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Convexification for natural gas transmission networks optimization

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  • Liang, Yingzong
  • Hui, Chi Wai

Abstract

Natural gas transmission is energy consuming due to significant pressure loss during the transportation process. Despite considerable effort to reduce its energy consumption in optimization study, the nonconvex behavior of mathematical models, mainly resulted from nonconvex pressure drop constraints, have made the problem challenging to tackle. To address this issue, this paper presents two convex formulation techniques to convexify the pressure drop constraints. The techniques use logical constraints to handle unknown gas flow direction to avoid absolute values and bilinear terms in the constraints. Modeling techniques are also presented to reformulate nonconvex compressor constraints into convex/concave ones. The proposed techniques are applied to two different scale natural gas transmission networks. Computational results suggest that the convexification relieves the models from local optima, and greatly improves solution quality and solution efficiency.

Suggested Citation

  • Liang, Yingzong & Hui, Chi Wai, 2018. "Convexification for natural gas transmission networks optimization," Energy, Elsevier, vol. 158(C), pages 1001-1016.
    • Handle: RePEc:eee:energy:v:158:y:2018:i:c:p:1001-1016
    DOI: 10.1016/j.energy.2018.06.107
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    3. Wang, Guotao & Zhao, Wei & Qiu, Rui & Liao, Qi & Lin, Zhenjia & Wang, Chang & Zhang, Haoran, 2023. "Operational optimization of large-scale thermal constrained natural gas pipeline networks: A novel iterative decomposition approach," Energy, Elsevier, vol. 282(C).
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    5. Wang, Bohong & Klemeš, Jiří Jaromír & Liang, Yongtu & Yuan, Meng & Zhang, Haoran & Liu, Jiayi, 2020. "Implementing hydrogen injection in coal-dominated regions: Supply chain optimisation and reliability analysis," Energy, Elsevier, vol. 201(C).

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