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Issue title: Applications of intelligent & fuzzy theory in engineering technologies and applied science
Guest editors: Álvaro Rocha
Article type: Research Article
Authors: Wei, Lixin | Dong, Hang* | Zhao, Jian | Zhou, Gang
Affiliations: Oil and Gas Storage and Transportation Engineering of Northeast Petroleum University, Daqing, China
Correspondence: [*] Corresponding author. Hang Dong, Oil and Gas Storage and Transportation Engineering of Northeast Petroleum University, Daqing, China. E-mail: [email protected].
Abstract: To minimize total construction investment of the gas field gathering and transmission pipeline network, the mathematic model for optimization design of the gathering and transmission pipeline network of the gas field is established, which takes the pipeline network topology layout, pipe diameter, wall thickness and electric tracing power as the decision variants and the pipeline hydraulic equilibrium, thermodynamic equilibrium and actual process requirements as the constraint conditions. Based on the structural features of the model, the mathematic model is decomposed into the pipeline network topology optimization and parameter optimization problem. The hybrid optimization solution strategy is proposed including multiple layers, punishment function and intelligent optimization algorithm. Based on the above work, 7 kernel program classes are developed with the aid of C++ Builder development platform, OLE DB database connection technology and Map Objects component technology. Based on these classes, the gathering and transmission pipeline network layout demonstration, process computing and optimization design is implemented via computers, thus the gathering and transmission pipeline network optimization design platform is developed. This software is used to optimize design of the gathering and transmission pipeline network in a block of Daqing oil field. Compared to the artificial design scheme, the optimization scheme can save 13.9% of the investment cost.
Keywords: Pipeline network optimization, topology optimization, parameter optimization, software, natural gas gathering
DOI: 10.3233/JIFS-169078
Journal: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 4, pp. 2375-2382, 2016
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