DocumentCode :
3184604
Title :
Forecasting Turkey´s short term hourly load with artificial neural networks
Author :
Bilgic, Mustafa ; Girep, C.P. ; Aslanoglu, S.Y. ; Aydinalp-Koksal, M.
Author_Institution :
Dept. of Environ. Eng., Hacettepe Univ., Ankara, Turkey
fYear :
2010
fDate :
March 29 2010-April 1 2010
Firstpage :
1
Lastpage :
5
Abstract :
Short term load forecasting (STLF) is necessary for economic and reliable timely information to operate an energy system and secure electricity. In this study, STLF systems were developed for nine load distribution regions of Turkey using artificial neural networks (ANN) approach. To our knowledge this is the first study that estimated the short term hourly load of all load distribution regions of Turkey with specific temperature data. The mean average percent error of total hourly load forecast for Turkey is found as 1.81%.
Keywords :
artificial intelligence; load forecasting; neural nets; power engineering computing; Turkey short term hourly load forecasting; artificial neural network approach; energy system; load distribution regions; Short term load forecasting; artificial neural networks;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Developments in Power System Protection (DPSP 2010). Managing the Change, 10th IET International Conference on
Conference_Location :
Manchester
Type :
conf
DOI :
10.1049/cp.2010.0341
Filename :
5522198
Link To Document :
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