DocumentCode
2872317
Title
The local power demand estimation based on artificial neural network technique
Author
Kiliç, O. ; Attar, P. ; Yumurtaci, R. ; Tanriöven, M.
Author_Institution
Dept. of Electr. Eng., Yildiz Univ., Istanbul, Turkey
Volume
2
fYear
1998
fDate
18-20 May 1998
Firstpage
988
Abstract
The demand to electrical energy increases day by day. It is very important to reflect this increasing demand accurately to power plant planning. ANN technique can be effectively used in load forecasting. In this paper, ANN load forecasting is performed by using some nonlinear input parameters such as temperature, humidity, rain conditions. Real electrical data obtained for the national grid and meteorological parameters are used in the presented application
Keywords
load forecasting; neural nets; power system analysis computing; artificial neural network; electrical data; electrical energy; humidity; load forecasting; local power demand estimation; meteorological parameters; national grid; nonlinear input parameters; power plant planning; rain; temperature; Artificial neural networks; Load forecasting; Neural networks; Neurons; Power demand; Power generation; Power generation planning; Power system modeling; Power system planning; Predictive models;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrotechnical Conference, 1998. MELECON 98., 9th Mediterranean
Conference_Location
Tel-Aviv
Print_ISBN
0-7803-3879-0
Type
conf
DOI
10.1109/MELCON.1998.699376
Filename
699376
Link To Document