A Mixed-Integer Linear Programming Model for the Station Capacity Allocation Problem of a Star-Tree Pipe Network
Publication: Journal of Pipeline Systems Engineering and Practice
Volume 14, Issue 1
Abstract
The optimization of the layout of the surface gathering and transportation pipe network in the oil and gas field can effectively reduce the total investment in the pipe network. Currently, based on the constraints of fixed station capacity in the star-tree pipe network topology, hierarchical optimization strategies are often used to optimize the pipe network layout. Aiming at the overall optimization of the layout of the star-tree ground gathering and transportation pipe network, this paper constructs a special mixed-integer linear programming (MILP) mathematical model considering the station capacity allocation problem, which can simultaneously obtain the optimal pipe network topology, pipe connection relationship, station location and quantity, station type, central station [central processing plant (CPP)] location and investment of each part. Numerical analysis of gas fields of different scales is used to discuss the influence of station capacity allocation and different station capacity combinations on the optimization of pipe network layout. The optimization effect of star-tree and star-star pipe network layout is compared and analyzed. The results not only prove the correctness and effectiveness of the model and algorithm proposed in this paper but also reduce the total investment of the pipe network. It can be seen that the optimization scheme has guiding significance for the surface engineering construction of the oil and gas fields.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was part of the program “Study on the optimization method and architecture of oil and gas pipeline network design in discrete space and network space,” funded by the National Natural Science Foundation of China, Grant No. 51704253. The authors are grateful to all study participants.
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Published In
Journal of Pipeline Systems Engineering and Practice
Volume 14 • Issue 1 • February 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Feb 5, 2022
Accepted: Jul 29, 2022
Published online: Oct 17, 2022
Published in print: Feb 1, 2023
Discussion open until: Mar 17, 2023
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