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Prediction and dynamic operation of gas distribution networks

机译:气体分配网络的预测和动态操作

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In the Netherlands a dense gas distribution network delivers gas to the majority of households. Traditionally only a few big suppliers deliver gas to the network, but currently there is a growing number of new small green gas suppliers in an increasingly flexible and competitive gas transport market. The gas transport providers, responsible for delivering gas to their customers, are confronted with a much more challenging task in operating the network, especially when confronted with fast changes in supply and demand and during maintenance and incidents. This complexity asks for operator support operating the network. In this paper we show, based on physical models of a typical network, involving hundreds of kilometers of pipelines and thousands of nodes and branches, how a fast and versatile simulation model, can predict the pressures and flows in the network. This gas transport simulation: predicting pressures, flows and mixtures at every location in the network, is the basis of controlling a less robust gas network, through periods of high and low demand. We will simulate a real network with the physical relations between flow, pressure, pressure drop, time-delay and mixing. Due to the nonlinear relations between pressure and flow, the standard techniques of dynamical (electrical) network simulation cannot be applied. They lead to instabilities, numerical inaccuracies and slow convergence. We will show how we solved these problems. We further show how this prediction model fits in an operator support environment that helps network operators in real-time management of operations.??
机译:在荷兰,密集的气体配送网络为广大家庭提供气体。传统上,只有少数大供应商将天然气送到网络,但目前在越来越灵活且竞争激烈的燃气运输市场中越来越多的新型绿色燃气供应商。燃气运输提供者负责将气体提供给客户,面对操作网络的更具挑战性的任务,特别是在面对供需变化以及维护和事件期间。这种复杂性要求操作网络的运营商支持。在本文中,我们展示了典型网络的物理模型,涉及数百公里的管道和数千个节点和分支机构,如何快速和多功能的仿真模型,可以预测网络中的压力和流量。这种气体运输模拟:预测网络中每个位置的压力,流量和混合物,是控制较轻的气体网络,通过高需求的时期控制较低的稳健性气体网络的基础。我们将模拟一个真正的网络,流量,压力,压降,时滞和混合之间的物理关系。由于压力和流量之间的非线性关系,无法应用动态(电气)网络仿真的标准技术。它们导致不稳定,数值不准确和缓慢的收敛性。我们将展示我们如何解决这些问题。我们进一步展示了该预测模型如何适合运营商支持环境,帮助网络运营商在实时管理操作中。??

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