Short-term Load Nonlinear Forecasting with High-Embedded Dimensions using Wavelet Decomposing and Chaos Theory

C. Jiang, C. Wang, and Y. Ma (PRC)


Wavelet; Chaos; Load forecasting


: This paper presents a novel technique for electric load forecasting based on wavelet decomposing and chaos theory. By wavelet decomposing, the electric load time series is decomposed into stationary time series and stochastic time series, and AR(n) model be imposed for forecasting stationary time series. By studying chaos characteristic of stochastic time series, this paper put forward a nonlinear chaos dynamics-forecasting model to dispose stochastic time series with high-embedded dimension. The new method can effectively decrease the Lyapunov exponential sum in added dimensions of reconstruction set when the dimensions of reconstructed space are increased. Finally, the forecasting result is reconstructed based on wavelet theory. The method is high precision and feasible through example test.

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