Development of a hybrid intelligent system for electrical load forecasting

  • Authors:

  • Ronaldo R. B. de Aquino;Aida A. Ferreira;Manoel A. Carvalho, Jr.;Milde M. S. Lira;Geane B. Silva;Otoni Nóbrega Neto

  • Affiliations:

  • Federal University of Pernambuco, Recife, PE, Brazil;Federal Center of Technologic Education of Pernambuco, Recife, PE, Brazil;Federal University of Pernambuco, Recife, PE, Brazil;Federal University of Pernambuco, Recife, PE, Brazil;Federal University of Pernambuco, Recife, PE, Brazil;Federal University of Pernambuco, Recife, PE, Brazil

  • Venue:
  • IBERAMIA-SBIA'06 Proceedings of the 2nd international joint conference, and Proceedings of the 10th Ibero-American Conference on AI 18th Brazilian conference on Advances in Artificial Intelligence
  • Year:
  • 2006

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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.