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dc.contributor.authorSáenz Aguirre, Aitor
dc.contributor.authorSáenz Aguirre, Jon ORCID
dc.contributor.authorUlazia Manterola, Alain ORCID
dc.contributor.authorIbarra Berastegi, Gabriel
dc.date.accessioned2022-01-24T09:16:08Z
dc.date.available2022-01-24T09:16:08Z
dc.date.issued2022-01-01
dc.identifier.citationEnergy Conversion and Management 251 : (2022) // Article ID 114914es_ES
dc.identifier.issn0196-8904
dc.identifier.issn1879-2227
dc.identifier.urihttp://hdl.handle.net/10810/55119
dc.description.abstract[EN] The most profitable offshore energy resources are usually found away from the coast. Nevertheless, the accessibility and grid integration in those areas are more complicated. To avoid this problematic, large scale hydrogen production is being promoted for far offshore applications. The main objective of this paper is to analyze the ability of wave energy converters to maximize hydrogen production in hybrid wind and wave far offshore farms. To that end, wind and wave resource data are obtained from ERA5 for different locations in the Atlantic ocean and a Maximum Covariance Analysis is proposed for the selection of the most representative locations. Furthermore, the suitability of different sized wave energy converters for auxiliary hydrogen production in the far offshore wind farms is also analysed. On that account, the hydrodynamic parameters of the oscillating bodies are obtained via simulations with a Boundary Element Method based code and their operation is modelled using the software tool Matlab. The combination of both methodologies enables to perform a realistic assessment of the contribution of the wave energy converters to the hydrogen generation of an hybrid energy farm, especially during those periods when the wind turbines would be stopped due to the variability of the wind. The obtained results show a considerable hydrogen generation capacity of the wave energy converters, up to 6.28% of the wind based generation, which could remarkably improve the efficiency of the far offshore farm and bring important economical profit. Wave energy converters are observed to be most profitable in those farms with low covariance between wind and waves, where the disconnection times of the wind turbines are prone to be more prolonged but the wave energy is still usable. In such cases, a maximum of 101.12 h of equivalent rated production of the wind turbine has been calculated to be recovered by the wave energy converters.es_ES
dc.description.sponsorshipThis paper is part of project PID2020-116153RB-I00 funded by MCIN/AEI/ 10.13039/501100011033. Authors also acknowledge financial support by the University of the Basque Country under the contract (UPV/EHU, GIU20/008).es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relationinfo:eu-repo/grantAgreement/MICINN/PID2020-116153RB-I00es_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectfar offshorees_ES
dc.subjecthydrogen productiones_ES
dc.subjectwave energyes_ES
dc.subjectwind energyes_ES
dc.subjectpoint absorberes_ES
dc.subjectERA5es_ES
dc.subjectmaximum covariance analysises_ES
dc.subjectfluid mechanicses_ES
dc.titleOptimal strategies of deployment of far offshore co-located wind-wave energy farmses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)es_ES
dc.rights.holderAtribución 3.0 España*
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0196890421010906?via%3Dihubes_ES
dc.identifier.doi10.1016/j.enconman.2021.114914
dc.departamentoesFísicaes_ES
dc.departamentoesIngeniería Energéticaes_ES
dc.departamentoeuEnergia Ingenieritzaes_ES
dc.departamentoeuFisikaes_ES


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© 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Except where otherwise noted, this item's license is described as © 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)