Short-term forecasting of electricity prices with a computationally efficient hybrid approach

dc.contributor.authorMarcos Peirotén, Rodrigo Alejandro dees-ES
dc.contributor.authorBello Morales, Antonioes-ES
dc.contributor.authorReneses Guillén, Javieres-ES
dc.date.accessioned2017-04-21T03:07:19Z
dc.date.available2017-04-21T03:07:19Z
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.description.versioninfo:eu-repo/semantics/draftes_ES
dc.format.mimetypeapplication/pdfes_ES
dc.identifier.urihttp://hdl.handle.net/11531/18132
dc.keywordses-ES
dc.keywordsEconometric Models, Electricity Markets, Fundamental Models, Hybrid Models, Short-Term Forecastingen-GB
dc.language.isoen-GBes_ES
dc.rightses_ES
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses_ES
dc.rights.uries_ES
dc.titleShort-term forecasting of electricity prices with a computationally efficient hybrid approaches_ES
dc.typeinfo:eu-repo/semantics/workingPaperes_ES

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