Synthetic gas networks for the statistical assessment of low-carbon distribution systems

Abstract

Most of the simulation studies on energy networks, including gas grids, derive their results from a limited number of network models. The findings of these works are therefore affected by a substantial case-specificity, which partially limits their validity and prevents their generalisation. To overcome this limitation, the present work proposes a novel statistical-based approach for studying distribution gas networks, enabled by a generator of random gas grids with accurate technical designs and structural features. Ten thousand random and unique networks are produced in three different tests, where increasingly tight constraints are applied to the synthetisation process for a higher control over the generated grids. The experiments verify the accuracy of the tool and highlight that substantial variations can be found in the hydraulic behaviour (pressures and gas velocities) and structural properties (pipe diameters and network volumes) of real-world gas networks. The observed 10,000 gas grids evidence the information gain offered by statistical-based approaches with respect to traditional case-specific studies. The tool opens a broad range of applications which include, but are not limited to, statistical analyses on the distributed injection of alternative gases, like hydrogen, in integrated, low-carbon, energy systems.