DocumentCode :
3087305
Title :
Next day price forecasting in deregulated market by combination of Artificial Neural Network and ARIMA time series models
Author :
Areekul, Phatchakorn ; Senjyu, Tomonobu ; Urasaki, Naomitsu ; Yona, Atsushi
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. of the Ryukyus, Nishihara, Japan
fYear :
2010
fDate :
15-17 June 2010
Firstpage :
1451
Lastpage :
1456
Abstract :
Electricity price forecasting is becoming increasingly relevant to power producers and consumers in the new competitive electric power markets, when planning bidding strategies in order to maximize their benefits and utilities, respectively. This paper proposed a method to predict hourly electricity prices for next-day electricity markets by combination methodology of ARIMA and ANN models. The proposed method is examined on the Australian National Electricity Market (NEM), New South Wales regional in year 2006. Comparison of forecasting performance with the proposed ARIMA, ANN and combination (ARIMA-ANN) models are presented. Empirical results indicate that an ARIMA-ANN model can improve the price forecasting accuracy.
Keywords :
autoregressive moving average processes; planning; power engineering computing; power markets; pricing; time series; ARIMA; Australian national electricity market; artificial neural network; autoregressive integrated moving average; deregulated market; electricity price forecasting; next day price forecasting; planning; time series models; Artificial neural networks; Australia; Consumer electronics; Economic forecasting; Electricity supply industry; Load forecasting; Power engineering and energy; Power system modeling; Predictive models; Production; ARIMA; Electricity price forecasting; back-propagation; combination methodology; neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2010 the 5th IEEE Conference on
Conference_Location :
Taichung
Print_ISBN :
978-1-4244-5045-9
Electronic_ISBN :
978-1-4244-5046-6
Type :
conf
DOI :
10.1109/ICIEA.2010.5514828
Filename :
5514828
Link To Document :
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