Forecasting electricity load demand: analysis of the 2001 rationing period in Brazil
This paper studies the electricity load demand behavior during the 2001 rationing period, which was implemented because of the Brazilian energetic crisis. The hourly data refers to a utility situated in the southeast of the country. We use the model proposed by Soares and Souza (2003), making use of generalized long memory to model the seasonal behavior of the load. The rationing period is shown to have imposed a structural break in the series, decreasing the load at about 20%. Even so, the forecast accuracy is decreased only marginally, and the forecasts rapidly readapt to the new situation. The forecast errors from this model also permit verifying the public response to pieces of information released regarding the crisis.
|Date of creation:||31 Jul 2003|
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- Soares, Lacir Jorge & Souza, Leonardo Rocha, 2006.
"Forecasting electricity demand using generalized long memory,"
International Journal of Forecasting,
Elsevier, vol. 22(1), pages 17-28.
- Soares, Lacir Jorge & Souza, Leonardo Rocha, 2003. "Forecasting electricity demand using generalized long memory," FGV/EPGE Economics Working Papers (Ensaios Economicos da EPGE) 486, FGV/EPGE - Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
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- Laurent Ferrara & Dominique Guegan, 1999. "Estimation and Applications of Gegenbauer Processes," Working Papers 99-27, Center for Research in Economics and Statistics.
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- 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.
- Ray, Bonnie K., 1993. "Long-range forecasting of IBM product revenues using a seasonal fractionally differenced ARMA model," International Journal of Forecasting, Elsevier, vol. 9(2), pages 255-269, August. Full references (including those not matched with items on IDEAS)
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