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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- 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.
- Josu Arteche & Peter M. Robinson, 1998. "Seasonal and cyclical long memory," LSE Research Online Documents on Economics 2241, London School of Economics and Political Science, LSE Library.
- Laurent Ferrara & Dominique Guegan, 1999. "Estimation and Applications of Gegenbauer Processes," Working Papers 99-27, Centre de Recherche en Economie et Statistique.
- 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.
- Ferrara, Laurent & Guegan, Dominique, 2001.
"Forecasting with k-Factor Gegenbauer Processes: Theory and Applications,"
Journal of Forecasting,
John Wiley & Sons, Ltd., vol. 20(8), pages 581-601, December.
- Laurent Ferrara & Dominique Guegan, 2001. "Forecasting with k-factor Gegenbauer Processes: Theory and Applications," Post-Print halshs-00193667, HAL.
- 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," Economics Working Papers (Ensaios Economicos da EPGE) 486, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
- Armstrong, J. Scott & Collopy, Fred, 1992. "Error measures for generalizing about forecasting methods: Empirical comparisons," International Journal of Forecasting, Elsevier, vol. 8(1), pages 69-80, June.
- repec:crs:wpaper:9927 is not listed on IDEAS
- 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.
- Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
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