DocumentCode
445667
Title
Artificial neural network based short-term load forecasting
Author
Munkhjargal, S. ; Manusov, V.Z.
Author_Institution
Novosibirsk State Tech. Univ., Russia
Volume
1
fYear
2004
fDate
26 June-3 July 2004
Firstpage
262
Abstract
This paper presents the development of an ANN based short-time load forecasting for a power system. Problems encountered in the data preparation, network structure definition, and suggested solutions are discussed. The proposed model can provide 1 to 24-steps ahead load forecast. Obtained results from extensive testing on the Mongolian power system network confirm the validity of the developed approach.
Keywords
load forecasting; neural nets; power engineering computing; Mongolian power system network; artificial neural network; short-term load forecasting; Artificial intelligence; Artificial neural networks; Consumer electronics; Electricity supply industry; Interference; Load forecasting; Load modeling; Neural networks; Power system modeling; Predictive models;
fLanguage
English
Publisher
ieee
Conference_Titel
Science and Technology, 2004. KORUS 2004. Proceedings. The 8th Russian-Korean International Symposium on
Print_ISBN
0-7803-8383-4
Type
conf
DOI
10.1109/KORUS.2004.1555339
Filename
1555339
Link To Document