A Neural Network Approach to m-Daily-Ahead Electricity Price Prediction

  • Hsiao-Tien Pao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)


This paper proposes an artificial neural network (ANN) model to predict m-daily-ahead electricity price using direct forecasting approach on European Energy Exchange (EEX) market. The most important characteristic of this model is the single output node for m-period-ahead forecasts. The potentials of ANNs are investigated by employing cross-validation schemes. Out-of-sample performance evaluated with three criteria across five forecasting horizons shows that the proposed ANNs are more robust multi-step-ahead forecasting method than autoregressive error models (AUTOREG). Moreover, ANN predictions are quite accurate even when the length of forecast horizon is relatively short or long.


Artificial Neural Network Model Electricity Price Input Node ARIMA Model Neural Network Approach 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hsiao-Tien Pao
    • 1
  1. 1.Department of Management ScienceNational Chiao Tung UniversityTaiwan

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