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dc.contributor.authorQiu, Kang
dc.contributor.authorAndersson, Leif Erik
dc.contributor.authorZotica, Cristina
dc.contributor.authorReyes-Lúa, Adriana
dc.contributor.authorMocholí Montañés, Rubén
dc.contributor.authorVerheyleweghen, Adriaen
dc.contributor.authorChabaud, Valentin Bruno
dc.contributor.authorVrana, Til Kristian
dc.date.accessioned2023-08-21T12:18:00Z
dc.date.available2023-08-21T12:18:00Z
dc.date.created2023-08-14T09:06:06Z
dc.date.issued2023
dc.identifier.citationComputer-aided chemical engineering. 2023, 52 1545-1550.en_US
dc.identifier.issn1570-7946
dc.identifier.urihttps://hdl.handle.net/11250/3085074
dc.description.abstractModel predictive control of compact combined cycles in offshore power plants integrating a wind farmen_US
dc.description.abstractCombined cycle gas turbine plants (CCGTs) fulfill an important role in emission reduction of offshore power systems as the bottoming cycle (BC) produces additional power from exhaust heat of the gas turbines (GTs). With increasing integration of wind turbines, CCGTs offshore must be flexible and provide variation management to the offshore energy system across multiple time scales. This work proposes a model predictive controller (MPC) sending setpoints to the CCGT to satisfy demand in the offshore power system under fluctuating wind power. A high-speed surrogate model suitable for optimizing in an MPC is identified. A linear MPC using a quadratic cost function with process constraints is formulated. The model-based control structure is then validated in simulation for satisfying a constant power demand under disturbances introduced by fluctuating wind power.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleModel predictive control of compact combined cycles in offshore power plants integrating a wind farmen_US
dc.title.alternativeModel predictive control of compact combined cycles in offshore power plants integrating a wind farmen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionacceptedVersionen_US
dc.rights.holderThe Authors hold the copyright to the Author Accepted Manuscript. Distributed under the terms of the Creative Commons Attribution License (CC BY 4.0)en_US
dc.source.pagenumber1545-1550en_US
dc.source.volume52en_US
dc.source.journalComputer-aided chemical engineeringen_US
dc.identifier.doi10.1016/B978-0-443-15274-0.50246-8
dc.identifier.cristin2166622
dc.relation.projectNorges forskningsråd: 296207en_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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