Resilience assessment methodology of natural gas network system under random leakage

Abstract

Natural gas accounts for more than 20% of global primary energy demand. Potential natural or man-made disasters can cause natural gas supply shortages, with severe economic and social consequences. System resilience is difficult to achieve because of many factors affecting the natural gas network system (NGNS) and the uncertainty of the timing, location, and shock strengths. A new methodology for evaluating the resilience of NGNS under random leakage conditions is developed by combining Monte Carlo simulation and hydraulic analysis of an unsteady flow. A resilience metric based on gas supply capacity and reliability is proposed. The extensive time delay and nonlinear dynamic characteristics of the system caused by the compressibility of the natural gas are considered in combination with hydraulic analysis. System uncertainty in damage and recovery states is resolved by batch simulation of the random leakage. The resilience value is calculated by integrating the performance curve. The proposed methodology is demonstrated on the NGNS of Shandong Province, China, and results show that it can effectively assess the resilience of the NGNS under random leakage conditions.