IEEJ Transactions on Power and Energy
Online ISSN : 1348-8147
Print ISSN : 0385-4213
ISSN-L : 0385-4213
Paper
Next Day Price Forecasting in Deregulated Market by Combination of Artificial Neural Network and ARIMA Time Series Models
Phatchakorn AreekulTomonobu SenjyuNaomitsu UrasakiAtsushi Yona
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JOURNAL FREE ACCESS

2009 Volume 129 Issue 10 Pages 1267-1274

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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.
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© 2009 by the Institute of Electrical Engineers of Japan
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