MISC

2009年

Next day price forecasting in deregulated market by combination of artificial neural network and ARIMA time series models

IEEJ Transactions on Power and Energy
  • Phatchakorn Areekul
  • ,
  • Tomonobu Senjyu
  • ,
  • Naomitsu Urasaki
  • ,
  • Atsushi Yona

129
10
開始ページ
1267
終了ページ
1274
記述言語
英語
掲載種別
DOI
10.1541/ieejpes.129.1267

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. © 2009 The Institute of Electrical Engineers of Japan.

リンク情報
DOI
https://doi.org/10.1541/ieejpes.129.1267
ID情報
  • DOI : 10.1541/ieejpes.129.1267
  • ISSN : 0385-4213
  • ISSN : 1348-8147
  • SCOPUS ID : 70450207418

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