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Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.author | Batlle López, Carlos | es-ES |
dc.contributor.author | Barquín Gil, Julián | es-ES |
dc.date.accessioned | 2016-05-23T03:06:58Z | - |
dc.date.available | 2016-05-23T03:06:58Z | - |
dc.date.issued | 2004-05-01 | es_ES |
dc.identifier.issn | 0142-0615 | es_ES |
dc.identifier.uri | https:doi.org10.1016j.ijepes.2003.10.007 | es_ES |
dc.description | Artículos en revistas | es_ES |
dc.description.abstract | es-ES | |
dc.description.abstract | This paper presents a fuel prices scenario generator in the frame of a simulation tool developed to support risk analysis in a competitive electricity environment. The tool feeds different exogenous risk factors to a wholesale electricity market model to perform a statistical analysis of the results. As the different fuel series that are studied, such as the oil or gas ones, present stochastic volatility and strong correlation among them, a multivariate Generalized Autoregressive Conditional Heteroskedastic model has been designed in order to allow the generation of future fuel prices paths. The model makes use of a decomposition method to simplify the consideration of the multidimensional conditional covariance. An example of its application with real data is also presented. | en-GB |
dc.format.mimetype | application/pdf | es_ES |
dc.language.iso | en-GB | es_ES |
dc.rights | es_ES | |
dc.rights.uri | es_ES | |
dc.source | Revista: International Journal of Electrical Power & Energy Systems, Periodo: 1, Volumen: online, Número: 4, Página inicial: 273, Página final: 280 | es_ES |
dc.subject.other | Instituto de Investigación Tecnológica (IIT) | es_ES |
dc.title | Fuel prices scenario generation based on a multivariate GARCH model for risk analysis in a wholesale electricity market | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.description.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.rights.accessRights | info:eu-repo/semantics/restrictedAccess | es_ES |
dc.keywords | es-ES | |
dc.keywords | Fuels; Monte Carlo methods; Power system modeling; Risk analysis; Stochastic processes | en-GB |
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