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dc.contributor.authorHalvorsen-Weare, Elin Espeland
dc.contributor.authorNorstad, Inge
dc.contributor.authorStålhane, Magnus
dc.contributor.authorNonås, Lars Magne
dc.date.accessioned2018-01-02T17:58:40Z
dc.date.available2018-01-02T17:58:40Z
dc.date.created2018-01-01T15:19:28Z
dc.date.issued2017-10
dc.identifier.citationEnergy Procedia. 2017, 137 531-538.nb_NO
dc.identifier.issn1876-6102
dc.identifier.urihttp://hdl.handle.net/11250/2474170
dc.description.abstractMaintenance operations at offshore wind farms are challenging due to the offshore element; maintenance technicians and spare parts need to be transported from an onshore port or offshore station to the individual wind farm components in need of maintenance. The vessel resources needed to support these maintenance tasks constitute a major part of the total maintenance costs, and hence up-keeping an optimal vessel fleet and corresponding deployment is essential to reduce cost-of-energy. This paper introduces a metaheuristic solution method to determine cost-efficient vessel fleets to support maintenance tasks at offshore wind farms under uncertainty. It considers weather conditions and failures leading to corrective maintenance tasks as stochastic parameters, and evaluates candidate solutions by a simulation program. The solution method has been incorporated in a decision support tool. Computational experiments, including comparison of results with an exact solution method, illustrate that the decision support tool can be used to provide near-optimal solutions within acceptable computational time.nb_NO
dc.language.isoengnb_NO
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.subjectoffshore windnb_NO
dc.subjectoperationnb_NO
dc.subjectmaintenancenb_NO
dc.subjectoperations researchnb_NO
dc.subjectfleet compositionnb_NO
dc.subjectdecision supportnb_NO
dc.subjectmetaheuristicnb_NO
dc.titleA metaheuristic solution method for optimizing vessel fleet size and mix for maintenance operations at offshore wind farms under uncertaintynb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.rights.holder© 2017 The Author(s). Published by Elsevier Ltd.nb_NO
dc.source.pagenumber531-538nb_NO
dc.source.volume137nb_NO
dc.source.journalEnergy Procedianb_NO
dc.identifier.doi10.1016/j.egypro.2017.10.382
dc.identifier.cristin1533274
cristin.unitcode7401,90,11,0
cristin.unitcode7566,7,0,0
cristin.unitnameAnvendt matematikk
cristin.unitnameMaritim
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
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