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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. 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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