A dynamic factor model for mid-term forecasting of wind power generation

García-Martos, Carolina y Sánchez Naranjo, María Jesús (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.

Descripción

Título: A dynamic factor model for mid-term forecasting of wind power generation
Autor/es:
  • García-Martos, Carolina
  • Sánchez Naranjo, María Jesús
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:
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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Resumen

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

Más información

ID de Registro: 33275
Identificador DC: http://oa.upm.es/33275/
Identificador OAI: oai:oa.upm.es:33275
URL Oficial: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6595168&punumber%3D6595168%26filter%3DAND%28p_IS_Number%3A6607268%29%26pageNumber%3D5&pageNumber=6
Depositado por: Memoria Investigacion
Depositado el: 23 Feb 2015 17:34
Ultima Modificación: 19 May 2017 15:36
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