A Hybrid Intelligent System for Short and Mid-term Forecasting for the CELPE Distribution Utility

This paper presents the development of a hybrid intelligent system, joining an artificial neural network (ANN) based technique and heuristic rules to adjust the short and mid-term electric load forecasting in the 3, 7, 15, 30, and 45 days ahead. 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 proposed system forecasts a holiday as one Saturday or Sunday based on the specialist's information that analyzes the load behaviors of each holiday. The hybrid intelligent system presented an improvement in the load forecasts in relation to the results achieved by the ANN alone. The program was implemented in MATLAB 7.0 R14.