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气田地面集输管网参数优化设计
引用本文:刘幕毅,付晓明,魏立新,杨广仁,王辉,潘峰.气田地面集输管网参数优化设计[J].当代化工,2017,46(4).
作者姓名:刘幕毅  付晓明  魏立新  杨广仁  王辉  潘峰
作者单位:1. 东北石油大学,黑龙江大庆,163318;2. 大庆油田有限责任公司储运销售分公司,黑龙江大庆,163000
基金项目:国家自然科学基金面上项目,国家自然科学基金重点项目
摘    要:气田集输管网参数优选是气田地面工程规划设计的关键,开展集输管网参数优化可以有效降低集气系统投资。针对气田常用管网结构和工艺流程,考虑伴热带传热对于管道工艺计算的影响,建立了以管网建设费用最小为目标,以温压平衡、经济流速、节点流量平衡等为约束条件的气田集输管网参数优化数学模型,根据模型的结构特点设计了粒子群智能求解算法,结合C#语言和Access数据库开发了优化设计软件。实例验证得出,模型及算法正确,粒子群求解算法可靠性和收敛性良好,优化软件稳定高效。

关 键 词:气田  集输管网  参数优化  粒子群  软件

Parameter Optimization Design of Gas Gathering Pipeline Network
LIU Mu-yi,FU Xiao-ming,WEI Li-xin,YANG Guang-ren,WANG Hui,PAN Feng.Parameter Optimization Design of Gas Gathering Pipeline Network[J].Contemporary Chemical Industry,2017,46(4).
Authors:LIU Mu-yi  FU Xiao-ming  WEI Li-xin  YANG Guang-ren  WANG Hui  PAN Feng
Abstract:Parameter optimization of gas gathering and transportation pipeline network is the key to planning and design of gas field surface engineering,and the optimization of gathering and transportation pipeline network parameters can effectively reduce the investment of gas gathering system.In this paper,aiming at common pipeline network structure and process flow of gas field,considering the influence of electric heating power on the calculation of pipeline process,the mathematical model for parameter optimization of gas gathering and transportation network was established,in which the minimum construction cost of pipeline network was the objective and the temperature and pressure balance,economic flow velocity,node flow balance and so on were taken as constraints.According to the structural characteristics of the model,the particle swarm intelligence algorithm was designed.Combined with C# language and Access database,the optimal design software was developed.The examples have verified that the model and algorithm are right,the particle swarm optimization algorithm has good reliability and convergence,and the optimization software is stable and efficient..
Keywords:Gas field  Gas gathering and transportation pipeline network  Parameter optimization  Particle swarm  Software
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