基于神经网络和小波变换的短期负荷预测方法

Ma Ning, Yunping Chen
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引用次数: 22

摘要

提出了一种基于人工神经网络和小波变换的短期负荷预测新方法。将负荷序列用小波变换映射到子序列上,然后用人工神经网络对子序列进行预测。预报时要考虑天气因素。在对负荷序列的所有子序列进行预测后,就可以组成或重构整个负荷序列。此外,提出了一种新的BP算法来加快训练过程,提高人工神经网络的收敛性。实验结果表明了所提原理的正确性和算法的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An ANN and wavelet transformation based method for short term load forecast
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.
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