Operation Optimization of Multiroute Cyclic Natural Gas Transmission Network under Different Objectives
Publication: Journal of Pipeline Systems Engineering and Practice
Volume 13, Issue 1
Abstract
Natural gas transmission networks (NGTNs) are the main facility connecting upstream gas sources and downstream consumers. For a cyclic NGTN with multiple gas transmission routes, different gas transportation schemes will affect not only the energy consumption of the system but also the pipeline transportation costs paid by consumers. In this paper, three operation optimization models are established to determine the optimal operating state of a multiroute cyclic NGTN under different scenarios. The three mathematical models correspond to three different objective functions: minimize the cost of compressor energy consumption, minimize the expense of pipeline transportation, and minimize the sum of the two expenses. The decision variables of the models include the pipeline flow rate, the number of operating compressors, and the outlet pressure of the compressors. In addition, a series of linear and nonlinear constraints of nodes, pipelines, and compressors is also proposed to guarantee the feasibility of solutions. The operation optimization problem is solved by the General Algebraic Modeling System (GAMS), and the effectiveness of this method is tested on a small double-route cyclic NGTN and a large three-route cyclic NGTN. The results show that the developed optimization model is able to find optimal solutions under different models. In the cyclic network, the difference in the flow distribution of gas transmission routes is the key factor affecting the optimization result. In addition, compared with the compressor energy consumption cost minimization objective, the pipeline transportation expense minimization objective can create greater economic benefits for consumers. In the two network cases, consumers can save 14.51 and RMB. Finally, optimizing the two objectives at the same time makes it possible to achieve an effective balance between them.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (51704253).
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© 2021 American Society of Civil Engineers.
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Received: May 16, 2021
Accepted: Oct 8, 2021
Published online: Nov 26, 2021
Published in print: Feb 1, 2022
Discussion open until: Apr 26, 2022
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