Natural gas pipeline network flow scheduling method, device and equipment

By constructing a natural gas pipeline network model and performing linearization and optimization, the problems of modeling complexity and transportation costs that cannot be considered in large-scale natural gas pipeline network flow direction scheduling are solved, and efficient and accurate flow scheduling is achieved.

CN122154114APending Publication Date: 2026-06-05CHINA UNIV OF PETROLEUM (BEIJING)
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
CHINA UNIV OF PETROLEUM (BEIJING)
Filing Date
2026-01-29
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

Existing technologies suffer from low accuracy and efficiency when dealing with large-scale, multi-cycle, multi-source, and multi-user natural gas pipeline flow direction scheduling, due to complex modeling, inability to consider transportation costs, and low precision.

Method used

By acquiring the physical structure data of the natural gas pipeline network, a natural gas pipeline network model is constructed, including the main source point, stations, gas source points, distribution points, gas storage facilities, and main sink points. The main source point and main sink point are introduced, and the problem is transformed into a single-source, single-sink minimum cost maximum flow problem. Combining graph theory modeling and MILP optimization, considering pipeline network constraints, linearization processing and optimization solutions are performed.

Benefits of technology

It improves computing efficiency and reliability, enabling more accurate and reliable scheduling of natural gas pipeline flow direction, adapting to large-scale, multi-cycle, multi-gas-source, and multi-user scenarios, and providing more precise scheduling data.

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Abstract

The application discloses a natural gas pipeline network flow scheduling method, device and equipment, wherein the method comprises the following steps: acquiring physical structure data of a natural gas pipeline network; processing and converting the physical structure data to obtain a natural gas pipeline network model; constructing a natural gas pipeline network scheduling model comprising a first target function, a second target function and pipeline network constraint conditions based on the natural gas pipeline network model, wherein the first target function takes the maximum gas supply of the natural gas pipeline network as a target, and the second target function takes the minimum transportation cost under the maximum gas supply as a target; performing linearization processing on the natural gas pipeline network scheduling model, and performing optimization solving on the processed natural gas pipeline network scheduling model to obtain scheduling data of the natural gas pipeline network, and scheduling each pipeline network object based on the scheduling data. Through the above method, the natural gas pipeline network flow direction scheduling can be adapted to large-scale, multi-period, multi-gas source and multi-user, and more accurate and reliable scheduling data can be obtained.
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