The calculation and optimal allocation of transmission capacity in natural gas networks with MINLP models
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The calculation and optimal allocation of transmission capacity in natural gas networks with MINLP models
Chinese Journal of Chemical EngineeringVol. 59, Issue 7, Pages: 251-261(2023)
Affiliations:
National Engineering Laboratory for Pipeline Safety/Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-, Beijing,Beijing,China,102249
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Published:2023
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Yaran Bu, Changchun Wu, Lili Zuo, Qian Chen. The calculation and optimal allocation of transmission capacity in natural gas networks with MINLP models[J]. Chinese Journal of Chemical Engineering, 2023, 59(7): 251-261.
DOI:
Yaran Bu, Changchun Wu, Lili Zuo, Qian Chen. The calculation and optimal allocation of transmission capacity in natural gas networks with MINLP models[J]. Chinese Journal of Chemical Engineering, 2023, 59(7): 251-261.DOI:
The calculation and optimal allocation of transmission capacity in natural gas networks with MINLP models
The transmission capacity of gas pipeline networks should be calculated and allocated to deal with the capacity booking with shippers. Technical capacities
which depend on the gas flow distribution at routes or interchange points
are calculated with a multiobjective optimization model and form a Pareto solution set in the entry/exit or point-to-point regime. Then
the commercial capacities
which can be directly applied in capacity booking
are calculated with single-objective optimization models that are transformed from the above multiobjective model based on three allocation rules and the demand of shippers. Next
peak-shaving capacities
which are daily oversupply or overdelivery amounts at inlets or deliveries
are calculated with two-stage transient optimization models. Considering the hydraulic process of a pipeline network and operating schemes of compressor stations
all the above models are mixed-integer nonlinear programming problems. Finally
a case study is made to demonstrate the ability of the models.
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