Abstract
This paper presents a hybrid intelligent system for electrical load forecast. Artificial Neural Networks (ANN) were combined with Heuristic Rules to create the system. The study was based on load demand data of Energy Company of Pernambuco (CELPE), whose data contain the hourly load consumption in the period from January-2000 until December-2004. The data of hourly consumption of the holidays were eliminated from the file, as well as the data regarding the more critical period of the rationing in Brazil (from May until July 2001). The hybrid intelligent system presented an improvement in the load forecasts in relation to the results achieved by the ANN alone. The system was implemented in MATLAB.
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de Aquino, R.R.B., Ferreira, A.A., Carvalho, M.A., Lira, M.M.S., Silva, G.B., Neto, O.N. (2006). Development of a Hybrid Intelligent System for Electrical Load Forecasting. In: Sichman, J.S., Coelho, H., Rezende, S.O. (eds) Advances in Artificial Intelligence - IBERAMIA-SBIA 2006. IBERAMIA SBIA 2006 2006. Lecture Notes in Computer Science(), vol 4140. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11874850_27
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DOI: https://doi.org/10.1007/11874850_27
Publisher Name: Springer, Berlin, Heidelberg
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