Title :
Artificial neural network based short-term load forecasting
Author :
Munkhjargal, S. ; Manusov, V.Z.
Author_Institution :
Novosibirsk State Tech. Univ., Russia
fDate :
26 June-3 July 2004
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;
Conference_Titel :
Science and Technology, 2004. KORUS 2004. Proceedings. The 8th Russian-Korean International Symposium on
Print_ISBN :
0-7803-8383-4
DOI :
10.1109/KORUS.2004.1555339
