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A method for the multi-objective optimization of the operation of natural gas pipeline networks considering supply reliability and operation efficiency

Abstract : Reliable gas supply for minimum risk of supply shortage and minimum power demand for low energy cost are two fundamental objectives of natural gas pipeline networks. In this paper, a multi-objective optimization method is developed to trade-off reliability and power demand in the decision process. In the optimization, the steady state behavior of the natural gas pipeline networks is considered, but the uncertainties of the supply conditions and customer consumptions are accounted for. The multi-objective optimization regards finding operational strategies that minimize power demand and risk of gas supply shortage. To quantify the probability of supply interruption in pipeline networks, a novel limit function is introduced based on the mass conservation equation. Then, the risk of interruption is calculated by combining the probability of interruption and its consequences, measured in utility terms. The multi-objective optimization problem is solved by the NSGA-II algorithm and its effectiveness is tested on two typical pipeline networks, i.e., a tree-topology network and a loop-topology network. The results show that the developed optimization model is able to find solutions which effectively compromise the need of minimizing gas supply shortage risk and reducing power demand. Finally, a sensitivity analysis is conducted to analyze the impact of demand uncertainties on the optimization resu
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https://hal-mines-paristech.archives-ouvertes.fr/hal-02432548
Contributeur : Magalie Prudon <>
Soumis le : mercredi 8 janvier 2020 - 14:54:10
Dernière modification le : jeudi 24 septembre 2020 - 17:20:28

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Huai Su, Enrico Zio, Jinjun Zhang, Xueyi Li, Lixun Chi, et al.. A method for the multi-objective optimization of the operation of natural gas pipeline networks considering supply reliability and operation efficiency. Computers and Chemical Engineering, Elsevier, 2019, 131, pp.106584. ⟨10.1016/j.compchemeng.2019.106584⟩. ⟨hal-02432548⟩

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