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