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ORCID: https://orcid.org/0000-0001-9405-5384
(2013).
A dynamic factor model for mid-term forecasting of wind power generation.
En: "10th International Conference on the European Energy Market (EEM)", 27/05/2013 - 31/05/2013, Estocolmo (Suecia). ISBN 978-1-4799-2008-2. pp. 1-8.
| Título: | A dynamic factor model for mid-term forecasting of wind power generation |
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| Autor/es: |
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| Tipo de Documento: | Ponencia en Congreso o Jornada (Artículo) |
| Título del Evento: | 10th International Conference on the European Energy Market (EEM) |
| Fechas del Evento: | 27/05/2013 - 31/05/2013 |
| Lugar del Evento: | Estocolmo (Suecia) |
| Título del Libro: | 10th International Conference on the European Energy Market (EEM) |
| Fecha: | 2013 |
| ISBN: | 978-1-4799-2008-2 |
| Materias: | |
| ODS: | |
| Palabras Clave Informales: | Multivariate Time Series, Unobserved Components, Dimensionality Reduction, Forecasting, Wind Power Production. |
| Escuela: | E.T.S.I. Industriales (UPM) |
| Departamento: | Ingeniería de Organización, Administración de Empresas y Estadística |
| Licencias Creative Commons: | Reconocimiento - Sin obra derivada - No comercial |
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The main objective of this paper is the development and application of multivariate time series models for forecasting aggregated wind power production in a country or region. Nowadays, in Spain, Denmark or Germany there is an increasing penetration of this kind of renewable energy, somehow to reduce energy dependence on the exterior, but always linked with the increaseand uncertainty affecting the prices of fossil fuels. The disposal of accurate predictions of wind power generation is a crucial task both for the System Operator as well as for all the agents of the Market. However, the vast majority of works rarely onsider forecasting horizons longer than 48 hours, although they are of interest for the system planning and operation. In this paper we use Dynamic Factor Analysis, adapting and modifying it conveniently, to reach our aim: the computation of accurate forecasts for the aggregated wind power production in a country for a forecasting horizon as long as possible, particularly up to 60 days (2 months). We illustrate this methodology and the results obtained for real data in the leading country in wind power production: Denmark
| ID de Registro: | 33275 |
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| Identificador DC: | https://oa.upm.es/33275/ |
| Identificador OAI: | oai:oa.upm.es:33275 |
| URL Oficial: | http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp... |
| Depositado por: | Memoria Investigacion |
| Depositado el: | 23 Feb 2015 17:34 |
| Ultima Modificación: | 08 Feb 2023 09:16 |
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