Data Analytics and Artificial Intelligence Applied to the Energy Transition. Galapagos case study
| dc.contributor.affiliation | Departamento de Organización de Empresas | |
| dc.contributor.affiliation | Instituto Universitario Mixto de Tecnología de Informática | |
| dc.contributor.affiliation | Escuela Técnica Superior de Ingeniería de Telecomunicación | |
| dc.contributor.affiliation | Grupo de Integración de Tecnologías de Información en las Organizaciones. ITIO | |
| dc.contributor.author | Icaza, Daniel | es_ES |
| dc.contributor.author | González-Ladrón-de-Guevara, Fernando | |
| dc.date.accessioned | 2024-12-11T12:09:53Z | |
| dc.date.available | 2024-12-11T12:09:53Z | |
| dc.date.issued | 2024-05-29 | es_ES |
| dc.description.abstract | [EN] For this research work, hybrid wind-photovoltaic systems were considered as primary sources of renewable energy that take advantage of wind speed and solar radiation and contribute to the energy transition of the Galapagos Islands. An approach is provided on the usefulness of artificial intelligence as support tools for the design of the sites in which energy plants should be implemented. The analysis focuses on identifying the available energy potentials through mapping and identification of the behavior patterns of the variables of both solar radiation and wind speeds essential for the transition process that is intended to be carried out in the Galapagos Islands. As a result, 36 possible useful sites for this transition process have been identified. | en_EN |
| dc.description.accrualMethod | S | es_ES |
| dc.description.bibliographicCitation | Icaza, D.; González-Ladrón-De-Guevara, F. (2024). Data Analytics and Artificial Intelligence Applied to the Energy Transition. Galapagos case study. IEEE Xplore. 753-760. https://doi.org/10.1109/icSmartGrid61824.2024.10578129 | es_ES |
| dc.description.upvformatpfin | 760 | es_ES |
| dc.description.upvformatpinicio | 753 | es_ES |
| dc.identifier.doi | 10.1109/icSmartGrid61824.2024.10578129 | es_ES |
| dc.identifier.isbn | 979-8-3503-6161-2 | es_ES |
| dc.identifier.uri | https://riunet.upv.es/handle/10251/212829 | |
| dc.language | Inglés | es_ES |
| dc.publisher | IEEE Xplore | es_ES |
| dc.relation.conferencedate | Mayo 27-29,2024 | es_ES |
| dc.relation.conferencename | 12th International Conference on Smart Grid (icSmartGrid 2024) | es_ES |
| dc.relation.conferenceplace | Setúbal, Portugal | es_ES |
| dc.relation.ispartof | 2024 12th International Conference on Smart Grid (icSmartGrid) | es_ES |
| dc.relation.pasarela | S\535107 | es_ES |
| dc.relation.publisherversion | https://doi.org/10.1109/icSmartGrid61824.2024.10578129 | es_ES |
| dc.rights | Reserva de todos los derechos | es_ES |
| dc.rights.accessRights | Cerrado | es_ES |
| dc.subject | Renewable energy | es_ES |
| dc.subject | Energy transition | es_ES |
| dc.subject | Simulation | es_ES |
| dc.subject | Planning | es_ES |
| dc.subject | Artificial intelligence | es_ES |
| dc.subject | Galapagos | es_ES |
| dc.subject.classification | ORGANIZACION DE EMPRESAS | es_ES |
| dc.title | Data Analytics and Artificial Intelligence Applied to the Energy Transition. Galapagos case study | es_ES |
| dc.type | Comunicación en congreso | es_ES |
| dc.type | Capítulo de libro | es_ES |
| dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
| dspace.entity.type | Publication | |
| person.identifier | 10314 | |
| person.identifier.orcid | 0000-0002-2617-1559 | |
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| relation.isAuthorOfPublication.latestForDiscovery | da670082-ee9a-4d1e-b492-7ff368469f90 | |
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| upv.uuid | 1ae39bfa-e0d0-410f-976c-4019583c1a62 | es_ES |
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