DocumentCode
1921233
Title
Short- Term Electric Load Forecasting Using Neural Networks
Author
Ramezani, Maryam ; Falaghi, Hamid ; Haghifam, Mahmood-Reza ; Shahryari, Gholam Ali
Author_Institution
Dept. of Electr. Eng., Tarbiat Modarres Univ., Tehran
Volume
2
fYear
2005
fDate
21-24 Nov. 2005
Firstpage
1525
Lastpage
1528
Abstract
Artificial neural network (ANN) techniques have been recently suggested for short term electric load forecasting by a large number of researchers. This work studies the applicability of this kind of models. The work is performed for a real forecasting application. The proposed models are capable of forecasting the next 24 hour load profile, the next hour load and the next day peak load. The inputs to the ANN models are load profiles and weather information. The ANN load forecasting models are trained on historical data that obtained from a real HV/MV substation in south of Iran. Final results indicate average errors of developed models and prove that these models can be applied to the prediction of load in real case
Keywords
load forecasting; neural nets; power engineering computing; ANN model; artificial neural network; historical data training; load prediction; load profile; short term electric load forecasting; substation; weather information; Artificial neural networks; Economic forecasting; Load forecasting; Load modeling; Neural networks; Power system modeling; Power system planning; Power system security; Predictive models; Weather forecasting; Artificial Neural Networks; Multi-Layer Perceptron (MLP) Neural Networks; Short-Term Electric Load Forecasting (STLF);
fLanguage
English
Publisher
ieee
Conference_Titel
Computer as a Tool, 2005. EUROCON 2005.The International Conference on
Conference_Location
Belgrade
Print_ISBN
1-4244-0049-X
Type
conf
DOI
10.1109/EURCON.2005.1630255
Filename
1630255
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