massimo & Carraro, Gianluca, 2022. "The potential of the natural gas grid to accommodate hydrogen as an energy vector in transition towards a fully renewable energy system," Applied Energy, Elsevier, vol. 313(C).
    3. Bermúdez, Alfredo & Shabani, Mohsen, 2022. "Numerical simulation of gas composition tracking in a gas transportation network," Energy, Elsevier, vol. 247(C).
    4. Kolb, Sebastian & Plankenbühler, Thomas & Frank, Jonas & Dettelbacher, Johannes & Ludwig, Ralf & Karl, Jürgen & Dillig, Marius, 2021. "Scenarios for the integration of renewable gases into the German natural gas market – A simulation-based optimisation approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    5. Farrokhifar, Meisam & Nie, Yinghui & Pozo, David, 2020. "Energy systems planning: A survey on models for integrated power and natural gas networks coordination," Applied Energy, Elsevier, vol. 262(C).
    6. 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.
    7. Kouchachvili, Lia & Entchev, Evgueniy, 2018. "Power to gas and H2/NG blend in SMART energy networks concept," Renewable Energy, Elsevier, vol. 125(C), pages 456-464.
    8. 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).
    9. Hong, Bingyuan & Du, Zhaonan & Qiao, Dan & Liu, Daiwei & Li, Yu & Sun, Xiaoqing & Gong, Jing & Zhang, Hongyu & Li, Xiaoping, 2024. "Sustainable supply chain of distributed multi-product gas fields based on skid-mounted equipment to dynamically respond to upstream and market fluctuations," Energy, Elsevier, vol. 292(C).
    10. 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).
    11. Il Hong Min & Seong-Gil Kang & Cheol Huh, 2018. "Instability Analysis of Supercritical CO 2 during Transportation and Injection in Carbon Capture and Storage Systems," Energies, MDPI, vol. 11(8), pages 1-19, August.
    12. Wen, Kai & Lu, Yangfan & Lu, Meitong & Zhang, Wenwei & Zhu, Ming & Qiao, Dan & Meng, Fanpeng & Zhang, Jing & Gong, Jing & Hong, Bingyuan, 2022. "Multi-period optimal infrastructure planning of natural gas pipeline network system integrating flowrate allocation," Energy, Elsevier, vol. 257(C).
    13. Cavana, Marco & Mazza, Andrea & Chicco, Gianfranco & Leone, Pierluigi, 2021. "Electrical and gas networks coupling through hydrogen blending under increasing distributed photovoltaic generation," Applied Energy, Elsevier, vol. 290(C).
    14. Chaczykowski, Maciej & Zarodkiewicz, Paweł, 2017. "Simulation of natural gas quality distribution for pipeline systems," Energy, Elsevier, vol. 134(C), pages 681-698.
    15. Emmanuel Ogbe & Ali Almansoori & Michael Fowler & Ali Elkamel, 2023. "Optimizing Renewable Injection in Integrated Natural Gas Pipeline Networks Using a Multi-Period Programming Approach," Energies, MDPI, vol. 16(6), pages 1-24, March.
    16. Saedi, Isam & Mhanna, Sleiman & Mancarella, Pierluigi, 2021. "Integrated electricity and gas system modelling with hydrogen injections and gas composition tracking," Applied Energy, Elsevier, vol. 303(C).
    17. Zhu, Jianhua & Peng, Yan & Gong, Zhuping & Sun, Yanming & Lai, Chaoan & Wang, Qing & Zhu, Xiaojun & Gan, Zhongxue, 2019. "Dynamic analysis of SNG and PNG supply: The stability and robustness view #," Energy, Elsevier, vol. 185(C), pages 717-729.
    18. Pellegrino, Sandro & Lanzini, Andrea & Leone, Pierluigi, 2017. "Greening the gas network – The need for modelling the distributed injection of alternative fuels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 266-286.
    19. Zhaoming Yang & Qi Xiang & Yuxuan He & Shiliang Peng & Michael Havbro Faber & Enrico Zio & Lili Zuo & Huai Su & Jinjun Zhang, 2023. "Resilience of Natural Gas Pipeline System: A Review and Outlook," Energies, MDPI, vol. 16(17), pages 1-19, August.
    20. Xuejie Li & Yuan Xue & Yuxing Li & Qingshan Feng, 2022. "An Optimization Method for a Compressor Standby Scheme Based on Reliability Analysis," Energies, MDPI, vol. 15(21), pages 1-16, November.

    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:eee:energy:v:215:y:2021:i:pa:s0360544220322386. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.