An ANN and wavelet transformation based method for short term load forecast

Author

Ning, Ma ; Yunping, Chen

Author_Institution

Sch. of Electr. Eng., Wuhan Univ. of Hydraulic & Electr. Eng., China

Volume

2

fYear

1998

fDate

3-5 Mar 1998

Firstpage

405

Abstract

A new method for short term load forecast based on an artificial neural network (ANN) and wavelet transformation is presented in this paper. The load series is mapped onto some sub-series with wavelet transformation and then the sub-series are forecast by ANN. Weather factors are taken into account in forecasting. After all sub-series of load series are forecast, the whole predicted load series can be composed or reconstructed. In addition, a new BP algorithm is proposed to speed up the training process and improve the convergence of the ANN. All experimental results show the correctness of the principles proposed and the feasibility of the algorithm

Keywords

backpropagation; load forecasting; neural nets; power system analysis computing; wavelet transforms; ANN convergence; artificial neural network; backpropagation; load series; predicted load series reconstruction; short term load forecast; sub-series; training process; wavelet transformation; weather factors; Artificial neural networks; Convergence; Equations; Load forecasting; Neural networks; Power generation; Predictive models; Temperature; Weather forecasting; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Energy Management and Power Delivery, 1998. Proceedings of EMPD '98. 1998 International Conference on

Print_ISBN

0-7803-4495-2

Type

conf

DOI

10.1109/EMPD.1998.702587

Filename

702587