In practice, transient gas transport problems frequently have to be solved for large-scale gas networks. Gas network optimization problems typically belong to the class of Mixed-Integer Nonlinear Programming Problems (MINLP). However current state-of-the-art MINLP solvers are not yet mature enough to solve large-scale real-world instances. Therefore, an established approach in practice is to solve the problems with respect to a coarser representation of the network and thereby reducing the size of the underlying model. Two well-known aggregation methods that effectively reduce the network size are parallel and serial pipe merges. However, these methods have only been studied in stationary gas transport problems so far. This paper closes this gap and presents parallel and serial pipe merging methods for transient gas transport problems. An empirical evaluation indicates that the developed methods perform very accurately on a huge set of fine-grained real-world data taken from one of the largest transmission system operators in Europe.

中文翻译：

---

瞬态气体管网优化问题的管道合并


在实践中，对于大规模天然气管网，经常需要解决瞬态气体传输问题。天然气管网优化问题通常属于混合整数非线性规划问题 （MINLP） 类。然而，当前最先进的 MINLP 求解器还不够成熟，无法解决大规模的实际实例。因此，实践中的既定方法是解决与网络的更粗略表示有关的问题，从而减小底层模型的大小。两种有效的聚合方法是并行和串行管道合并，它们可以有效减小网络大小。然而，到目前为止，这些方法仅在固定气体传输问题中进行了研究。本文缩小了这一差距，并提出了用于瞬态气体输送问题的并联和串行管道合并方法。实证评估表明，开发的方法对从欧洲最大的输电系统运营商之一获取的大量细粒度真实数据执行非常准确。