A method for establishing a natural gas pipeline network scheduling optimization model, an optimization method and device

By combining nonlinear optimization models and swarm optimization algorithms with Levy flight technology to optimize natural gas pipeline network scheduling, the problem of high energy consumption in large-scale pipeline systems has been solved, and efficient and accurate power consumption optimization of compressor stations has been achieved.

CN122154109APending Publication Date: 2026-06-05CHINA NAT PETROLEUM CORP
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CHINA NAT PETROLEUM CORP
Filing Date
2024-12-03
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

In large-scale natural gas pipeline systems, existing technologies such as dynamic programming and branch-and-bound methods are computationally expensive and difficult to obtain accurate results quickly. Furthermore, manual scheduling schemes are time-consuming and do not take energy consumption into account, making it difficult to optimize the energy consumption of natural gas pipelines efficiently.

Method used

A nonlinear optimization model and a population optimization algorithm are used to realize the random walk of individuals in the population through Levy flight, optimize the objective function to minimize the power consumption of the compressor station, and establish a natural gas pipeline network scheduling optimization model based on the feature dataset.

Benefits of technology

It enables efficient and accurate optimization of compressor station power consumption in large-scale natural gas pipeline systems, reduces energy consumption, improves global search capabilities, avoids local optima, and improves scheduling efficiency.

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Abstract

The present specification relates to the technical field of natural gas pipeline network scheduling, and provides a natural gas pipeline network scheduling optimization model establishment method, an optimization method and a device. The method comprises: receiving a feature data set of natural gas pipeline network scheduling; inputting the feature data set into a nonlinear optimization model to obtain a corresponding prediction result; establishing an objective function and constraint conditions with minimization of compressor station power consumption of the natural gas pipeline network as an optimization target according to the prediction result; performing iterative exchange evolution between multiple populations by using a population optimization algorithm, and realizing random walk of specified individuals in the population by Levy flight in the process of iterative exchange evolution to optimize the objective function and obtain an optimal solution of the objective function; and optimizing model parameters of the nonlinear optimization model according to the optimal solution of the objective function to determine an optimized nonlinear optimization model as a natural gas pipeline network scheduling optimization model. Through the embodiment of the present specification, natural gas pipeline network scheduling optimization can be efficiently and accurately realized.
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