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A smooth transition periodic autoregressive (STPAR) model for short-term load forecasting

  • Amaral, Luiz Felipe
  • Souza, Reinaldo Castro
  • Stevenson, Maxwell
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    This paper compares the short-term load performance of several forecasting models, including a new class of nonlinear models known as smooth transition periodic autoregressive (STPAR) models. A model building procedure is developed for the STPAR model, along with a linearity test against smooth transition periodic autoregressive behaviour. The predictive ability of the STPAR model is evaluated against alternative load forecasting models using load data from the Australian electricity market.

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    File URL: http://www.sciencedirect.com/science/article/B6V92-4TRR8MR-1/2/618a77b74c0807633c05ea7d1be853f5
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    Article provided by Elsevier in its journal International Journal of Forecasting.

    Volume (Year): 24 (2008)
    Issue (Month): 4 ()
    Pages: 603-615

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    Handle: RePEc:eee:intfor:v:24:y:2008:i:4:p:603-615
    Contact details of provider: Web page: http://www.elsevier.com/locate/ijforecast

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    1. Svec, J. & Stevenson, M., 2007. "Modelling and forecasting temperature based weather derivatives," Global Finance Journal, Elsevier, vol. 18(2), pages 185-204.
    2. Soares, Lacir Jorge & Souza, Leonardo Rocha, 2003. "Forecasting Electricity Demand Using Generalized Long Memory," Economics Working Papers (Ensaios Economicos da EPGE) 486, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
    3. repec:cup:cbooks:9780521565882 is not listed on IDEAS
    4. Eitrheim, Oyvind & Terasvirta, Timo, 1996. "Testing the adequacy of smooth transition autoregressive models," Journal of Econometrics, Elsevier, vol. 74(1), pages 59-75, September.
    5. Fiebig, Denzil G. & Bartels, Robert & Aigner, Dennis J., 1991. "A random coefficient approach to the estimation of residential end-use load profiles," Journal of Econometrics, Elsevier, vol. 50(3), pages 297-327, December.
    6. Franses, Philip Hans & Paap, Richard, 2004. "Periodic Time Series Models," OUP Catalogue, Oxford University Press, number 9780199242030, March.
    7. Taylor, James W. & de Menezes, Lilian M. & McSharry, Patrick E., 2006. "A comparison of univariate methods for forecasting electricity demand up to a day ahead," International Journal of Forecasting, Elsevier, vol. 22(1), pages 1-16.
    8. Joanna Nowicka-Zagrajek & Rafal Weron, 2002. "Modeling electricity loads in California: ARMA models with hyperbolic noise," HSC Research Reports HSC/02/02, Hugo Steinhaus Center, Wroclaw University of Technology.
    9. Taylor, James W., 2006. "Density forecasting for the efficient balancing of the generation and consumption of electricity," International Journal of Forecasting, Elsevier, vol. 22(4), pages 707-724.
    10. Hippert, H.S. & Bunn, D.W. & Souza, R.C., 2005. "Large neural networks for electricity load forecasting: Are they overfitted?," International Journal of Forecasting, Elsevier, vol. 21(3), pages 425-434.
    11. Darbellay, Georges A. & Slama, Marek, 2000. "Forecasting the short-term demand for electricity: Do neural networks stand a better chance?," International Journal of Forecasting, Elsevier, vol. 16(1), pages 71-83.
    12. Smith, Michael, 2000. "Modeling and Short-term Forecasting of New South Wales Electricity System Load," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(4), pages 465-78, October.
    13. Taylor, James W. & Buizza, Roberto, 2003. "Using weather ensemble predictions in electricity demand forecasting," International Journal of Forecasting, Elsevier, vol. 19(1), pages 57-70.
    14. Ramanathan, Ramu & Engle, Robert & Granger, Clive W. J. & Vahid-Araghi, Farshid & Brace, Casey, 1997. "Shorte-run forecasts of electricity loads and peaks," International Journal of Forecasting, Elsevier, vol. 13(2), pages 161-174, June.
    15. Max Stevenson & Maurice Peat, 2000. "Forecasting Australian Unemployment Rates," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 4(1), pages 41-55, March.
    16. repec:cup:cbooks:9780521562607 is not listed on IDEAS
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