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Value chain optimization in large scale gas network considering elevation and transmission direction.

Xifeng Ning1, Jinfeng Qiu2, Dejun Yu3

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This summary is machine-generated.

This study optimizes natural gas transmission in China's largest pipeline network. A new sequential linear programming algorithm efficiently solves complex operational problems, ensuring reliable energy delivery.

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Area of Science:

  • Engineering
  • Operations Research
  • Energy Systems

Background:

  • China's largest natural gas company manages an extensive pipeline network.
  • Seasonal demand fluctuations complicate gas transmission and network operations.
  • Accurate modeling of gas flow, including elevation, is crucial for efficient operations.

Purpose of the Study:

  • To develop an efficient algorithm for optimizing natural gas transmission in a large-scale network.
  • To address the complexities of non-linear, non-convex mixed-integer problems in gas pipeline operations.
  • To improve the operational basis for monthly gas transmission decisions.

Main Methods:

  • A modified Weymouth equation incorporating elevation was used to model gas flow.
  • A sequential linear programming algorithm was developed and applied.
  • The algorithm was tested on a real-world, large-scale Chinese natural gas network.

Main Results:

  • The proposed algorithm demonstrated efficiency in solving the large-scale optimization problem.
  • High-quality solutions were generated for the complex gas transmission operations.
  • The method provides a viable approach for operational planning in extensive pipeline networks.

Conclusions:

  • Sequential linear programming offers an effective solution for optimizing natural gas transmission.
  • The modified Weymouth equation accurately captures physical gas flow dynamics, including elevation.
  • The developed algorithm enhances operational efficiency and reliability for major energy companies.