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An integrated optimization model for natural gas supply chain

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  • Zarei, Javad
  • Amin-Naseri, Mohammad Reza

Abstract

Natural gas is a green fossil fuel with the highest demand growth. Natural gas industry is composed of different sectors that form a complex and large supply chain. These sectors make their own decisions individually, resulting in implementation of non-optimal decisions. The aim of this study is to design and optimize an integrated natural gas supply chain (NGSC) formulated as a mixed integer linear programming (MILP) model. The model minimizes total cost and optimizes gas flow between supply chain nodes through pipelines, location-allocation of facilities and pipeline routes along with their capacities, number of pipelines, capacity expansion, extraction, production, storage, exports and imports. The proposed model is applied to a real world case study based on information derived from Iran's NGSC. Finally, the change effect of the most important parameters on the optimal solution is investigated and three actual scenarios are analyzed. The results indicate that the parameters of operating costs and demand volume have a significant effect on the optimal solution and the largest share of supply chain costs is related to operating expenditures. Moreover, the expansion of joint fields and zero import capacity will lead to a remarkable increase in total supply chain costs.

Suggested Citation

  • Zarei, Javad & Amin-Naseri, Mohammad Reza, 2019. "An integrated optimization model for natural gas supply chain," Energy, Elsevier, vol. 185(C), pages 1114-1130.
    • Handle: RePEc:eee:energy:v:185:y:2019:i:c:p:1114-1130
    DOI: 10.1016/j.energy.2019.07.117
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    Cited by:

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    7. 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).
    8. Dong, Kangyin & Li, Jiaman & Zhang, Haoran, 2023. "LNG point supply of villages and towns in China: Challenges and countermeasures," Applied Energy, Elsevier, vol. 334(C).

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