Optimal scheduling model to minimize tritium inventory level in fuel cycle of tritium plant

•We introduced a mathematical model for the fueling line of fuel cycle modeling to minimize the tritium inventory level.•We obtained the tritium working inventory in the Isotope Separation System during one burn and dwell cycle under different tokamak operation modes.•The model provides insights on...

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Bibliographic Details
Published in:Fusion engineering and design 2018-11, Vol.136, p.747-751
Main Authors: Lee, Suh-Young, Chang, Min Ho, Yun, Sei-Hun, Ha, Jin-Kuk, Lee, In-Beum, Lee, Euy Soo
Format: Article
Language:English
Subjects:
Burn-and-dwell operation
Electric power generation
Flow velocity
Fuel cycle
Fuel cycles
Fusion
Isotope separation
Minlp
Mixed integer
Nonlinear programming
Nuclear power plants
Nuclear reactors
Optimal operation
Optimization
Power plants
Scheduling
Tokamak devices
Tritium
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Summary:•We introduced a mathematical model for the fueling line of fuel cycle modeling to minimize the tritium inventory level.•We obtained the tritium working inventory in the Isotope Separation System during one burn and dwell cycle under different tokamak operation modes.•The model provides insights on determining the optimum scheduling results for minimizing tritium working inventory. This paper proposes an optimization model for the scheduling of the fuel cycle of a fusion power plant. The objective of the problem is to minimize the tritium working inventory in the Isotope Separation System under periodic demand, thereby solving problems associated with high inventories. The model is formulated as a mixed integer nonlinear programming problem based on the state-task network approach. The proposed model is applied to inductive, hybrid, and non-inductive tokamak operation modes. With proposed case studies, the model is expected to provide many useful insights to determine the optimum scheduling results providing information on flow pattern, flow rate, and flow timing between equipment while minimizing tritium working inventory.
ISSN:0920-3796
1873-7196
DOI:10.1016/j.fusengdes.2018.04.003