Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Variable importance Assessment and prediction using regression trees: Application to electricity markets
Year:2014
Research Areas
  • Statistics,
  • Engineering
Information
Abstract
The purpose of this paper is electricity price forecasting through regression tree methods. Electricity price forecasting has become the focus of considerable interest in a deregulated energy market. It is essential for suppliers and buyers to rely on reasonable forecasts for the elaboration of bidding strategies to mitigate losses and increase benefits. Here, three forms of regression tree models have been applied: CART, Bagging and Random Forests, which have been used in two directions: first, to identify the variables dominating the marginal price of the commodity and second, for short-run (one hour ahead and day ahead) electricity price forecasting for the Spanish-Iberian Market.
International
Si
Congress
7Th International Conference of the ERCIM WG on Computational & Methodological Statistics ( ERCIM 2014)
960
Place
Pisa
Reviewers
Si
ISBN/ISSN
978-84-937822-4-5
Start Date
05/12/2014
End Date
08/12/2014
From page
1
To page
12
Conference Proceedings of the ERCIM WG
Participants
  • Autor: M. Camino Gonzalez Fernandez (UPM)
  • Autor: Jose Manuel Mira Mcwilliams (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Estadística computacional y Modelado estocástico
  • Centro o Instituto I+D+i: Instituto Universitario de Investigación del Automóvil (INSIA)
  • Departamento: Ingeniería de Organización, Administración de Empresas y Estadística
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