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A framework of smart pipeline system and its application on multiproduct pipeline leakage handling

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  • He, Guoxi
  • Li, Yansong
  • Huang, Yuanjie
  • Sun, Liying
  • Liao, Kexi

Abstract

The management system is essential to ensure the smooth operation of the long-distance pipeline. Here, a framework of a smart pipeline system and its application on multiproduct pipeline network are proposed where a pipeline monitoring and accidental leak handling system based on real-time Big Data and Distributed Computing for integrity management is introduced. A novel construction of data-chain and module-chain in the management of pipeline integrity is given. New computational modules for locating a leak, calculating leakage volume and executing shutdown procedure are proposed for emergency treatment. A new optimal model aiming at minimal ALV (accumulative leakage volume) is established to obtain a pipeline shutdown scheme. Several experiments relying on multiproduct pipelines are implemented to test the effectiveness of the framework and evaluate the applicability of the modules. The results demonstrate that the estimations of the starting time, location, coefficient, and leakage volume could be fulfilled within the duration of a negative pressure wave going through the selected pipeline. Meanwhile, the pre-forming of the pipeline shutdown procedure as well as obtaining the ALV could be achieved. The outcomes could provide guidance for the construction of smart pipeline network, pipeline shutdown management, prediction of leakage influential range and subsequent incident investigations.

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  • He, Guoxi & Li, Yansong & Huang, Yuanjie & Sun, Liying & Liao, Kexi, 2019. "A framework of smart pipeline system and its application on multiproduct pipeline leakage handling," Energy, Elsevier, vol. 188(C).
    • Handle: RePEc:eee:energy:v:188:y:2019:i:c:s0360544219317256
    DOI: 10.1016/j.energy.2019.116031
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    References listed on IDEAS

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    1. Li, Kang & Zhou, Xuejin & Tu, Ran & Xie, Qiyuan & Jiang, Xi, 2014. "The flow and heat transfer characteristics of supercritical CO2 leakage from a pipeline," Energy, Elsevier, vol. 71(C), pages 665-672.
    2. Gangolells, Marta & Casals, Miquel & Forcada, Núria & Macarulla, Marcel & Giretti, Alberto, 2015. "Environmental impacts related to the commissioning and usage phase of an intelligent energy management system," Applied Energy, Elsevier, vol. 138(C), pages 216-223.
    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. Tylman, Wojciech & Kolczyński, Jakub & Anders, George J., 2010. "Fully automatic AI-based leak detection system," Energy, Elsevier, vol. 35(9), pages 3838-3848.
    5. Wang, Yaran & You, Shijun & Zhang, Huan & Zheng, Xuejing & Zheng, Wandong & Miao, Qingwei & Lu, Gang, 2017. "Thermal transient prediction of district heating pipeline: Optimal selection of the time and spatial steps for fast and accurate calculation," Applied Energy, Elsevier, vol. 206(C), pages 900-910.
    6. Wang, Hai & Wang, Haiying & Zhu, Tong & Deng, Wanli, 2017. "A novel model for steam transportation considering drainage loss in pipeline networks," Applied Energy, Elsevier, vol. 188(C), pages 178-189.
    7. Yang, Zhao & Xiong, Zhuang & Shao, Min, 2010. "A new method of leak location for the natural gas pipeline based on wavelet analysis," Energy, Elsevier, vol. 35(9), pages 3814-3820.
    8. Xie, Qiyuan & Tu, Ran & Jiang, Xi & Li, Kang & Zhou, Xuejin, 2014. "The leakage behavior of supercritical CO2 flow in an experimental pipeline system," Applied Energy, Elsevier, vol. 130(C), pages 574-580.
    9. Casals, Miquel & Gangolells, Marta & Forcada, Núria & Macarulla, Marcel & Giretti, Alberto & Vaccarini, Massimo, 2016. "SEAM4US: An intelligent energy management system for underground stations," Applied Energy, Elsevier, vol. 166(C), pages 150-164.
    10. Rimkevicius, Sigitas & Kaliatka, Algirdas & Valincius, Mindaugas & Dundulis, Gintautas & Janulionis, Remigijus & Grybenas, Albertas & Zutautaite, Inga, 2012. "Development of approach for reliability assessment of pipeline network systems," Applied Energy, Elsevier, vol. 94(C), pages 22-33.
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    1. Wang, Chang & Zheng, Jianqin & Liang, Yongtu & Wang, Bohong & Klemeš, Jiří Jaromír & Zhu, Zhu & Liao, Qi, 2022. "Deeppipe: An intelligent monitoring framework for operating condition of multi-product pipelines," Energy, Elsevier, vol. 261(PB).

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