• 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