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Memorias de investigación
Research Publications in journals:
Multivariate exponential smoothing and dynamic factor model applied to hourly electricity price analysis
Year:2014
Research Areas
  • Statistics
Information
Abstract
Thanks to its very simple recursive computing scheme, exponential smoothing has become a popular technique to forecast time series. In this work we show the advantages of its multivariate version and present some properties of the model which allows us to perform a dynamic factor analysis. This analysis leads to a simple methodology to reduce the number of parameters (useful when the dimension of observations is large) via a linear transformation that decomposes the multivariate process into independent univariate exponential smoothing processes, characterized by a single smoothing parameter that goes from zero (white noise process) to one (random walk process). A computer implementation of the EM algorithm has been built for the maximum likelihood estimation of the models. The practicality of the method is demonstrated by its application to hourly electricity price predictions in some day-ahead markets, such as Omel, Powernext, and Nord Pool markets, whose forecasts are given as examples. This paper has supplementary material online.
International
Si
JCR
Si
Title
Technometrics
ISBN
0040-1706
Impact factor JCR
1,424
Impact info
Datos JCR del año 2012
Volume
--
10.1080/00401706.2013.860920
Journal number
--
From page
--
To page
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Month
SIN MES
Ranking
26/117 STATISTIC and PROBABILITY
Participants
  • Autor: Jaime Carpio Huertas (UPM)
  • Autor: Jesus Juan Ruiz (UPM)
  • Autor: Damián López (U. Politécnica de Cartagena)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Estadística computacional y Modelado estocástico
  • Departamento: Ingeniería Energética
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