dc.contributor.author | Peres, Gonçalo | |
dc.contributor.author | Tallón Ballesteros, Antonio Javier | |
dc.contributor.author | Cavique, Luís | |
dc.date.accessioned | 2021-12-22T17:02:28Z | |
dc.date.available | 2021-12-22T17:02:28Z | |
dc.date.issued | 2021 | |
dc.description.abstract | Electricity 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.sponsorship | This 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.version | info:eu-repo/semantics/publishedVersion | pt_PT |
dc.identifier.doi | 10.1007/978-3-030-91608-4_48 | pt_PT |
dc.identifier.uri | http://hdl.handle.net/10400.2/11543 | |
dc.language.iso | eng | pt_PT |
dc.peerreviewed | yes | pt_PT |
dc.subject | Economic prediction | pt_PT |
dc.subject | Forecasting | pt_PT |
dc.subject | Iberian electricity market (MIBEL) | pt_PT |
dc.subject | Auto machine learning | pt_PT |
dc.subject | Multi-attribute decision | pt_PT |
dc.title | Multi-Attribute forecast of the price in the Iberian Electricity Market | pt_PT |
dc.type | book part | |
dspace.entity.type | Publication | |
oaire.citation.endPage | 492 | pt_PT |
oaire.citation.startPage | 485 | pt_PT |
oaire.citation.title | Intelligent Data Engineering and Automated Learning – IDEAL 2021 | pt_PT |
oaire.citation.volume | 13113 | pt_PT |
person.familyName | Peres | |
person.familyName | Tallón Ballesteros | |
person.familyName | Cavique | |
person.givenName | Gonçalo | |
person.givenName | Antonio Javier | |
person.givenName | Luís | |
person.identifier.ciencia-id | 911E-84AC-3956 | |
person.identifier.orcid | 0000-0001-7410-6236 | |
person.identifier.orcid | 0000-0002-9699-1894 | |
person.identifier.orcid | 0000-0002-5590-1493 | |
person.identifier.scopus-author-id | 36192484400 | |
rcaap.rights | openAccess | pt_PT |
rcaap.type | bookPart | pt_PT |
relation.isAuthorOfPublication | dda0dfe1-5a3d-4bb3-9895-ce55975af325 | |
relation.isAuthorOfPublication | dafdc6ef-a36d-4a85-92d2-6140bd1082cd | |
relation.isAuthorOfPublication | 40906a16-46a2-42f1-b26d-7db7012294ee | |
relation.isAuthorOfPublication.latestForDiscovery | dda0dfe1-5a3d-4bb3-9895-ce55975af325 |
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