Synthetic models of distribution gas networks in low-carbon energy systems

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

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

A Statistical Assessment of Blending Hydrogen into Gas Networks

The deployment of low-carbon hydrogen in gas grids comes with strategic benefits in terms of energy system integration and decarbonization. However, hydrogen thermophysical properties substantially differ from natural gas and pose concerns of technical and regulatory nature. The present study investigates the blending of hydrogen into distribution gas networks, focusing on the steady-state fluid dynamic response of the grids and gas quality compliance issues at increasing hydrogen admixture levels. Two blending strategies are analyzed, the first of which involves the supply of NG–H2 blends at the city gate, while the latter addresses the injection of pure hydrogen in internal grid locations. In contrast with traditional case-specific analyses, results are derived from simulations executed over a large number (i.e., one thousand) of synthetic models of gas networks. The responses of the grids are therefore analyzed in a statistical fashion. The results highlight that lower probabilities of violating fluid dynamic and quality restrictions are obtained when hydrogen injection occurs close to or in correspondence with the system city gate. When pure hydrogen is injected in internal grid locations, even very low volumes (1% vol of the total) may determine gas quality violations, while fluid dynamic issues arise only in rare cases of significant hydrogen injection volumes (30% vol of the total)

Pressure management in smart gas networks for increasing hydrogen blending

The injection of hydrogen into existing gas grids is acknowledged as a promising option for decarbonizing gas systems and enhancing the integration among energy sectors. Nevertheless, it affects the hydraulics and the quality management of networks. When the network is fed by multiple infeed sites and hydrogen is fed from a single injection point, non-homogeneous hydrogen distribution throughout the grid happens to lead to a reduction of the possible amount of hydrogen to be safely injected within the grid. To mitigate these impacts, novel operational schemes should therefore be implemented. In the present work, the modulation of the outlet pressures of gas infeed sites is proposed as an effective strategy to accommodate larger hydrogen volumes into gas grids, extending the area of the network reached by hydrogen while keeping compliance with quality and hydraulic restrictions. A distribution network operated at two cascading pressure tiers interfaced by pressure regulators constitutes the case study, which is simulated by a fluid-dynamic and multi-component model for gas networks. Results suggest that higher shares of hydrogen and other green gases can be introduced into existing distribution systems by implementing novel asset management schemes with negligible impact on grid operations

Generation of synthetic models of gas distribution networks with spatial and multi-level features

This paper addresses the generation of models of distribution gas networks with realistic topological, spatial and technical features. The proposed algorithm offers a novel methodology for reproducing networks with multiple pressure levels. The procedure is tailor-designed for gas distribution networks, although minor ad-hoc modifications could extend its application to virtually any other physical network infrastructure. A probabilistic approach is followed, in which Gaussian Mixture Models (GMM) are used for spatial placement of the synthetic nodes and distance-based criteria are formulated to establish connections among them. Different pressure levelsare separately generated and connected in a hierarchical fashion via pressure reduction stations, while independent subnetwork islands are identified by introducing a novel clustering scheme. The strengths and feasibility of the approach are verified on a real test case via comparison of specific structural properties and results highlight a fine agreement between the topology and the geographical distribution of the real and synthetic networks. It follows that the algorithm offers a first effective solution toward the generation of spatially-embedded network models to treat gas networks and structures with multiple hierarchical levels