Generic layout optimization design methodology for China's loop-star natural gas field pipeline network

IF 4.2 3区 工程技术 Q2 ENERGY & FUELS
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引用次数: 0

Abstract

The layout optimization design of a natural gas gathering pipeline network is a multi-objective optimization problem because the extant theories are unable to meet the different decision preferences in scheme design, which restricts the intelligentization of gas gathering pipeline layout optimization. Currently, there are no generic design studies on the loop-star pipeline network. Therefore, this paper proposes a generic layout optimization model containing a large number of discrete and continuous variables, such as pipe connection relationships, pipe sizes, pipe length, and pipe specifications. In the solution section, drawing inspiration from the hormone regulation mechanism and local foraging rule in bionics, an improved particle swarm optimization algorithm based on hormone regulation (HRPSO) is proposed, and it obtains the favorable parameters range of the HRPSO algorithm. The results illustrate that the HRPSO algorithm exhibits convergence to the global optimum with a probability of 1. In comparison to manual design, the comprehensive costs of the optimized scheme are saved by 22.71% with the HRPSO algorithm. Compared to the four PSO variants in the paper, it can save costs by 5.38%, 4.95%, 4.09%, and 3.65%, respectively.
中国环星天然气田管网通用布局优化设计方法
天然气集输管网的布局优化设计是一个多目标优化问题,因为现有理论无法满足方案设计中不同的决策偏好,限制了集输管道布局优化的智能化。目前,还没有关于环星管网的通用设计研究。因此,本文提出了一个包含大量离散变量和连续变量的通用布局优化模型,如管道连接关系、管道尺寸、管道长度和管道规格等。在求解部分,借鉴仿生学中的激素调节机制和局部觅食规则,提出了一种基于激素调节的改进粒子群优化算法(HRPSO),并获得了 HRPSO 算法的有利参数范围。结果表明,HRPSO 算法收敛到全局最优的概率为 1。与人工设计相比,HRPSO 算法优化方案的综合成本节约了 22.71%。与本文中的四种 PSO 变体相比,它可分别节约成本 5.38%、4.95%、4.09% 和 3.65%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Natural Gas Industry B
Natural Gas Industry B Earth and Planetary Sciences-Geology
CiteScore
5.80
自引率
6.10%
发文量
46
审稿时长
79 days
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