This paper investigates the influence of failure of transmission network key elements on security of natural gas delivery. The proposed framework combines the probabilistic structure integrity study and the hydraulic analysis. A factor called a volumetric loss was introduced to quantify the effect of network failure. Based on the magnetic flux leakage diagnostics, the rupture probability of steel tube plastic collapse was estimated using a random variable method and Monte Carlo solution. In-line inspections should monitor only the rate of tube wall corrosion, whereas the proposed methodology enables the pipeline operator to evaluate the system ability to deliver gas at the customer nodes. For the hydraulic analysis, an unsteady gas flow model was applied using conservation principles of mass, momentum, and energy. The flow model was tuned to real pressure and temperature data using a multi-objective optimization approach. To demonstrate the practical value of the methodology, the time and amount of gas shortage, line pack, and a volumetric loss were computed for a real tree-topological pipeline network. Simulations demonstrated that the highest volumetric loss is experienced when both compressor stations are shut down. The aim of the proposed algorithm is identification of critical nodes as well as evaluation of measures for improving the gas supply reliability to the customers.

本文研究了输电网络关键元件故障对天然气输送安全性的影响。所提出的框架结合了概率结构完整性研究和水力分析。为了量化网络故障的影响，引入了一个称为体积损失的因素。基于漏磁诊断，使用随机变量法和蒙特卡洛方法估计了钢管塑料塌陷的破裂概率。在线检查应仅监视管壁腐蚀的速率，而所提出的方法使管道运营商能够评估系统在客户节点处输送天然气的能力。对于水力分析，使用质量，动量和能量守恒原理应用了非稳态气体流动模型。使用多目标优化方法将流量模型调整为实际压力和温度数据。为了证明该方法的实用价值，针对真实的树状拓扑管道网络计算了气体短缺的时间和数量，管线组和体积损失。仿真表明，两个压缩机站都关闭时，体积损失最大。所提出的算法的目的是识别关键节点以及评估用于改善向用户的气体供应可靠性的措施。仿真表明，两个压缩机站都关闭时，体积损失最大。所提出的算法的目的是识别关键节点以及评估用于改善向用户的气体供应可靠性的措施。仿真表明，两个压缩机站都关闭时，体积损失最大。所提出的算法的目的是识别关键节点以及评估用于改善向用户的气体供应可靠性的措施。