Title :
Enhancing the performances of a basic neural network tool for short-term forecasting of Italian electric load
Author :
Lamedica, R. ; Mazzaro, M. ; Modesto, C. ; Prudenzi, A.
Author_Institution :
Dept. of Electr. Eng., Rome Univ., Italy
Abstract :
In a previous study a basic multilayer perceptron artificial neural network for short-term forecasting of Italian hourly electric load has been implemented. The procedure has permitted adequate forecasting accuracies to be obtained for all the days with normal load conditions. However, the techniques adopted show some accuracy deficiencies while forecasting days with anomalous load conditions due to social factors (vacation periods, holidays, long weekends) and peculiar meteorological conditions as well. The paper illustrates the research activity conducted for enhancing the forecasting performances of the basic artificial neural network during these periods
Keywords :
load forecasting; multilayer perceptrons; power system analysis computing; Italian electric load; Italian hourly electric load; artificial neural network; multilayer perceptron; short-term forecasting; Artificial neural networks; Economic forecasting; Load forecasting; Meteorology; Neural networks; Neurons; Power industry; Predictive models; Social factors; Weather forecasting;
Conference_Titel :
Electrotechnical Conference, 1996. MELECON '96., 8th Mediterranean
Conference_Location :
Bari
Print_ISBN :
0-7803-3109-5
DOI :
10.1109/MELCON.1996.551348