Optimal Operation of Transient Gas Transport Networks

dc.contributor.authorHoppmann-Baum, Kai
dc.contributor.authorHennings, Felix
dc.contributor.authorLenz, Ralf
dc.contributor.authorGotzes, Uwe
dc.contributor.authorHeinecke, Nina
dc.contributor.authorSpreckelsen, Klaus
dc.contributor.authorKoch, Thorsten
dc.date.accessioned2023-04-06T12:13:50Z
dc.date.available2023-04-06T12:13:50Z
dc.date.issued2021-02-16
dc.date.updated2023-03-25T07:11:06Z
dc.description.abstractIn this paper, we describe an algorithmic framework for the optimal operation of transient gas transport networks consisting of a hierarchical MILP formulation together with a sequential linear programming inspired post-processing routine. Its implementation is part of the KOMPASS decision support system, which is currently used in an industrial setting. Real-world gas transport networks are controlled by operating complex pipeline intersection areas, which comprise multiple compressor units, regulators, and valves. In the following, we introduce the concept of network stations to model them. Thereby, we represent the technical capabilities of a station by hand-tailored artificial arcs and add them to network. Furthermore, we choose from a predefined set of flow directions for each network station and time step, which determines where the gas enters and leaves the station. Additionally, we have to select a supported simple state, which consists of two subsets of artificial arcs: Arcs that must and arcs that cannot be used. The goal is to determine a stable control of the network satisfying all supplies and demands. The pipeline intersections, that are represented by the network stations, were initially built centuries ago. Subsequently, due to updates, changes, and extensions, they evolved into highly complex and involved topologies. To extract their basic properties and to model them using computer-readable and optimizable descriptions took several years of effort. To support the dispatchers in controlling the network, we need to compute a continuously updated list of recommended measures. Our motivation for the model presented here is to make fast decisions on important transient global control parameters, i.e., how to route the flow and where to compress the gas. Detailed continuous and discrete technical control measures realizing them, which take all hardware details into account, are determined in a subsequent step. In this paper, we present computational results from the KOMPASS project using detailed real-world data.en
dc.description.sponsorshipBMBF, 05M14ZAM, Forschungscampus Modal - Mathematical Optimization and Data Analysis Laboratories. Antrag auf die erste Hauptphase (Implementierung) des Forschungscampus Modal
dc.description.sponsorshipBMBF, 05M20ZBM, Forschungscampus MODAL - Mathematical Optimization and Data Analysis Laboratories - zweite Förderphase (Stabilisierung)
dc.identifier.eissn1573-2924
dc.identifier.issn1389-4420
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/18511
dc.identifier.urihttps://doi.org/10.14279/depositonce-17320
dc.language.isoen
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc500 Naturwissenschaften und Mathematik::510 Mathematik::510 Mathematik
dc.subject.othertransient gas network optimizationen
dc.subject.otherhierarchical optimizationen
dc.subject.othermixed integer linear programmingen
dc.titleOptimal Operation of Transient Gas Transport Networksen
dc.typeArticle
dc.type.versionpublishedVersion
dcterms.bibliographicCitation.doi10.1007/s11081-020-09584-x
dcterms.bibliographicCitation.issue2
dcterms.bibliographicCitation.journaltitleOptimization and Engineering
dcterms.bibliographicCitation.originalpublishernameSpringer Nature
dcterms.bibliographicCitation.originalpublisherplaceHeidelberg
dcterms.bibliographicCitation.pageend781
dcterms.bibliographicCitation.pagestart735
dcterms.bibliographicCitation.volume22
dcterms.rightsHolder.referenceCreative-Commons-Lizenz
tub.accessrights.dnbfree
tub.affiliationFak. 2 Mathematik und Naturwissenschaften::Inst. Mathematik::FG Software und Algorithmen für die diskrete Optimierung
tub.publisher.universityorinstitutionTechnische Universität Berlin

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