Abstract Pipelines are one of the most efficient methods to transport large quantities of natural gas from gas reserves to main markets. However, because of the unsteady nature of gas flow, the operation of pipelines is always dynamic. Furthermore, the uncertainties in demand and the fluctuation of gas composition also make the efficient operation of these dynamic processes challenging. This study addresses the problem of determining the optimal operation to minimize compression costs, while considering demand and gas composition uncertainties. A dynamic pipeline network model is developed with rigorous thermodynamic equations, allowing accurate calculation of gas compressibility factor at any temporal and spatial point. The supply gas composition and demand nodes flow rates are assumed to be uncertain. To deal with these uncertainties, a robust optimization algorithm is applied using back-off constraints calculated from Monte Carlo simulation. Through successive iterations, the algorithm terminates at a solution that is robust to a specified level of process variability with minimal cost. We show from the case studies that the formulated model and the algorithm can successfully address the problem with acceptable computational cost.

中文翻译：

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需求和成分不确定的天然气管网动态优化

摘要 管道是将大量天然气从储气库输送到主要市场的最有效方法之一。然而，由于气体流动的不稳定特性，管道的运行始终是动态的。此外，需求的不确定性和气体成分的波动也使这些动态过程的有效运行具有挑战性。该研究解决了确定最佳操作以最小化压缩成本的问题，同时考虑了需求和气体成分的不确定性。动态管网模型采用严格的热力学方程开发，可准确计算任何时间和空间点的气体压缩系数。假设供应气体成分和需求节点流速是不确定的。为了应对这些不确定性，使用从蒙特卡罗模拟计算的回退约束来应用稳健的优化算法。通过连续的迭代，该算法终止于以最小成本对指定水平的过程可变性具有鲁棒性的解决方案。我们从案例研究中表明，制定的模型和算法可以以可接受的计算成本成功解决问题。