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dc.contributor.authorRinaldi, G
dc.date.accessioned2019-02-04T09:48:22Z
dc.date.issued2019-02-04
dc.description.abstractOffshore renewable devices hold a large potential as renewable energy sources, but their deployment costs are still too high compared to those of other technologies. Operation and maintenance, as well as management of the assets, are main contributors to the overall costs of the projects, and decision-support tools in this area are required to decrease the final cost of energy.\\ In this thesis a complete characterisation and optimisation framework for the operation, maintenance and assets management of an offshore renewable farm is presented. The methodology uses known approaches, based on Monte Carlo simulation for the characterisation of the key performance indicators of the offshore renewable farm, and genetic algorithms as a search heuristic for the proposal of improved strategies. These methods, coupled in an integrated framework, constitute a novel and valuable tool to support the decision-making process in this area. The methods developed consider multiple aspects for the accurate description of the problem, including considerations on the reliability of the devices and limitations on the offshore operations dictated by the properties of the maintenance assets. Mechanisms and constraints that influence the maintenance procedures are considered and used to determine the optimal strategy. The models are flexible over a range of offshore renewable technologies, and adaptable to different offshore farm sizes and layouts, as well as maintenance assets and configurations of the devices. The approaches presented demonstrate the potential for cost reduction in the operation and maintenance strategy selection, and highlight the importance of computational tools to improve the profitability of a project while ensuring that satisfactory levels of availability and reliability are preserved. Three case studies to show the benefits of application of such methodologies, as well as the validity of their implementation, are provided. Areas for further development are identified, and suggestions to improve the effectiveness of decision-making tools for the assets management of offshore renewable technologies are provided.en_GB
dc.description.sponsorshipEuropean Commissionen_GB
dc.description.sponsorshipMojo Ocean Dynamics Ltd. T/A Mojo Maritime Ltden_GB
dc.identifier.grantnumber607656en_GB
dc.identifier.urihttp://hdl.handle.net/10871/35702
dc.publisherUniversity of Exeteren_GB
dc.subjectOperation and maintenanceen_GB
dc.subjectReliabilityen_GB
dc.subjectOffshore renewableen_GB
dc.subjectDecision-makingen_GB
dc.subjectOptimizationen_GB
dc.subjectGenetic algorithmen_GB
dc.subjectMonte Carloen_GB
dc.titleAn integrated operation and maintenance framework for offshore renewable energyen_GB
dc.typeThesis or dissertationen_GB
dc.contributor.advisorJohanning, Len_GB
dc.publisher.departmentRenewable Energyen_GB
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
dc.type.degreetitleDoctor of Philosophy in Renewable Energyen_GB
dc.type.qualificationlevelDoctoralen_GB
dc.type.qualificationnameDoctoral Thesisen_GB
dcterms.dateAccepted2019-02-04
exeter.funder::European Commissionen_GB
exeter.funder::Mojo Ocean Dynamics Ltd. T/A Mojo Maritime Ltden_GB
rioxxterms.versionNAen_GB
rioxxterms.licenseref.startdate2018-10-22
rioxxterms.typeThesisen_GB
refterms.dateFOA2019-06-03T08:04:46Z


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