DocumentCode :
3509575
Title :
An artificial neural network based short term load forecasting with special tuning for weekends and seasonal changes
Author :
Moharari, Nadar S. ; Debs, Atif S.
Author_Institution :
Sch. of Electr. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
fYear :
1993
fDate :
1993
Firstpage :
279
Lastpage :
283
Abstract :
The artificial neural network (ANN) technique is utilized for power electric load forecasting using the backpropagation algorithm developed by the authors. The major contribution of this work is the ability to forecast the power electric load for weekends and holidays as well as weekdays with a relatively small training set. In addition the effect of seasonal change in load pattern can be tracked down. Their approach is to introduce three different sets of inputs to the ANN in order to follow the load pattern, weather pattern, seasonal factors and to consider special events like weekends and holidays.
Keywords :
backpropagation; load forecasting; neural nets; power engineering computing; power systems; AI; artificial neural network; backpropagation algorithm; power engineering computing; seasonal changes; short term load forecasting; training; tuning; weather pattern; weekends; Artificial neural networks; Backpropagation algorithms; Fuels; Load forecasting; Maintenance; Neurons; Power system reliability; Terminology; Testing; Weather forecasting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks to Power Systems, 1993. ANNPS '93., Proceedings of the Second International Forum on Applications of
Conference_Location :
Yokohama, Japan
Print_ISBN :
0-7803-1217-1
Type :
conf
DOI :
10.1109/ANN.1993.264334
Filename :
264334
Link To Document :
بازگشت