Title :
Forecasting electricity prices in spot markets — One week horizon approach
Author :
Duarte, A.F. ; Fidalgo, J.N. ; Saraiva, J.T.
Author_Institution :
Efacec Eng. S.A., Porto, Portugal
Abstract :
This paper describes the methodology developed to build estimates of electricity prices having the horizon of one week. This approach uses artificial neural networks and includes a particular treatment of weekends and national holidays as a way to improve the quality of the results. The developed approach was tested using data obtained from the Spanish market operator for the time period of 2006 to 2008. The obtained value of MAPE -Mean Absolute Percentage Error - was 12,62% for workdays and 10,73% for holidays and weekends. The obtained results show that this study has interest to the market agents in question, since realistic forecasting was achieved.
Keywords :
artificial intelligence; forecasting theory; neural nets; power engineering computing; power markets; pricing; Spanish market operator; artificial neural network; electricity price forecasting; mean absolute percentage error; one week horizon approach; spot market; Artificial neural networks; Economic forecasting; Electricity supply industry; Helium; Humans; Mathematical model; Nervous system; Neurons; Power generation; Testing; Artificial Neural Networks; Electricity Markets; Electricity Sector Restructuring; Forecasting Electricity Prices;
Conference_Titel :
PowerTech, 2009 IEEE Bucharest
Conference_Location :
Bucharest
Print_ISBN :
978-1-4244-2234-0
Electronic_ISBN :
978-1-4244-2235-7
DOI :
10.1109/PTC.2009.5282124