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dc.contributor.author | Mytilinou, Varvara | es_ES |
dc.contributor.author | Lozano-Mínguez, Estívaliz | es_ES |
dc.contributor.author | Kolios, Athanasios | es_ES |
dc.date.accessioned | 2024-02-07T19:02:37Z | |
dc.date.available | 2024-02-07T19:02:37Z | |
dc.date.issued | 2018-07 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/202404 | |
dc.description.abstract | [EN] This research develops a framework to assist wind energy developers to select the optimum deployment site of a wind farm by considering the Round 3 available zones in the UK. The framework includes optimization techniques, decision-making methods and experts' input in order to support investment decisions. Further, techno-economic evaluation, life cycle costing (LCC) and physical aspects for each location are considered along with experts' opinions to provide deeper insight into the decision-making process. A process on the criteria selection is also presented and seven conflicting criteria are being considered for implementation in the technique for the order of preference by similarity to the ideal solution (TOPSIS) method in order to suggest the optimum location that was produced by the nondominated sorting genetic algorithm (NSGAII). For the given inputs, Seagreen Alpha, near the Isle of May, was found to be the most probable solution, followed by Moray Firth Eastern Development Area 1, near Wick, which demonstrates by example the effectiveness of the newly introduced framework that is also transferable and generic. The outcomes are expected to help stakeholders and decision makers to make better informed and cost-effective decisions under uncertainty when investing in offshore wind energy in the UK. | es_ES |
dc.description.sponsorship | This work was supported by Grant EP/L016303/1 for Cranfield University, Centre for Doctoral Training in Renewable Energy Marine Structures (REMS) (http://www.rems-cdt.ac.uk/) from the UK Engineering and Physical Sciences Research Council (EPSRC). Data underlying this paper can be accessed at https://doi.org/10.17862/cranfield.rd.6292703. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | MDPI AG | es_ES |
dc.relation.ispartof | Energies | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Multi-objective optimization | es_ES |
dc.subject | Nondominated sorting genetic algorithm (NSGA) | es_ES |
dc.subject | Multi-criteria decision making (MCDM) | es_ES |
dc.subject | Technique for the order of preference by similarity to the ideal solution (TOPSIS) | es_ES |
dc.subject | Life cycle cost | es_ES |
dc.subject.classification | MECANICA DE LOS MEDIOS CONTINUOS Y TEORIA DE ESTRUCTURAS | es_ES |
dc.title | A Framework for the Selection of Optimum Offshore Wind Farm Locations for Deployment | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3390/en11071855 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EPSRC//EP%2FL016303%2F1/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros de Caminos, Canales y Puertos - Escola Tècnica Superior d'Enginyers de Camins, Canals i Ports | es_ES |
dc.description.bibliographicCitation | Mytilinou, V.; Lozano-Mínguez, E.; Kolios, A. (2018). A Framework for the Selection of Optimum Offshore Wind Farm Locations for Deployment. Energies. 11(7). https://doi.org/10.3390/en11071855 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3390/en11071855 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 11 | es_ES |
dc.description.issue | 7 | es_ES |
dc.identifier.eissn | 1996-1073 | es_ES |
dc.relation.pasarela | S\367389 | es_ES |
dc.contributor.funder | UK Research and Innovation | es_ES |
dc.contributor.funder | Engineering and Physical Sciences Research Council, Reino Unido | es_ES |