Journal
COMPUTERS & INDUSTRIAL ENGINEERING
Volume 131, Issue -, Pages 115-130Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2019.03.041
Keywords
Supply chain system; Multi-state natural gas; Optimal design and operation; Uncertainty; Monte Carlo sampling
Funding
- National Natural Science Foundation of China [51874325]
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The transportation and storage mode of natural gas is various, and natural gas can be transformed into multiple states. Furthermore, it is realized that there are uncertainties in the natural gas purchase price and cities' demands. Thus, the optimal design and operation for the supply chain of multi-state natural gas are revealed as a complex issue. Although many scholars have researched this issue, they usually focused on the design and operation optimization for one-state natural gas. To consider the uncertainties in natural gas purchase price and demand, this paper develops a multi-simulation MILP model based on Monte Carlo sampling, which is used for simulation runs to generate a deal of uncertain parameters. The model captures four seasons, three states of natural gas and four transport options. Finally, four cases are presented as an example to illustrate the solution that can satisfy the real requirements, testifying the application of the model. Simultaneously, it is confirmed that the price uncertainty and the demand uncertainty respectively play an important role in the entire operation cost and the construction scheme of the system.
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