DocumentCode :
2752331
Title :
Short-term load forecasting using a chaotic time series
Author :
Michanos, S.P. ; Tsakoumis, A.C. ; Fessas, P. ; Vladov, S.S. ; Mladenov, Valeri M.
Volume :
2
fYear :
2003
fDate :
0-0 2003
Firstpage :
437
Abstract :
A new approach to short-term load forecasting (STLF) in power systems is described in this paper. The method uses a chaotic time series and artificial neural network. The paper describes chaos time series analysis of daily power system peak loads. Nonlinear mapping of deterministic chaos is identified by multilayer perceptron (MLP). Using embedding dimension and delay time, an attractor in pseudo phase plane and an ANN model trained by this attractor are constructed. The proposed approach is demonstrated by an example.
Keywords :
chaos; load forecasting; multilayer perceptrons; time series; ANN model; artificial neural network; chaotic time series; delay time; deterministic chaos; embedding dimensions; multilayer perceptron; nonlinear mapping; power system peak loads; pseudo phase plane; short-term load forecasting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Circuits and Systems, 2003. SCS 2003. International Symposium on
Print_ISBN :
0-7803-7979-9
Type :
conf
DOI :
10.1109/SCS.2003.1227083
Filename :
5731316
Link To Document :
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