DocumentCode
1837362
Title
EM estimation of multivariate dynamic models for predicting electricity prices
Author
López, Damián ; Juan, Jesus ; Carpio, Jaime
Author_Institution
Univ. Politec. de Madrid, Madrid, Spain
fYear
2010
fDate
23-25 June 2010
Firstpage
1
Lastpage
6
Abstract
In order to make short-term predictions of electricity prices, linear dynamic models in their state-space formulation have been studied. A computer implementation of the EM (Expectation - Maximization) algorithm has been made for maximum likelihood estimation for a Multivariate EWMA model, (exponentially smoothing). In this approach the problem includes a large number of parameters to be estimated as we have implemented the possibility of eliminating superfluous parameters. Finally, we present the results of the hourly spot price forecasts in Powernext, Nord Pool and OMEL markets.
Keywords
expectation-maximisation algorithm; power markets; pricing; Nord Pool markets; OMEL markets; Powernext markets; electricity prices prediction; expectation-maximization algorithm; exponentially smoothing; linear dynamic models; maximum likelihood estimation; multivariate EWMA model; multivariate dynamic models; state-space formulation; Biological system modeling; Electricity; Predictive models; Forecasting; moving average processes; state space methods; time series;
fLanguage
English
Publisher
ieee
Conference_Titel
Energy Market (EEM), 2010 7th International Conference on the European
Conference_Location
Madrid
Print_ISBN
978-1-4244-6838-6
Type
conf
DOI
10.1109/EEM.2010.5558693
Filename
5558693
Link To Document