Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/309789 
Year of Publication: 
2022
Citation: 
[Journal:] Mathematical Methods of Operations Research [ISSN:] 1432-5217 [Volume:] 95 [Issue:] 3 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2022 [Pages:] 475-501
Publisher: 
Springer, Berlin, Heidelberg
Abstract: 
We are concerned with the simulation and optimization of large-scale gas pipeline systems in an error-controlled environment. The gas flow dynamics is locally approximated by sufficiently accurate physical models taken from a hierarchy of decreasing complexity and varying over time. Feasible work regions of compressor stations consisting of several turbo compressors are included by semiconvex approximations of aggregated characteristic fields. A discrete adjoint approach within a first-discretize-then-optimize strategy is proposed and a sequential quadratic programming with an active set strategy is applied to solve the nonlinear constrained optimization problems resulting from a validation of nominations. The method proposed here accelerates the computation of near-term forecasts of sudden changes in the gas management and allows for an economic control of intra-day gas flow schedules in large networks. Case studies for real gas pipeline systems show the remarkable performance of the new method.
Subjects: 
Transient gas supply networks
Model hierarchy
Error estimators
Adaptivity
Optimal control
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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