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dc.contributor.authorMarcos Peirotén, Rodrigo Alejandro dees-ES
dc.contributor.authorBello Morales, Antonioes-ES
dc.contributor.authorReneses Guillén, Javieres-ES
dc.date.accessioned2017-12-21T15:52:50Z-
dc.date.available2017-12-21T15:52:50Z-
dc.date.issued2017-06-06es_ES
dc.identifier.urihttp://hdl.handle.net/11531/24706-
dc.descriptionCapítulos en libroses_ES
dc.description.abstractes-ES
dc.description.abstractElectricity price forecasting models are of great importance for market participants due to their considerable volatility, especially in deregulated and competitive contexts. As a result, these models are highly demanded, especially in day-to-day applications, which require not only accurate results, but also fast responsiveness. Taking these needs into account, this work proposes a novel short-term electricity forecasting approach by means of a hybrid model, combining econometric and fundamental methods. In order to validate this work’s proposed method under complex price dynamics, the model has been tested for the Iberian electricity market case, and further verified by comparing its performance with other, more traditional, forecasting models.en-GB
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoen-GBes_ES
dc.publisherTechnische Universität Dresden (Dresde, Alemania)es_ES
dc.rightses_ES
dc.rights.uries_ES
dc.sourceLibro: 14th International Conference on the European Energy Market - EEM17, Página inicial: 1-6, Página final:es_ES
dc.subject.otherInstituto de Investigación Tecnológica (IIT)es_ES
dc.titleShort-term forecasting of electricity prices with a computationally efficient hybrid approaches_ES
dc.typeinfo:eu-repo/semantics/bookPartes_ES
dc.description.versioninfo:eu-repo/semantics/publishedVersiones_ES
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses_ES
dc.keywordses-ES
dc.keywordsEconometric Models, Electricity Markets, Fundamental Models, Hybrid Models, Short-Term Forecastingen-GB
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