DocumentCode
3227681
Title
Tool for short-term load forecasting in transmission systems based on artificial intelligence techniques
Author
Guirelli, C.R. ; Jardini, J.A. ; Magrini, L.C. ; Yasuoka, J. ; Campos, A.C. ; Bastos, M.
Author_Institution
Escola Politecnica da USP, Brazil
fYear
2004
fDate
8-11 Nov. 2004
Firstpage
243
Lastpage
248
Abstract
This paper analyzes the use of wavelets and artificial intelligence techniques for short-term load forecast of energy transmission systems. Neural networks, fuzzy logic and wavelets have been investigated so as to determine the best-fit forecasting method for this issue. The development of a forecasting computer system is the outcome of this joint research project with CTEEP Transmissao Paulista.
Keywords
artificial intelligence; fuzzy logic; fuzzy neural nets; load forecasting; power transmission planning; CTEEP Transmissao Paulista; artificial intelligence techniques; computer system forecasting; energy transmission system planning; fuzzy logic; neural networks; short-term load forecasting; wavelets; Artificial intelligence; Artificial neural networks; Databases; Distortion measurement; Filtering; Fuzzy logic; Load forecasting; SCADA systems; Sampling methods; Wavelet analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Transmission and Distribution Conference and Exposition: Latin America, 2004 IEEE/PES
Print_ISBN
0-7803-8775-9
Type
conf
DOI
10.1109/TDC.2004.1432385
Filename
1432385
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