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The Performance of Time Series Models to Forecast Short-Term Electricity Demand

  • Park, W.G. (Digital Inclusion Policy Division, NIA) ;
  • Kim, S. (Department of Applied Statistics, Chung-Ang University)
  • Received : 2012.09.25
  • Accepted : 2012.11.06
  • Published : 2012.11.30

Abstract

In this paper, we applied seasonal time series models such as ARIMA, FARIMA, AR-GARCH and Holt-Winters in consideration of seasonality to forecast short-term electricity demand data. The results for performance evaluation on the time series models show that seasonal FARIMA and seasonal Holt-Winters models perform adequately under the criterion of Mean Absolute Percentage Error(MAPE).

Keywords

References

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