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Multi-Attribute forecast of the price in the Iberian Electricity Market

dc.contributor.authorPeres, Gonçalo
dc.contributor.authorTallón Ballesteros, Antonio Javier
dc.contributor.authorCavique, Luís
dc.date.accessioned2021-12-22T17:02:28Z
dc.date.available2021-12-22T17:02:28Z
dc.date.issued2021
dc.description.abstractElectricity has been acquiring a more significant presence in our lives, and it is estimated that the future AQ1 will be increasingly electric. Nowadays, we have access to enormous amounts of data that do not have much-added value if they cannot support decision-making or plan systems in advance and correctly. Forecasts are vital tools to support decision-making. We believe it is possible to resort to open data available on the Internet to make electricity price forecasts that - decision-makers can use in the sector. In this work, we study the multi-attribute hourly forecast of the electricity price in MIBEL (Iberian electricity market) for the 24 h of the following day, using open data. The realization of the multi-attribute predictions fell on the TIM (‘Tangent Information Modeler’) tool with AutoML (‘Auto Machine Learning’) capabilities. The TOPSIS (‘technique for order of preference by similarity to ideal solution’) decision support technique was used to analyze the results.pt_PT
dc.description.sponsorshipThis work has been partially subsidized by these projects: TIN2017-88209- C2-2-R (Spanish Inter-Ministerial Commission of Science and Technology), FEDER funds and US-1263341 (Junta de Andalucía).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1007/978-3-030-91608-4_48pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.2/11543
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.subjectEconomic predictionpt_PT
dc.subjectForecastingpt_PT
dc.subjectIberian electricity market (MIBEL)pt_PT
dc.subjectAuto machine learningpt_PT
dc.subjectMulti-attribute decisionpt_PT
dc.titleMulti-Attribute forecast of the price in the Iberian Electricity Marketpt_PT
dc.typebook part
dspace.entity.typePublication
oaire.citation.endPage492pt_PT
oaire.citation.startPage485pt_PT
oaire.citation.titleIntelligent Data Engineering and Automated Learning – IDEAL 2021pt_PT
oaire.citation.volume13113pt_PT
person.familyNamePeres
person.familyNameTallón Ballesteros
person.familyNameCavique
person.givenNameGonçalo
person.givenNameAntonio Javier
person.givenNameLuís
person.identifier.ciencia-id911E-84AC-3956
person.identifier.orcid0000-0001-7410-6236
person.identifier.orcid0000-0002-9699-1894
person.identifier.orcid0000-0002-5590-1493
person.identifier.scopus-author-id36192484400
rcaap.rightsopenAccesspt_PT
rcaap.typebookPartpt_PT
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relation.isAuthorOfPublicationdafdc6ef-a36d-4a85-92d2-6140bd1082cd
relation.isAuthorOfPublication40906a16-46a2-42f1-b26d-7db7012294ee
relation.isAuthorOfPublication.latestForDiscoverydda0dfe1-5a3d-4bb3-9895-ce55975af325

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