Short-term load forecasting using a chaotic time series

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 identifi...

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Bibliographic Details
Main Authors: Michanos, S.P., Tsakoumis, A.C., Fessas, P., Vladov, S.S., Mladenov, V.M.
Format: Conference Proceeding
Language:English
Citations: Items that cite this one
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Summary: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.
DOI:10.1109/SCS.2003.1227083