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Global layout optimization of star-tree gas gathering pipeline network via an improved genetic optimization algorithm.

Authors :
Peng, Jinghong
Zhou, Jun
Liang, Guangchuan
Qin, Can
Peng, Cao
Chen, YuLin
Hu, Chengqiang
Source :
Journal of Intelligent & Fuzzy Systems; 2023, Vol. 44 Issue 2, p2655-2672, 18p
Publication Year :
2023

Abstract

Gas gathering pipeline network system is an important process facility for gas field production, which is responsible for collecting, transporting and purifying natural gas produced by wells. In this paper, an optimization model for the layout of star-tree gas gathering pipeline network in discrete space is established to find the most economical design scheme. The decision variables include valve set position, station position and pipeline connection relation. A series of equality and inequality constraints are developed, including node flow balance constraints, pipeline hydraulic constraints and pipeline structure constraints. A global optimization strategy is proposed and an improved genetic algorithm is used to solve the model. To verify the validity of the proposed method, the optimization model is applied to a coalbed methane field gathering pipeline network in China. The results show that the global optimization scheme saves 1489.74×10<superscript>4</superscript> RMB (26.36%) in investment cost compared with the original scheme. In addition, the comparison between the global and hierarchical optimization scheme shows that the investment cost of the global optimization scheme is 567.22×10<superscript>4</superscript> RMB less than that of the hierarchical optimization scheme, which further proves the superiority of the global optimization method. Finally, the study of this paper can provide theoretical guidance for the design and planning of gas field gathering pipeline network. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10641246
Volume :
44
Issue :
2
Database :
Complementary Index
Journal :
Journal of Intelligent & Fuzzy Systems
Publication Type :
Academic Journal
Accession number :
161762973
Full Text :
https://doi.org/10.3233/JIFS-222199