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Improving the natural gas transporting based on the steady state simulation results

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  • Szoplik, Jolanta

Abstract

The work presents an example of practical application of gas flow modeling results in the network, that was obtained for the existing gas network and for real data about network load depending on the time of day and air temperature. The gas network load in network connections was estimated based on real data concerning gas consumption by customers and weather data in 2010, based on two-parametric model based on the number of degree-days of heating. The aim of this study was to elaborate a relationship between pressure and gas stream introduced into the gas network. It was demonstrated that practical application of elaborated relationship in gas reduction station allows for the automatic adjustment of gas pressure in the network to the volume of network load and maintenance of gas pressure in the whole network at possibly the lowest level. It was concluded based on the results obtained that such an approach allows to reduce the amount of gas supplied to the network by 0.4% of the annual network load.

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  • Szoplik, Jolanta, 2016. "Improving the natural gas transporting based on the steady state simulation results," Energy, Elsevier, vol. 109(C), pages 105-116.
    • Handle: RePEc:eee:energy:v:109:y:2016:i:c:p:105-116
    DOI: 10.1016/j.energy.2016.04.104
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    6. Kai Wen & Zijie Xia & Weichao Yu & Jing Gong, 2018. "A New Lumped Parameter Model for Natural Gas Pipelines in State Space," Energies, MDPI, vol. 11(8), pages 1-17, July.
    7. Szoplik, Jolanta & Muchel, Paulina, 2023. "Using an artificial neural network model for natural gas compositions forecasting," Energy, Elsevier, vol. 263(PD).
    8. Mikolajková, Markéta & Saxén, Henrik & Pettersson, Frank, 2018. "Linearization of an MINLP model and its application to gas distribution optimization," Energy, Elsevier, vol. 146(C), pages 156-168.
    9. Mikolajková, Markéta & Haikarainen, Carl & Saxén, Henrik & Pettersson, Frank, 2017. "Optimization of a natural gas distribution network with potential future extensions," Energy, Elsevier, vol. 125(C), pages 848-859.
    10. Ding, Hongbing & Zhang, Yu & Sun, Chunqian & Yang, Yan & Wen, Chuang, 2022. "Numerical simulation of supersonic condensation flows using Eulerian-Lagrangian and Eulerian wall film models," Energy, Elsevier, vol. 258(C).
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