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Two-stage optimization model for scheduling multiproduct pipeline network with multi-source and multi-terminal

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  • Li, Zhuochao
  • Guo, Yi
  • Wang, Bohong
  • Yan, Yamin
  • Liang, Yongtu
  • Mikulčić, Hrvoje

Abstract

The multiproduct pipeline network with multi-source and multi-terminal encompasses multi-point injection and multi-point distribution. Upon reorganization of batches at transfer depots, the intricacies of precise batch tracking become increasingly complex, thereby rendering the optimization of multiproduct pipeline network scheduling particularly arduous. In this paper, we introduce a dynamic index batch numbering method. By delineating the boundaries of intermediate injection points, the issue is bifurcated into two sub-problems: the optimization of batch planning for multiproduct pipeline with single-source and multi-terminal and the optimization of resource allocation at intermediate oil depots. The proposed algorithm is validated on two genuine multiproduct pipeline networks in China, demonstrating its capability to generate feasible solutions within a computational constraint of 18,000 CPU seconds. The findings reveal that this methodology holistically considers the entire pipeline network system, encompassing upstream oil intake, downstream oil supply, and the tank capacities of transfer depots, thereby establishing a coherent link between pipeline scheduling and depot planning. This paper may serve as a reference for the automated formulation of multiproduct pipeline network scheduling strategies.

Suggested Citation

  • Li, Zhuochao & Guo, Yi & Wang, Bohong & Yan, Yamin & Liang, Yongtu & Mikulčić, Hrvoje, 2024. "Two-stage optimization model for scheduling multiproduct pipeline network with multi-source and multi-terminal," Energy, Elsevier, vol. 306(C).
    • Handle: RePEc:eee:energy:v:306:y:2024:i:c:s0360544224022850
    DOI: 10.1016/j.energy.2024.132511
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    References listed on IDEAS

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    1. Du, Jian & Zheng, Jianqin & Liang, Yongtu & Xia, Yuheng & Wang, Bohong & Shao, Qi & Liao, Qi & Tu, Renfu & Xu, Bin & Xu, Ning, 2023. "Deeppipe: An intelligent framework for predicting mixed oil concentration in multi-product pipeline," Energy, Elsevier, vol. 282(C).
    2. Wei, Qi & Zhou, Peng & Shi, Xunpeng, 2023. "The congestion cost of pipeline networks under third-party access in China's natural gas market," Energy, Elsevier, vol. 284(C).
    3. Chen, Haihong & Zuo, Lili & Wu, Changchun & Li, Qingping, 2019. "An MILP formulation for optimizing detailed schedules of a multiproduct pipeline network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 123(C), pages 142-164.
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