Volume 6 Number 3 (Mar. 2011)
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JSW 2011 Vol.6(3): 452-459 ISSN: 1796-217X
doi: 10.4304/jsw.6.3.452-459

Adaptive Genetic Algorithm for Steady-State Operation Optimization in Natural Gas Networks

Changjun Li, Wenlong Jia, Yi Yang, Xia Wu
School of Petroleum Engineering, Southwest Petroleum University, Chengdu, China

Abstract—Natural gas is normally transported through a vast network of pipelines. A pipeline network is generally established to connect gas wells with gas processing fields (gathering network) or to transmit gas at high pressure from gas sources to regional demand points (trunk network) or to distribute gas to consumers at low pressure from regional demand points (distribution network). The problems involved in optimizing the operation conditions of networks to promote benefit belong to a class of non-liner optimization problems. The operation benefit of gas network is combined with the purchase and sale prices of gas, the quantity bought and sold of gas and the management costs. Aimed at the maximum operation benefit, the paper proposes an operation optimization model of gas network with consideration of quantity input (output) constraints of each node, operation pressure constraints of pipelines, compressor constraints, valve constraints and hydraulic constraints of the pipeline system. The model adapts to all kinds of pipeline structures, followed with our presentation of a global approach, which is based on the method of adaptive genetic algorithm, to the optimization model. Afterwards, computer software is developed to optimize the operation conditions of gas trunk networks, gas gathering and distribution networks. Finally, an application example is demonstrated.

Index Terms—gas pipeline network, operation optimization, mathematical model, adaptive genetic algorithm


Cite: Changjun Li, Wenlong Jia, Yi Yang, Xia Wu, "Adaptive Genetic Algorithm for Steady-State Operation Optimization in Natural Gas Networks," Journal of Software vol. 6, no. 3, pp. 452-459, 2011.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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